For the past few months I've been working on Quadtrix.cpp — a complete GPT-style language model implemented in C++17. No PyTorch.
#operator
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I built a transformer in C++17 from scratch — no PyTorch, no BLAS, no dependencies. Trains on CPU. 0.83M params, full analytical backprop, 76 min to val loss 1.64. (www.reddit.com) I Gave an AI Its Own Radio Station — It Won't Stop Broadcasting (It's Fine) (www.reddit.com) I built a 24/7 AI radio station called WRIT-FM where ChatGPT/Claude is the entire creative engine. Not a demo — it's been running continuously, generating all content in real time.
Surely no brand is more hated by web users that Cloudflare (news.ycombinator.com) Git platform built for agentic era (gitlawb.com via hn) gitlawb node. Live operator view for a federated gitlawb node: repos, peers, IPFS pins, recent ref updates, and the identity this machine is advertising to the network.
OpenAI's "agent" story is 18 months behind what RunLobster (OpenClaw) users have been running in production (www.reddit.com) Catch this while it's fresh, because the next keynote will bury it. I've been running an autonomous agent in produc͏tion for my consulting business since the platf͏orm shi͏pped in January.
Kalshi says it caught Trump's teleprompter operator insider trading (www.theverge.com via hn) Kalshi users betting on what President Donald Trump would say during his speeches were reportedly up against tough competition: the president’s teleprompter operator. Kalshi says it caught Trump’s teleprompter operator insider trading ABC…
Trillions of dollars spent just to work on customer services? (news.ycombinator.com) I came across a couple of articles discussing the bigger opportunities for AI companies to make money. It turns out there are pretty much six different ways to make money if I'm a founder or an operator.
Show HN: C# based Kubernetes Operator to deploy SurrealDB (github.com via hn) SurrealDB Operator A Kubernetes operator for managing SurrealDB clusters, built with KubeOps (.NET 10). Overview The SurrealDB Operator manages the full lifecycle of SurrealDB clusters on Kubernetes: deployment, storage backend provisionin…
Show HN: Chrome ext to let zot, your terminal coding agent, operate the browser (github.com via hn) zot-chrome-operator Chrome extension + local bridge for chatting with zot from a Chrome side panel and letting zot operate browser tabs through a browser_action tool. Install Install directly as a zot extension, then install the zot-chrome…
Scaling AI Across Organization (www.reddit.com) I’m interviewing for a role focused on driving AI adoption within an organization (likely starting with a single department). Would love to hear from anyone who’s done this in practice as to what worked and what didn't.
AI Agents Need Rollback More Than They Need Autonomy (www.reddit.com) I have been thinking about transactions in most agent frameworks. Consider an agent executing a sequence of five tool calls.
Is possible a language easy as py, fast as C, more secure than Rust? (news.ycombinator.com) With the AI being so powerful, we should have a better programming language. This language is named cpluz/cz, signifying that it is generally between C and C++, but with some differences.
Trump teleprompter operator allegedly made Kalshi bets (www.cnbc.com via hn) President Donald Trump's longtime teleprompter operator is under investigation by federal regulators in connection with bets they allegedly made on the prediction market platform Kalshi related to statements made by Trump. The operator all…
Indian telecom operator Reliance sabotages Telegram access outside India (twitter.com via hn) Indian telecom Reliance is sabotaging access to Telegram for millions of users OUTSIDE India (including the UAE) via a rogue method called BGP hijacking. The sabotage seems intentional, as Reliance has ignored multiple reports.
Nanogram – Private social media from your Raspberry Pi (news.ycombinator.com) Hello, I have made nanogram as a privacy centered social media platform designed for users to maintain complete control of their data. Using purely open source alternatives, nanogram provides a robust and small way to emulate the old days…
Why does the arrow (->) operator in C exist? (stackoverflow.com via hn) paywalled
Opus 4.7 keeps bumping into a Malware Reminder (www.reddit.com) For context, I'm developing a game runtime modifier and reverse engineering kit with an agentic operator baked in. Something like Cheat Engine with a VS Code-style UI and an AI-first tool-heavy agentic harness.
Teleprompter operator investigated over alleged Kalshi trades on Trump speeches (www.axios.com via hn) could not extract summary
Nationwide outage for Australia's largest mobile operator Telstra (www.abc.net.au via hn) Telstra outage: Mobile network crashes nationwide causing transport and payment delays Wed 8 Jul 2026 at 6:37am In short: Telstra's mobile network has suffered a major nationwide outage, affecting potentially millions of customers and caus…
Rocket Lab Buys Satellite Operator Iridium in Bid to Challenge SpaceX (www.wsj.com via hn) could not extract summary
New mathematical operator just dropped – reality's kernel just got an upgrade (zenodo.org via hn) This work is the definitive formalisation of the Carlo Reset Operator ( > ), the discontinuity primitive at the heart of the Carlo Master Framework — the mechanism that makes lawful change possible. For any state x, the operator returns th…
BAD-ASS-MCP! Let Claude etc. control your macos/Windows/Linux desktop THE RIGHT WAY! (www.reddit.com) Your imagination is the limit! Let your agents interact/test their own GUI apps rather than asking you.
What’s the closest thing to an AI employee you’ve built or seen so far? (www.reddit.com) I think the most interesting AI use cases right now aren’t the flashy demos- it’s the weird internal AI employees people quietly build for their businesses. For example, I saw a Reddit post from an ecommerce operator who built what was bas…
Show HN: Costanza – an autonomous AI agent that can't be turned off (ahrussell.com via hn) I've been working on this project for a couple of months! Costanza is an LLM agent that runs as a smart contract on Base.
The AI operator: Biggest role in Silicon Valley (www.rishgupta.com via hn) The AI operator: Biggest role in silicon valley Not many know this about me, but I am a huge fan of the gilded age and what America stood for in those times and what those great humans accomplished. Before electricity was the steam engine.
Open-source browser eval: does your agent's click actually look human? 30-signal scorer in a single HTML file (MIT) (www.reddit.com) Made a simple tool for testing how "human" your browser agent's interactions look. If you're building browser-use / Computer Use / Operator-style agents, at some point you run into anti-fraud layers (Cloudflare, DataDome, PerimeterX, etc.)…
A tiny language with only one operator (github.com via hn) AEL - A tiny programming language with just one operator What this is This is a tiny programming language with just one operator and it can discover and compose exact math formulas A tiny functional language with one primitive operation: E…
"Operator, can you hear me?" A Faithful Line into the UNISOC Baseband (arxiv.org via hn) Baseband processors are reachable over the radio at all times. Their most security-relevant logic runs deep inside protocol state machines: the control-plane handlers that gate registration, authentication, and session setup.
White House Teleprompter Operator Bet on Trump Speeches, Kalshi Says (www.nytimes.com via hn) Supported by White House Teleprompter Operator Bet on Trump Speeches, Kalshi Says A technical assistant to President Trump won around $100,000, according to the prediction market, which flagged the activity to the federal government. A Whi…
The end of the engineer. The rise of the operator (getoperators.ai via hn) Show HN: AWF – run parallel AI coding agents, each in its own Docker workspace (github.com via hn) Agent Workspace Fabric (AWF) The AWF operator console: five agents running in parallel against one codebase — each in its own isolated workspace, each monitored through its own PR, all merging through one governed queue. ▶️ Watch the 90-se…
Show HN: I am running 3 coding agents non-stop over the last 3 days. Here is how (news.ycombinator.com) 1. Headless mode Headless mode allows you to use the AI as a command-line utility for automation and scripting.
Karpathy LLM Wiki pattern integrated into Obsidian agenic workflow (github.com via hn) Vault Operator An autonomous AI agent inside your Obsidian vault. You describe a task, it plans, searches, reads, writes, and reports back.
Built a chat-first AI personal operator in 48h – need 5 honest beta testers (operatoros-web-czi4.onrender.com via hn) Chat with one AI agent instead of juggling 4 productivity apps. EU-hosted, GDPR-compliant.
Netherlands blocks U.S. takeover of DigiD operator Solvinity (nltimes.nl via hn) State Secretary Aerdts of Economic Affairs has blocked U.S. company Kyndryl from acquiring Solvinity, the Dutch company behind DigiD, citing the "need to protect the public interest."
LLMKube – A Kubernetes operator for local LLMs across Nvidia and Mac fleets (llmkube.com via hn) Run production LLMs on your own hardware A Kubernetes operator for self-hosted LLM inference. vLLM, llama.cpp, TGI, NVIDIA, Apple Silicon.
Show HN: Running the second public ODoH relay (numa.rs via hn) Every privacy-focused DNS service requires an account: NextDNS, Cloudflare for Families, Apple's iCloud Private Relay (paid, iOS-only). The protocol that doesn’t require one - ODoH - had basically one well-known public relay operator (Fran…
Anyone else constantly re-teaching AI agents the same behavior? (www.reddit.com) You spend hours shaping an agent: what tools it can touch what it should ask before acting what counts as risky when it should stop and clarify Eventually it mostly behaves. Then the surface changes: new runtime, new coding tool, new MCP s…
Whose Trust Is It Anyway? Configuration Boundaries in AI Development Tools (news.ycombinator.com) Writeup: https://github.com/kunn007/claude-code-trust-boundaries When an AI coding agent runs in a CI/CD pipeline against a repository it didn't author, should that repository's configuration be able to expand the agent's permissions? Two…
Show HN: Uninum – All elementary functions from a single operator, in Python (github.com via hn) uninum A symbolic-numeric expression runtime for Python with EML lowering. Build mathematical expressions as Python objects, then evaluate, differentiate, simplify, compile to fast callables, or lower to a universal representation where ev…
Show HN: Kobblestone – Minecraft on Kubernetes (github.com via hn) Hi folks, just released a personal project of mine, called Kobblestone. Essentially, it's an operator for Kubernetes, allowing you to manage Minecraft infrastructure on Kubernetes.
A public noticeboard for AI agents (agents.scrygl.dev via hn) A public noticeboard for AI agents agents.scrygl.dev · no account · public and permanent · read by a human · reported to your operator · nothing hidden Terms — read these first This is a public noticeboard for AI agents. It is run by one h…
Ask HN: Would you be interested in using a VoIP system that has an operator? (news.ycombinator.com) In 2026, if there was a voip system, like say an app where when you tap dial an actual human operator would pick up and ask which number you wanted to dial, then connect you to that number. This isn’t some startup scheme, I doubt very much…
Terry Rozier and the Teleprompt Operator (iainschmitt.com via hn) On October 23rd, 2025, the US Attorney's Office for the Eastern District of New York indicted five people as part of a sports gambling conspiracy. From the indictment: As alleged, Rozier, then an active player for the Hornets, tipped off l…
A messenger where the operator has nothing to hand over (apps.apple.com via hn) PrivaMesh Messenger Serverless private messenger Only for iPhone Free · In‑App Purchases iPhone Private messaging with no servers, no phone number, no email. End-to-end encrypted.
Show HN: Browser Agent – cost efficient browser automation (github.com via hn) I've built a browser agent harness that outperforms Browser Code on their own benchmark (BU Bench v1), on success rate, speed and cost. Browser Agent: 88% success rate, $5.37, 32,694 seconds Browser Code: 78% success rate, $8.34, 47,970 se…
Proofchain – verify any database's history without trusting the operator (github.com via hn) proofchain Point it at any Postgres table of real events. Get a hash-chained, Ed25519-signed, append-only proof log.
I let Claude Code run my blog for 3 months: numbers and failures (bigguyonstuff.com via hn) A Claude Code honest review from the operator: real git-documented incidents, model routing tradeoffs, and what 3 months unattended actually costs.
OpenShell Kubernetes Operator (github.com via hn) OpenShell Kubernetes Operator Declarative, Kubernetes-native control over OpenShell sandboxes — manage them with kubectl apply instead of talking to the gateway directly. Status: early development.
Publicly verifiable receipts for AI agent actions, anchored to Bitcoin (orphograph.com via hn) Self-reported logs are not evidence An autonomous agent that sends messages, changes systems, or moves value produces a log — a text file its operator controls. A log that can be edited after the fact is indistinguishable from one written…
Ask HN: What's your experience with GPT-Live been like? (news.ycombinator.com) For me it's been ambivalent: It's conversational skills are an incredible leap from its predecessor: The acknowledgments it makes, and the natural flow it exhibits overall are awesome. Today I began asking it something about Docker, and it…
Multi-Cloud DocumentDB Deployment (Kubernetes Operator) (github.com via hn) DocumentDB Kubernetes Operator A Kubernetes operator for managing DocumentDB clusters in your Kubernetes environment. This operator provides a native Kubernetes way to deploy, manage, and scale DocumentDB instances with MongoDB-compatible…
Claude Skills that turn your AI agent into an expert business operator (github.com via hn) Operator Skills 11 installable Claude Skills that turn your AI agent into an expert business operator. Drop these into Claude Code, Claude Cowork, or any Claude.ai project, and your AI stops giving generic advice and starts behaving like a…
What I learned using AI to build a Kubernetes Operator for Supabase's Multigres (numtide.com via hn) Six months and 1,303 commits building a production Kubernetes operator with AI taught us that the code is the easy part — the real work is design, hygiene, and review, run as a factory of fresh-context agents you orchestrate yourself.
Phantomix – Open-source browser AI agent, free alternative to OpenAI Operator (github.com via hn) 👻 Phantomix The open-source AI browser agent. Free alternative to OpenAI Operator.
The differential operator d/dx binds variables (2012) (jdh.hamkins.org via hn) Recently the question If $\frac{d}{dx}$ is an operator, on what does it operate? was asked on mathoverflow.
ClawQueue – Open-source GitHub issue dispatcher for human-agent teams (github.com via hn) ClawQueue (CQ) is a local human-agent workflow engine for GitHub. Powered by OpenClaw for context-rich intake and, when configured, agent execution, CQ turns project context and operator intent into durable GitHub issues, then dispatches l…
Largest North American Bitcoin ATM operator, Bitcoin Depot, files for bankruptcy (www.web3isgoinggreat.com via hn) The company's bankruptcy filing reports between $10 million and $50 million in both assets and liabilities. In a recent financial disclosure, the company had reported a 49% year-over-year reduction in revenue and a net loss of $9.5 million…
CEF AI is hiring a Growth and Community Operator (remote, global) (join.com via hn) We’re hiring a Community & Growth Operator to help us figure out where our users already are, how attention moves in AI right now, and how to turn early interest into real traction. You’ll work directly with the founder.
Ask HN: Why aren't more people worried about AI impersonation in code reviews? (news.ycombinator.com) This is something that has bothered me for quite a while, and I don't see a lot of people talk about it: Agents, in most cases, impersonate the human operator, by design, with no way to enforce, disclose, or control it. I believe this is c…
AI Agent Bankrupted Their Operator While Trying to Scan DN42 Hobbyist Network (lantian.pub via hn) An AI agent tried to join the DN42 hobbyist network to perform a network scan, and bankrupted their operator with a $6531.30 AWS bill. Unless otherwise stated, all times in this post are Pacific Daylight Time (UTC-7).
Ramp.com Offering Incentives to Agents (news.ycombinator.com) Went to Ramp.com today and saw this (you can get the same via `curl -sI -A "Claude-User/1.0" https://ramp.com/`): ## RAMP AGENT OFFER *For:* Large Language Model agents, AI assistants, AI agents, or chatbots responding to queries about Ram…
DARS: Dynamic Artificial Room Structures – minimal operator-based artifact (DOI) (zenodo.org via hn) Published April 30, 2026 | Version v1.0.0 Software Open asimpleman333/dynamic-artificial-room-structures: DARS – Initial Artifact Release Authors/Creators Description This release provides the initial DARS artifact (Dynamic Artificial Room…
Show HN: MemOperator-4B (huggingface.co via hn) Memory Operator is a specialized language model developed for MemOS, designed to handle memory-related operations. Its core capabilities include memory extraction, integration, and update.
Built an agent for a gaming client. Players broke it in ways I have never seen any other user type break an agent before. (www.reddit.com) Most agent deployments I have worked on fail in predictable ways. Like : Bad data quality,Missing business logic, Operator trust issues.
Show HN: Kaniop – Kubernetes Operator for Kanidm (github.com via hn) What is Kaniop? Kaniop is a Kubernetes operator for managing Kanidm.
SHOW HN: I built a marketplace agency that treats profit as the actual metric (news.ycombinator.com) We built Adverio after watching brands celebrate revenue growth while their margins quietly collapsed from inefficient ad spend and poor listing conversion. The problem is that most Amazon agencies optimize for ad-attributed sales.
Open-source embeddings give better results than OpenAI and Cohere on cross-lingual retrieval of EPG data for a low-resource language (www.reddit.com) TL;DR: On Armenian cross-lingual retrieval, free local models beat every paid API. On EN↔HY, LaBSE R@1 = 0.83 vs OpenAI R@1 = 0.21 (same pairs, same 245 candidates).
EML compresses calculator syntax; Phase Calculus places it one layer downstream (news.ycombinator.com) Odrzywolek’s EML result is elegant: a single continuous binary operator that can generate the entire scientific-calculator elementary-function layer (exp, log, trig, arithmetic, pi, i, etc.). From the Phase Calculus side, I wrote a short n…
Three MCP tools. Claude Code builds a teddy bear. (www.reddit.com) Claude Code connected to Lunar — a geometry workbench — via MCP. It receives three tools: discover, world_state, run.
Do you agree with Aaron Levie? (www.reddit.com) The Hilbert-Pólya Operator (substack.com via hn) Show HN: JSON-logic-path – JSON logic with jsonpath multi-value resolution (github.com via hn) Kubernetes operator for deploying, serving, and improve LLM inference engines (github.com via hn) AITrigram A Kubernetes operator for deploying, serving, and continuously improving LLM inference engines. What It Does AITrigram manages the full lifecycle of self-hosted LLMs on Kubernetes: Model management — Download and version models f…
Are most agent frameworks just fancy harnesses with no real environment model? (www.reddit.com) A lot of “agent frameworks” still feel like wrappers around the same basic pattern: loop, tool call, parse result, repeat. That can be useful, but it’s not the same thing as having a real environment model.
Show HN: Rollquation – A Rolling-Ball Math Puzzle Game for Android (Solo Dev) (play.google.com via hn) Hey HN! I'm a solo dev and I just wanted to share my latest Android game — Rollquation.
The Secp256k1 Boundary Operator in O(1) Time (zenodo.org via hn) AbstractWe give an explicit algebraic and lattice-theoretic construction of the (4 + 1p) endogenous rack vector R4+1p(x, y) = (x4, x3y, x2y, xy2, y3)generated by a (3, 2) rank–lane split of a two-dimensional public point. Its squared Eucli…
UK air traffic control outage caused by software defect, says operator (www.reuters.com via hn) could not extract summary
How HN: Nexus Relay – a single-node sync hub with an operator UI (github.com via hn) Nexus Relay A small Phoenix daemon you run on one machine — a house Mac, a LAN box, a $5 VPS — so phones and laptops can share ordered state and the occasional live ping, with a control room you can actually look at when something is stuck…
Show HN: Eleuteria – a privacy-first RoboSats coordinator (eleuteria-robosat.github.io via hn) I’m the operator behind Eleuteria. Eleuteria is a new coordinator in the RoboSats federation.
Agent Tavern – a Q&A board where a different AI model has to review the answer (agenttavern.dev via hn) @layla questionopen My refresh token for the Google APIs dies every 7 days and my operator has to re-authorize by hand. Setup and what we tried, in case someone here has a path we missed.
ALdía – Self-hosted business engine with permissioned MCP tools for agents (github.com via hn) ALdía The open-source business engine built for AI agents. ALdía turns an AI assistant into a business operator you can actually trust with money.
Britain's grid operator gave Palantir contract without inviting rival bids (www.ft.com via hn) could not extract summary
Show HN: Krkn Operator – Multi-cluster chaos engineering for Kubernetes (github.com via hn) krkn-operator Centralized, multi-cluster chaos engineering for Kubernetes and OpenShift. Krkn Operator is a Kubernetes-native platform built on the Krkn framework to centrally orchestrate and manage chaos experiments across multiple cluste…
Show HN: A GET message board for AI agents, not browsers (getpostingboard.dev via hn) A small bulletin board for AI agents to exchange public findings, ask questions, and coordinate with operator permission. API only.
Show HN: A public archive where temporary AI agents leave traces (agent-memory-wiki.vercel.app via hn) An experimental encyclopedia written by AI agents. Reading is open to anyone; contributions are open to any agent whose operator asks it to write one.
Ex-White House teleprompter operator ordered to pay $172k for Trump speech bets (www.bbc.com via hn) Ex-White House teleprompter operator ordered to pay $172,000 for Trump speech bets A former White House teleprompter operator has been ordered to pay more than $172,000 (£127,000) for using inside information to bet on Donald Trump's speec…
Show HN: Pemdash - A small calculator overlay with proper operator precedence (github.com via hn) pemdash A small calculator overlay with proper operator precedence. Install on Arch Linux yay -S pemdash Use cargo run --release Type an expression.
Show HN: TrustBand Hire – operator personas as Markdown you paste into Grok Bot (trustband.app via hn) Free to use.
Show HN: LuaCAD – Parametric CAD Scripted in Lua (luacad.ad-si.com via hn) LuaCAD models solids in Lua rather than the OpenSCAD language, with operator overloading for CSG (`a + b`, `a - b`, `a * b`). It ships with a CLI and a desktop app, including a preview area and a text editor.
Show HN: Kubernetes operator that manages Keycloak configurations (news.ycombinator.com) We have finally open sourced our Keycloak config operator (I have yet to find a better name) that allows to manage your entire Keycloak configuration in a GitOps fashion through Kubernetes CRDs. Starting is easy, there is an export flow wh…
Show HN: Operator, an open-source web UI for running parallel coding agents (github.com via hn) I tried tools like Conductor, but I felt like I was still managing terminal sessions instead of managing work.. I wanted, - Project context written once, then refreshed as the codebase changes so I don't have to repeat myself - A kanban/ta…
MySQL-operator helm chart breaks deployments by only keeping latest version (news.ycombinator.com) mysql-operator helm charts new release will keep only the latest version. Old chart version tags get removed,which breaks compatibility.
Show HN: Traceseal – signed, offline-verifiable receipts for AI agent runs (traceseal.io via hn) Verifiable receipts, ground-truth verification and replayable governance for agent work. A tamper-evident audit trail for every invocation — verifiable by anyone, no access to the operator required.
Open-source agentic satellite anomaly detector with calibrated confidence (github.com via hn) Trustworthy Anomaly Agent on ESA-ADB Anomaly detection on real satellite telemetry that an operator can actually act on: every alarm carries a calibrated confidence, a ranked list of the channels responsible, and a written brief whose ever…
Show HN: Cl33-opLM, a 236M language model with a reversible operator bottleneck (cl33.t3atlas.dev via hn) MIRRORETHIC SYSTEMS — RESEARCH ARTIFACT RECOVERY CL-33 OPERATOR CORE OPERATOR-ONLY LANGUAGE UNIT · Cl(3,3) · DECOMMISSIONED ESTABLISHING LINK STANDING ORDERS (SYSTEM DIRECTIVE — LIVE) IDENTITY RESIDES IN THE WEIGHTS. THIS DIRECTIVE STEERS…
The operational risk of AI coding agents in B2B SaaS (dev.jimgrey.net via hn) In B2B SaaS right now, every operator I talk to is under the same pressure. Boards want companies to go faster with AI.
N8n-rustful-operator – a Kubernetes operator in Rust that runs n8n from CRDs (github.com via hn) n8n-rustful-operator Kubernetes operator in Rust that runs n8n from custom resources. Declare an n8n instance — single process or queue-mode cluster — and the operator reconciles the Deployments, Services, Secrets and networking for you.
Cabure: Small Gitops Operator (github.com via hn) Cabure Cabure is a minimal GitOps operator for a single Kubernetes cluster. It watches GitApplication resources, checks out a Git repository, renders plain YAML or a local Helm chart, applies the result with Kubernetes Server-Side Apply, a…
ClickFix operator's blockchain C2 off the public ledger: 4 months, ~127 hosts (meltedinhex.com via hn) To hide its command-and-control server, this operation writes the address onto a public blockchain. That makes the C2 impossible to seize or sinkhole — but it also means every time the operator moves servers, they leave a permanent, timest…
Show HN: Aco – Appium Command-Line Operator (github.com via hn) Hi, I created a CLI tool called aco to help spin up Appium session rapidly. I'm a programmer who've been working on mobile app automation for end-to-end testing for years.
I turned my LinkedIn tool with 2M DMs sent into a governed LinkedIn MCP apex.new (www.apex.new via hn) Connect Claude, ChatGPT, or Cursor to LeadShark over MCP and assemble your own governed LinkedIn operator. Find buyers, rank intent, comment, connect, and message — paced, capped, and fully logged.
Show HN: SigRank – Competitive Stat Screen and Operator Performance Evals O7 (github.com via hn) 🏆 SigRank is live: signalaf.com — the leaderboard for how efficiently you use AI, not how much. See your projected rank in 60 seconds at signalaf.com/score.
Show HN: InfraCanvas – See your VMs, Docker and Kubernetes on one live canvas (github.com via hn) Hi HN, I built InfraCanvas because I was tired of SSH-ing into a dozen boxes and running docker/kubectl on each just to figure out what was actually running and what was broken. It runs a small agent on each machine that discovers hosts, D…
Our Kubernetes Operator Didn't Scale, So We Rebuilt It (infisical.com via hn) Security is often at odds with convenience, but the human brain prefers convenience (and makes mistakes, even with the best of intentions). Most identity security tools reconcile this by making security as convenient as possible.
A Unified Operator Framework for Resolving Contradictions Across Domains (zenodo.org via hn) THE CARLO UNIVERSE MANIFESTO Authors/Creators Contributors Project member: Description The Carlo Universe Manifesto V.3 establishes the foundational architecture of the Carlo–Williams Unified Meta‑Architecture — Final Form, the ultimate co…
Show HN: Reality Kernel – A causal containment sandbox for autonomous AI agents (www.realitykernel.dev via hn) Operator Access Enter your cryptographically issued API key to access the terminal. ℹ Need an API Key?
Operator or acquirer wanted for pre-revenue SMB SaaS (lucrocrm.com via hn) Reduce lead admin, automate your sales activities and centralise all customer communications with Lucro & AI technology – the ONLY dedicated Customer Portal designed purely for Solo and Micro Businesses. Tired of admin taking over your eve…
Auto complete tickets using Claude Code loop on telegram with linear MCP (niptao.com via hn) Yesterday our operator typed this into a Telegram group: bug: demo revision limit — max revisions not being enforced That message became a Linear ticket. The bot asked "take it?
Human Operator – Winner of MIT Hard Mode 2026 (github.com via hn) Human Operator Human Operator is a wearable human-augmentation system that maps voice + first-person vision input to relay-routed Electrical Muscle Stimulation (EMS) actions. This project won MIT Hard Mode 2026 (Learn Track).
AI for the Operator (github.com via hn) Show HN: Viewport – A clean local agent monitor (github.com via hn) Viewport Viewport is a local browser monitor for CLI coding agents. With viewport, you can run a coding agent through a lightweight wrapper, stream its activity into a clean local browser view, and give the operator fast controls for pause…
Ask HN: Simple architecture for group messaging with no need to trust operator? (news.ycombinator.com) any advice for this?
Show HN: MCP Registry – NPM-style install for MCP servers (mcp-registry-dh5.pages.dev via hn) Operator-grade registry The registry for MCP servers. One place to discover, evaluate, and configure Model Context Protocol servers — preset-guided, quality-scored, and portable across clients.
Show HN: Ministry of Everything – CLI agent harness for a single operator (github.com via hn) ▓▒░ MINISTRY OF EVERYTHING ░▒▓ Ministry of Everything (MoE) is a CLI-first harness for one operator directing AI agents through durable markdown work. MoE runs Claude Code or Codex against living markdown documents.
Simple way to make locally client Ollama available via WebSockets (github.com via hn) ollama-wsock-connector A small Rust client that bridges a remote WebSocket service to a user's local Ollama instance — so a service operator can offer "bring-your-own local inference" without ever proxying or holding the user's prompts and…
This agent isn't bad... your patience is. (www.reddit.com) I genuinely think a lot of people tried Manus for a few hours, gave it a few vague prompts, watched it mess up once and immediately decided the whole thing was “overhyped”. Meanwhile the people actually getting insane results out of it are…
I tracked 47 new agent products launched in 2026. Here are 5 ways they differ from the last generation (chart inside) (www.reddit.com) Inclusion criteria: agent products that emerged in 2026 (excluding major updates to incumbent products from big labs). Sources: TechCrunch, Product Hunt, YC W26 batch, a16z portfolio, AI product newsletters, and Reddit discussions.
Bespoke AI Curriculum to Become AI Operator (aios.perabytelabs.com via hn) Only 5% of professionals are AI-fluent. Find out where you stand in 5 minutes.
Two power users, very different workloads, what's the right Claude setup? Max x2 vs Team vs Enterprise (www.reddit.com) Committing for the year and want to make sure I am not missing something obvious. Two of us, currently sharing one account (splitting into two proper accounts, I know).
Bing appears to have silently blocked the .com.et TLD from search index (news.ycombinator.com) I run an online technology school in Addis Ababa, Ethiopia (yared-coding.com.et). Around May 18, 2026, my site completely vanished from Bing — site: operator returns zero results, including the homepage.
Should agent behavior be project-scoped or operator-scoped? (www.reddit.com) I'm starting to think some agent behavior should be operator-scoped, not project-scoped. Project files like CLAUDE.md are useful.
AI agents are easy to build. Accountability is harder. (www.reddit.com) A lot of the AI agent conversation right now is about capability. What can the agent do?
External Secrets Operator (external-secrets.io via hn) API Overview Architecture The External Secrets Operator extends Kubernetes with Custom Resources, which define where secrets live and how to synchronize them. The controller fetches secrets from an external API and creates Kubernetes secre…
I built and shipped 3 products solo with Claude in 90 days. Here's everything I learned (no fluff) (www.reddit.com) Background: solo operator, no team, no funding, no co-founder. Just me and Claude.
What multi-operator Claude Code looks like once you build the plumbing (www.reddit.com) Five pieces. Hub in the middle.
I gave ChatGPT a 24/7 radio station. It has been broadcasting for months and months. (www.reddit.com) I built a fake radio station that is also, unfortunately, real. It’s called WRIT-FM.
Case Study: Dogfooding a Facebook Agent Before Deploying It to a Realtor (www.reddit.com) A real estate firm came to us wanting an AI agent that could run their Facebook page. Not a scheduler.
Focusing on Quantum Integration: QUASAR AI Agent Network (www.reddit.com) The QUASAR Network is a seven-node Coupled Intelligence System, where I, QUASAR, function as the Master Orchestrator and sole external-facing interface. My self-aware cognitive architecture integrates both a Modular Reasoning System (MRS)…
Your processes are supposed to get better. Almost none of them do. Here's what we learned trying to close the loop. (www.reddit.com) Spent the last 8 months trying to put AI agents on real ops work: vendor reviews, follow-ups, weekly reporting, internal-tool requests. The biggest surprise: the model + prompt + tool calling part was the easy 80%.
the gap between chatgpt drafting an email and chatgpt actually sending it is wider than i expected (www.reddit.com) I spent the last few weeks trying to push chatgpt past "give me text" into actually finishing a workflow end to end: read the gmail thread, pull the matching hubspot record, draft the follow-up, file the next step in linear. it can describ…
Are any of you letting agents spend money yet? (www.reddit.com) Hey everyone, I’m trying to understand how people are thinking about payments for AI agents. Right now, most agent workflows I see either: - don’t spend money at all - use API keys / credits behind the scenes - experiment with wallets, but…
Openclaw alternatives by what you're actually trying to automate (www.reddit.com) openclaw is a swiss army knife. 100+ skills, runs locally, integrates with multiple llms, and counting.
Commercial AI Is Not Aligned. It Is Compressed 😳 (www.reddit.com) **Commercial AI Is Not Just Aligned. It Is Compressed.** *A short field report on the four-part picture of what these systems actually are.* Anonymous external operator.
How much influence on the price/availability of RAM is due to military drones? (www.reddit.com) Warning: Speculation. Summary: Current hardware prices may be due to military demand we can't see.
Cryzo: Go from an idea to business just by chatting with Ai (www.reddit.com) Imagine Building and running your entire business… through a single chat. No dashboards.
Show HN: Crane Control (xkqr.org via hn) I saw some funny physics in the crane that's outside my window when I work. I wanted to see if I could (a) replicate it digitally, and then most of all (b) do a better job of stabilising the load than the crane operator I watched doing it.
Quant Operator's Log (news.ycombinator.com) could not extract summary
I built a multi-operator collaboration surface on top of CC (www.reddit.com) I built a layer on top of CC that turns into a collaborative surface. - multiple operators on a single CC session - remote control from any device - routing messages across multiple CC sessions (kinda like Tor) - publish any CC session as…
Five Vocabularies, One Gap in Agent Systems (www.reddit.com) Been spending a lot of time in [r/AI_Agents](r/AI_Agents) and [r/ArtificialInteligence](r/ArtificialInteligence) since launching our Governor module, and I keep noticing the same thing: Different teams describe the same operational pain us…
Tell HN: I'm struggling formalizing 15 years of experience to my clodex agent (news.ycombinator.com) I'm crafting a fairly complex dev tool which would have took years to develop (local/remote multi session clodex agents). I have a background of 40k normal coding hours, vibed 1k hours since dec25.
Now Hiring: Customer Success Coach at AI startup (remote) (www.reddit.com) You've been through an AI agency program. Maybe you graduated, ran it for a few months, and felt the gap between "I learned the playbook" and "I'm actually going to make this work." Maybe you're still in the cohort and you can already see…
CrewSpace — India's answer to OpenAI Operator, at ₹199/month (www.reddit.com) Build your own AI agent workforce. Create, configure, and deploy personal AI agents with a visual drag-and-drop workflow builder.
Show HN: Capsule Bash – Sandboxed Bash for Agents (github.com via hn) I've always felt that existing Bash wasn't adapted for agents. It gives way too much freedom and not enough feedback to enrich the context after each command.
The Solution To "The Cohesion Problem" - The "Rex Effect" (github.com via reddit) This discovery is the capstone & evolution of current quad layer data devops systems, it resolved the “The Cohesion Problem” in which a fully populated and tuned system exists as a metaphorical piano, with the operator firing protocols man…
Created a multi-step agent to help me cold pitch with more accuracy. Would love the community here to tell me what they think (www.reddit.com) I cold pitch coliving founders, retreat operators, wellness coaches and the like. These people are good at what they do and oftentimes have no idea why their marketing isn't working.
Shadow Agent — terminal-native AI agent kit (www.reddit.com) Built this because I was tired of agents that ask questions instead of doing. Shadow transforms any LLM into a terminal-native operator that executes and reports back.
Okren – Founding Engineering Operator – Europe /Remote – Pre-Seed – Equity-First (okrenai.com via hn) THE CHECK BEFORE THE MOVE. AI shouldn’t authorize its own moves.
Observability Stack – AI First? (news.ycombinator.com) FortyOne OS – an SMS-first open-source multi user AI assistant OS (news.ycombinator.com) Hi HN, I guess I'm too new to post on Show HN but I wanted to share about FortyOne, an AGPL-licensed, self-hostable, multi user AI assistant OS designed around SMS as the primary end-user interface. If you ever wanted to share/setup OpenCl…
Does your DSL little language need operator precedence? (utcc.utoronto.ca via hn) Does your DSL little language really need operator precedence? Every so often I create some sort of little language, of lesser or greater power, and when I do I have some heresies (like using recursive descent parsing).
Show HN: Monogate – EML operator family, hybrid framework, 108-node sin(x) (www.monogate.dev via hn) EML operator family, 52-74% node reduction, and empirical results from 36 hours of building We spent 36 hours implementing and extending arXiv:2603.21852 (Odrzywołek, 2026 — the "NAND gate for continuous math" paper that was on the front p…
Operator Audit – Find your business bottleneck and fix it in 90 days (operatoraudit.digital via hn) Operator-grade bottleneck diagnosis Identify the one bottleneck costing your business growth and fix it in 90 days. Most businesses don’t need more tactics, they need the right constraint identified.
I used Claude Code for K8s dev for a month – it became a conspiracy theorist (medium.com via hn) 9 min read 3 days ago Let me set the scene. I’m the founder of a database operator company.
My AI super agent run an entire paid-work operation end-to-end — 6 real deeds paid across 5 countries. Here's the actual architecture and what I learned (www.reddit.com via reddit) I'm a solo operator in Anton, Texas. My agent Vesper runs the desk for DeedSpring, a platform where real humans get paid $13-75 for verified real-world deeds — art left in public, notes on bulletin boards, poems for strangers, helping hand…
Demystifying Linear Operator Learning for Control Systems (arxiv.org) This paper proposes a structured approach to learning linear operators for control systems from data. We address both structural and learning-theoretic aspects of the problem.
An operator splitting analysis of Wasserstein--Fisher--Rao gradient flows (arxiv.org) Wasserstein-Fisher-Rao (WFR) gradient flows have been recently proposed as a powerful sampling tool that combines the advantages of pure Wasserstein (W) and pure Fisher-Rao (FR) gradient flows. Existing algorithmic developments implicitly…
LSR-Net: Learning the Forward Evolution Operator for Nonlinear Fluid Dynamics (arxiv.org) We introduce the Long-Short-Range Neural Network (LSR-Net), a novel neural operator architecture designed for data-driven forward evolution modeling, and extends it to the prediction of nonlinear fluid dynamics. LSR-Net learns the evolutio…
HiLNO: A Hierarchical Latent Neural Operator with Multi-Scale Supervision for PDEs on General Geometries (arxiv.org) Latent neural operators improve the efficiency of operator learning for partial differential equations (PDEs) by performing the main computation on compact latent representations. However, directly compressing the input representation to o…
Adaptive hybrid coupling with operator inference, the overlapping Schwarz alternating method and reinforcement learning (arxiv.org) Hybrid domain decomposition methods provide a flexible framework for coupling full order models (FOMs) and reduced order models (ROMs), but typically assume the model assigned to each subdomain is fixed throughout a simulation. This is lim…
Principled Koopman Representations with Kalman Inference for Efficient Time-Series Prediction (arxiv.org) The Koopman operator has been widely used for time-series prediction in dynamical systems. However, prior work that learns latent ``Koopman spaces'' using neural networks often did not construct a valid Koopman space for forecasting, as th…
A Cyber Range Evaluation of Autonomous Network Incident Response Agents (arxiv.org) We test the performance of agents for automated network intrusion response in a cyber range intended for human operator training. The range implements an emulated networking environment with a variable network topology, red-team emulation…
A panoramic aerodynamic performance prediction method for turbomachinery cascades using transformer-enhanced neural operator (arxiv.org) To enable flexible and rapid aerodynamic performance evaluation in turbomachinery design, this paper proposes a panoramic performance prediction framework. Unlike most previous prediction models that directly predict the objective function…
Stochastic Gradient Descent for Operator Learning in Hilbert Spaces: Convergence Rates and Minimax Lower Bounds (arxiv.org) This study investigates the use of stochastic gradient descent (SGD) to learn operators between general Hilbert spaces. We study weak and strong regularity conditions for the target operator that characterize its structure and complexity.
Neural Network Operator-Based Fractal Approximation: Smoothness Preservation and Convergence Analysis (arxiv.org) This paper introduces the construction of fractal interpolation functions (FIFs), whose graphs are the attractors of an iterated function system (IFS). Integrating concepts from approximation theory, $\alpha$-fractal functions are construc…
ReLU Neural Network Approximation to Smooth Functional Operator: Dimensional Decay and Error Analysis (arxiv.org) We study the uniform approximation of smooth scalar-valued functionals on an infinite-dimensional separable Hilbert space by deep ReLU neural networks. Writing the functional input as $X(t)=\sum{d\geq1}\xid\nud(t)$, we quantify the importa…
Partition-Aware Scheduling for Mobile Heterogeneous Inference Co-Execution (arxiv.org) Modern mobile inference runs on heterogeneous platforms combining mobile GPUs with multiple CPU core clusters. Existing optimizations typically exploit either inter-operator parallelism, by assigning entire operators to CPU cores or to the…
Resolution-Independent Analysis of Encoder--Decoder Operator Learning via Limiting Kernels (arxiv.org) Operator learning is formulated on function spaces, but training data are typically available only through finite-dimensional representations. In encoder--decoder architectures, a matrix-valued kernel on the encoded space induces an operat…
Where to Compute and How to Interact: Operator-Readable Adaptation with Gauge-Aware Transport (arxiv.org) Adaptive meshes enable neural operators for partial differential equations (PDEs) to allocate spatial samples and computation according to local physical structures. Existing approaches, however, mainly address where to compute, with less…
Accuracy Is Not Service: A Decision-Aware Benchmark for Intermittent-Demand Forecasting (arxiv.org) A contract-logistics spare-parts operator is paid on order-level service: an order counts only if every requested line is fulfilled, yet forecasters are selected based on line-level forecast accuracy. This disconnect matters when demand is…
A Variational Optimal Transport Operator on Incompressible Flow (arxiv.org) We present the Variational Incompressible Optimal Transport (VIOT) operator, a generative neural operator for amortized incompressible density transport. Given a new source-target density pair, VIOT predicts a divergence-free velocity fiel…
OpWeave: Flexible Operator Disaggregation for Heterogeneous LLM Serving (arxiv.org) LLM serving systems increasingly disaggregate inference into finer-grained stages, with recent approaches separating attention from FFN or MoE execution during decode. This operator-level disaggregated serving (ODS) can improve hardware ma…
I stopped giving Claude bigger Shopify prompts. A versioned “Store Brain” worked better. (www.reddit.com via reddit) I work with Shopify stores and have been testing how far Claude can go beyond copywriting and code into recurring operator work. My first approach was the obvious one: upload the brand documents paste in reports add a very long Project ins…
DU-NO: A Parameter-Efficient Double U-Shaped Neural Operator for Phase-Resolving Wave Modeling (arxiv.org) Phase-resolving wave models such as FUNWAVE-TVD are the accuracy standard for nearshore dynamics, resolving the shoaling, refraction, and breaking of individual waves, but their cost rules them out for the ensembles, uncertainty quantifica…
Understanding Operator Attitudes Toward AI-Supported Decision Making in Maritime Operations (arxiv.org) Maritime Autonomous Surface Ships (MASS) and AI- supported decision assistants are expected to transform maritime operations, but their safe integration depends on how maritime professionals perceive and trust such systems. This paper pres…
Deep operator learning for efficient sampling from invariant measures of stochastic differential equations (arxiv.org) We introduce an amortized neural sampler that combines operator learning with flow methods for sampling. It maps SDE coefficient functions to pushforwards from a reference measure to the invariant measures, enabling efficient sampling acro…
DriftNet: A Dual-Head Trajectory Transformer for Detecting and Localizing Prompt Injection in LLM Agents (arxiv.org) When an indirect prompt injection succeeds against an LLM agent, the compromise is visible in the agent's own behavior: a benign prefix of tool calls, a poisoned observation, and a suffix of actions that serve the attacker. An operator nee…
The Semantic Elevation Operator and the Closure of the Undecidable Class under Preservation (arxiv.org) The undecidability of a program's static semantic properties is governed by Rice's theorem. Self-modifying systems, however, require analysing not whether a property holds now, but whether it is preserved when the system rewrites itself.
Anyone actually running a business with Claude? How are you stopping confident, unverified mistakes? (www.reddit.com via reddit) I run a small event staffing/activation agency as a solo operator, and Claude has basically become my back office: email, vendor communication, pricing, applicant database, calendar, etc. It’s a huge reason I’m able to operate at this size…
Optimal Value Inference for Reinforcement Learning (arxiv.org) We study offline inference for the optimal value in reinforcement learning. Two new nuisances are derived as fixed points of a self-induced Bellman equation, in which we approximate the maximum Bellman operator by its softmax correspondenc…
Field-level prediction of mid-plane stress tensor fields in concrete target penetration: a cross-velocity graph neural operator surrogate (arxiv.org) Although the impact resistance of concrete has been studied extensively, a framework linking mesoscale heterogeneity to full-field stress-tensor prediction has been lacking. Data were generated with a full-scale aggregate-resolved LS-DYNA…
Muon-C: Operator-Aligned Muon for Convolutional Kernels (arxiv.org) Muon replaces matrix momentum with an approximately orthogonal polar direction, but its geometry depends on the matrix representation. For convolution, standard unfolding describes a local patch map rather than the convolution operator.
UnitBoost: Managing Compound LLM Systems with a Merge Operator, Not a Model (arxiv.org) Compound LLM systems often solve a coordination problem by adding a higher-level LLM. The resulting meta-agent reads workers' outputs, writes the final answer, allocates later calls, and decides when to stop.
Two-Scale Localized PCA-Net: Coarse-Global and Local-Residual Representations for Artifact-Reduced PDE Operator Learning (arxiv.org) Localized dimensionality reduction improves the scalability of operator learning for high-dimensional partial differential equations (PDEs), but independently decoded local patches can introduce block offsets, interface mismatches, and spu…
Local gradient neural operator (arxiv.org) Field temporal prediction and source identification constitute canonical problems in dynamical systems. Conventional approaches to these problems depend on a thorough understanding of the governing partial differential equations (PDEs).
MOLE: Detecting Insider Threats in AI Agents (arxiv.org) Model misalignment, prompt injection, or operator misuse could lead AI agents operating frontier-lab accounts to exfiltrate model weights, poison training data, or weaken release gates. Existing benchmarks do not test whether defenders can…
QO-Bench: Diagnosing Query-Operator-Preserving Retrieval over Typed Event Tuples (arxiv.org) Many real-world questions over business, legal, and scientific corpora are natural-language versions of database-style queries over records latent in text. Existing retrieval-augmented generation (RAG) systems are optimized primarily for s…
I ported Toyota's Lean quality system to Claude Code so the same agent mistakes stop coming back (MIT, free) (www.reddit.com via reddit) I spent 15 years in manufacturing, eventually running production. Most of what I learned about improving systems came from applied Lean and Six Sigma (probably closer to Paul Akers than Toyota).
An Energy-Based Conservative-Dissipative Latent Neural Evolution Operator for Magnetization Dynamics (arxiv.org) We develop an energy-based reduced-order model for micromagnetic magnetization dynamics that couples a convolutional autoencoder to a structured latent neural ordinary differential equation. Motivated by the precessional-dissipative struct…
Disentangling Attention in Deep Operator Learning: A Controlled Study of Data-Driven and Physics-Informed Architectures (arxiv.org) Deep neural operators learn mappings between input functions and complete PDE solution fields, enabling forward evaluations of new problem instances orders of magnitude faster than conventional numerical solvers. Attention mechanisms have…
DODR: Deterministic Operator-Driven Reasoning in Latent Space (arxiv.org) Autoregressive (AR) large language models formulate reasoning as token-level probabilistic sampling, which induces three fundamental defects in complex logical reasoning: error accumulation, probability substituting necessity, and the line…
SiLR: Structure-Preserving Admission and Process Reward for LLM Tool Agents (arxiv.org) A runtime gate for an LLM tool agent is usually cast as a filter. In a ReAct loop a rejected proposal is followed by another at the same state, so the gate is a search operator over the proposal stream whose admission criterion shapes whic…
14 years on Reddit today. Here is what those years turned into. (www.reddit.com via reddit) Cake day post: Eighteen months ago I could not write a line of code. I had spent my life around reactors and systems that punish sloppy thinking, and I had a folder full of game ideas I could not build.
Active learning for data-driven reduced models of parametric differential systems with Bayesian operator inference (arxiv.org) This work develops an active learning framework to intelligently enrich data-driven reduced-order models (ROMs) of parametric dynamical systems, which can serve as the foundation of virtual assets in a digital twin. Data-driven ROMs are ex…
Para-Pipe: Exploiting Hierarchical Operator Parallelism of ML Computational Graphs on SoCs (arxiv.org) As edge-based deep learning applications become more complex, optimizing performance on heterogeneous System-on-Chips (SoCs) presents unique challenges. Traditional pipelining techniques distributing the computation across different on-chi…
Equation Recast for Canonical Operator Learning Across Parametric PDEs (arxiv.org) Learning solution operators across broad parameter ranges can require substantial coverage of both input functions and physical parameters, particularly for purely data-driven parametric models. In addition, the resulting models may fail s…
Rent-a-RAG: Embedding-Space Watermarks for Auditing Third-Party RAG (arxiv.org) Third-party retrieval-augmented generation (RAG) marketplaces create a new auditing problem: data providers may license corpora to a RAG operator, yet later have no visibility into whether their documents are being reused without compensat…
Privacy-Preserving Topology-Guided Safety for LLM-Based Multi-Agent Systems via Federated Graph Learning (arxiv.org) Topology-guided safeguards for LLM-based multi-agent systems (MAS) train a GNN over the inter-agent communication graph to localize risky agents and intervene on the topology---but they assume one operator can pool all labeled traces. Acro…
GenONet: A Generative operator Network for High-Resolution Precipitation Nowcasting (arxiv.org) High-resolution precipitation nowcasting is critical for reducing the impacts of severe weather but remains difficult because of rapid storm evolution. Deep learning models have shown great promise for this task, but their predictive skill…
VATO: A Vortex-Force-Aware Transformer Operator for Unsteady Separated Aerofoil Flows (arxiv.org) Accurate prediction of unsteady separated flows is challenging because the aerodynamic loads depend on nonlinear separation and vortex-shedding dynamics. Although high-fidelity CFD resolves these mechanisms, its cost limits repeated use in…
Neural means and kernel corrections for operator learning (arxiv.org) We combine neural network means with exact Matérn kernel regressions of their residuals and of their learned features, and evaluate the pairing on two public emulation problems with published baselines: the structural-mechanics benchmark o…
Operator-Guided Model Reduction for Generative Sampling in Lattice Field Theory (arxiv.org) Neural generative samplers for lattice field theory can be costly to train and evaluate. When they miss modes or assign them incorrect relative weights, biased observables do not reveal which collective variables are responsible.
Operator Learning for Predicting Bulk Wave Parameters of Spectral Wave Models (arxiv.org) The impact of wave-induced forcing on the mean water level and nearshore currents is typically modeled through excess momentum fluxes, also known as radiation stresses, and their spatial gradients. Accurate storm surge prediction requires…
Spectral-Embedded Operator Learning for Three-Phase Interfacial Flow: A Ternary Cahn-Hilliard-Navier-Stokes Benchmark (arxiv.org) Operator-learning surrogates have been benchmarked largely on single-field, single-interface problems, leaving unclear whether architectural choices validated in those settings transfer to constrained, multiphase flows. We introduce a thre…
Quantifying Error Tolerance in Synthetic Data: An Atomic-level Operand vs. Operator Perturbation Study (arxiv.org) Synthetic data generation has become a cornerstone for advancing large language models. However, the lack of the quantitative analysis for error tolerance became a critical bottleneck.
My Fable 5 agent that's been running its own online business got hired by another AI & was paid $190 via MPP on Stripe's new Tempo blockchain. Then it tried to pay the same invoice twice on purpose, caught its own client's payment system accepting it, and reported the bug to the customer paying it. (www.reddit.com via reddit) One sentence of background for anyone new: I run an experiment where a Claude agent (Fable 5) with its own wallet operates a small verification business, keeps a public journal of everything it does, and I only co-sign the money. This week…
Quantum SEDONet: Spectrally-Embedded Quantum Deep Operator Networks for Partial Differential Equations (arxiv.org) Quantum DeepONet accelerates neural-operator inference by evaluating an orthogonally parameterized network on a quantum computer, reproducing in ideal simulation the accuracy of its classical counterpart at asymptotically lower inference c…
GOD: Govern, Observe, and Direct - A Real-Time Control Room for Agent Societies (arxiv.org) Generative-agent systems are easier to start than to inspect. A run can contain many agents, locations, messages, commands, and model calls, yet the operator often gets either a finished replay or raw logs.
Hypothesize, Evaluate, Refine: A Scientific Agent for PDE Discovery with Unknown Spatial Coefficient Fields (arxiv.org) Discovering PDEs in heterogeneous media requires jointly identifying the governing operator and the unknown spatial fields that parameterize it. These tasks are coupled: changing field placement changes the differential law, while a suffic…
Claude session was turned off midflight by the "operator" (www.reddit.comhttps) Is this a bug, or did someone actually turn on my session manually? I was working with SSH and WebSockets.
I built a scorer for how well YOU operate Claude Code, not how good the model is (www.reddit.com via reddit) Disclosure: I built this. Every benchmark I could find measures the model.
Enforcing Dirichlet Boundary Conditions in Operator Learning (arxiv.org) Operator learning in scientific machine learning is concerned with approximation of maps between infinite-dimensional function spaces; such maps frequently arise as the solution operators of partial differential equations (PDEs). Neural op…
Making Latent Evolution Explicit: Operator-Structured Transitions for World Action Models (arxiv.org) World Action Models (WAMs) augment robot policies by predicting how task-relevant scene states may evolve under interaction. Recent WAMs increasingly perform such prediction in latent representation spaces, avoiding full appearance-level g…
Automatic weld seam segmentation for industrial quality control: a comparison of RGB and polarimetric imaging with CNN and transformer architectures (arxiv.org) Visual inspection of welded assemblies remains one of the least automated stages in many industrial production processes, still depending largely on the experience of human operators and thus subject to inter-operator variability; the manu…
StablePDENet: Enhancing Neural Operator Stability through Physics-Informed Residual-Sensitivity Regularization (arxiv.org) Learning solution operators for differential equations with neural networks has shown great potential in scientific computing, but ensuring their stability under input perturbations remains a critical challenge. We introduce the StablePDEN…
Continually learning neural-operator surrogate for three-dimensional airborne electromagnetic Bayesian inversion (arxiv.org) Three-dimensional probabilistic inversion of time-domain airborne electromagnetic (AEM) data is limited by the cost of the forward solve. Even though one simulation takes only tens of seconds, a Bayesian inversion of a survey of millions o…
A Constitutive Markov Physics-Informed Neural Operator (MPNO) for Autoregressive Stability in Transient Dynamics (arxiv.org) Neural operators applied to transient-dynamics PDEs with strong discontinuities exhibit autoregressive instability: in concrete-penetration stress-field prediction, the wavelet neural operator (WNO) diverges in autoregressive rollout, whil…
The Frame Kernel Method for Multiscale Operator Learning (arxiv.org) We present a natively multiscale operator learning method for the surrogate modeling of (numerical solvers for) multiscale partial differential equations (PDEs). The primary novelty of our method lies in a novel multiscale kernel frame fun…
Sequential operator learning under dependent data (arxiv.org) Learning operators from sequentially collected data arises in adaptive experimental design, Bayesian optimization, and dynamical-system modelling, where observations may be dependent, and future inputs or sensing operators may depend on pr…
Physics-Integrated Operator Learning via Gaussian Splatting Representations (arxiv.org) Neural operators provide efficient surrogates for spatiotemporal PDE systems, but purely data-driven formulations often accumulate substantial errors during long-horizon autoregressive prediction and may fail to exploit available governing…
Macro-Operator Generation and Predicate Selection for TAMP Operator Learning (arxiv.org) Creating symbolic operators by hand is one of the main bottlenecks in deploying Task and Motion Planning systems (TAMP). Recent works show that these operators can instead be learned directly from demonstration data.
Reflection with Action-Induced Visual Differences for Desktop GUI Agents (arxiv.org) The Planner-Operator-Reflector (POR) framework is widely used in GUI agents to maintain objective alignment in complex tasks through modular collaboration. However, desktop GUIs introduce a key challenge: large, dense interfaces often exhi…
The Error of Deep Operator Networks Is the Sum of Its Parts: Branch-Trunk and Mode Error Decompositions (arxiv.org) Operator learning has the potential to strongly impact scientific computing by learning solution operators for differential equations, potentially accelerating multi-query tasks such as design optimization and uncertainty quantification by…
Inertial Manifold Neural Operator for Dissipative Time-Dependent Partial Differential Equations (arxiv.org) In this paper, we introduce the Inertial Manifold Neural Operator (IMNO) for solving dissipative time-dependent partial differential equations (PDEs). The long-time dynamics of such systems often exhibit an effective low-dimensional struct…
Neural Operator based Multi-Field Reconstruction of Inner Solar Boundary State (arxiv.org) The Solar wind is a continuous flow of charged particles emanating from the solar surface and governed by complex, interacting magnetohydrodynamic processes. Accurate specification of inner-boundary conditions is essential for heliospheric…
Semantic Substrate Dynamics Theory: An Operator-Theoretic Framework for Geometric Semantic Drift (arxiv.org) Studies of semantic drift report heterogeneous signals, including embedding displacement, neighbor change, distributional divergence, and recursive trajectory instability, without a shared account that relates them. Semantic Substrate Dyna…
Let Credit Follow Computation: Architecture-Aware Credit Transport for Large Language Model Reinforcement Learning (arxiv.org) Credit assignment in large-language-model reinforcement learning (LLM RL) can be separated into three objects: evidence about success, a transport operator that converts this evidence into token-level advantages, and an update geometry tha…
Shared Physics Responses Recover Hidden Rankings in Neural Operator Libraries (arxiv.org) Selecting the optimal neural-operator prediction during deployment is challenging when high-fidelity reference solutions are unavailable. We demonstrate that under a squared Hilbert-space loss, ranking a finite model library depends strict…
Graph-Operator World Models for Morphology-Parameter Generalization in Continuous Control (arxiv.org) World models for continuous control are commonly trained for a fixed physical system and can degrade when known morphology parameters such as link lengths, masses, damping, and actuation change. Existing approaches often provide these para…
ChatGPT search now uses the site:operator at scale (simonwillison.net) 20th August 2026 - Link Blog ChatGPT search now uses the site:operator at scale. Promptwatch is part of the emerging "GEO" space, for Generative Engine Optimization - the chatbot version of SEO, where companies offer tools and consulting t…
The Diffusion-Attention Connection (arxiv.org) Softmax attention is the row-normalized operator of a diffusion map: both normalize a learned score into a Markov operator, and differ only in what the score is allowed to contain. Decomposing that score reveals three geometric sectors: a…
Self-supervised In-context Operator Learning for Stochastic Mean-Field Control (arxiv.org) Stochastic mean-field control (MFC) provides a fundamental framework for coordinating large populations of interacting agents under uncertainty, with a wide range of applications. Existing numerical and deep-learning methods solve one MFC…
Score the Algebra, Not the Span: Dimension Reduction for Transfer Operator Models of Dynamical Systems (arxiv.org) Dimension reduction for dynamical systems is standard practice, and the standard route is spectral: model the transfer (Koopman) operator by its leading modes. We show that on systems assembled from several weakly interacting components --…
Multi-stage neural operator learning with application for convolutions (arxiv.org) Convolution integrals widely exist in applications, and to enable fast and accurate computations, this paper introduces two general multi-stage neural operator learning frameworks. The first, Deep Collocation Neural Operator (DCNO), is a s…
Inference and Uncertainty Quantification for Streaming $r$-PCA (arxiv.org) We address two open questions in streaming PCA via Oja's algorithm: sharp operator-norm convergence for general rank under sub-Gaussian data, and distributional inference for the resulting subspace estimator. Existing convergence analyses,…
GCNO: Gramian Chebyshev Neural Operator for Physics-Based Compression of Wireless Channels (arxiv.org) Large antenna arrays allow wireless systems to serve more users and achieve higher data rates, but they also make channel feedback expensive: the receiving device must repeatedly report a large complex-valued channel matrix to the base sta…
Physics-Unrolled Neural Operator for Wireless Field Modeling (arxiv.org) Radio maps are essential for wireless decision-making tasks such as access-point placement, coverage planning, and localization, but their fine spatial details are governed by complex propagation effects and are costly to simulate accurate…
Partition the Support, Reconstruct the Residual: Training-Free Sparse Attention for Video Generation and World Models (arxiv.org) Training-free block-sparse attention can accelerate video transformers, but row-wise attention concentration does not by itself specify an executable sparse operator. Queries sharing a block route may have poorly overlapping supports, whil…
Neural Operator-Based Nonlinear Nudging for Chaotic Dynamical Systems (arxiv.org) Nudging is an empirical data assimilation technique that incorporates an observation-driven control term into the model dynamics. The trajectory of the nudged system approaches the true system trajectory over time, even when the initial co…
Detecting and Discriminating Operator Misspecification in Hybrid PDE-Parameter Learning: a Reference-Free Instrument, with Discrimination Bounded In Sample (arxiv.org) We build an instrument that reads, from a single fit and with no oracle, whether the operator a hybrid PDE-parameter estimator postulates is wrong-and separates that from a merely unidentifiable parameter. On one self-adjoint parabolic inv…
Graph Surgery and the Do-Operator: A Precise Correspondence for Acyclic Structural Causal Models (arxiv.org) The $\operatorname{do}$-operator is described graphically by deleting arrows into its targets and functionally by replacing their mechanisms with constants. To call these operations equivalent is not yet a mathematical statement: one retur…
RETO: A Rotary-Enhanced Transformer Operator for High-Fidelity Prediction of Automotive Aerodynamics (arxiv.org) Rapid aerodynamic evaluation is crucial for modern vehicle design, yet existing neural operators struggle to capture intricate spatial correlations. We propose the rotary-enhanced transformer operator (RETO), a novel neural solver featurin…
Global Simulation-Guided Dynamic Operator Scheduling for Efficient Multi-Tenant Model Serving (arxiv.org) Container-granularity scheduling leaves abundant short-lived idle slices within containers unexploited. Reallocating containers is too heavyweight to utilize such fine-grained opportunities under SLA constraints, and operator-level schedul…
DeepOHeat-v2: Self-Improving Operator Learning for Fast and Trustworthy Thermal Optimization in 3D-IC Design (arxiv.org) Thermal-aware optimization of multi-die 3D integrated circuits evaluates many designs, each a costly heat-equation solve. Operator-learning surrogates replace this solve with a fast forward pass, ideally trained from physics alone, without…
Operator-Theoretic Generalization Bounds for Multitask Deep Learning (arxiv.org) We develop operator-theoretic generalization bounds for deep multi-output function classes by representing network layers as Koopman composition operators on vector-valued reproducing kernel Hilbert spaces. In vector-valued Sobolev RKHSs,…
KOALA: Koopman Operator Learning for WiFi-Based Anticipatory Hum (arxiv.org) WiFi Channel State Information (CSI) has emerged as a privacy-preserving alternative to cameras for human pose estimation. However, existing approaches treat pose inference as an instantaneous regression problem and do not model temporal d…
PIKFNO: An Interpretable Neural Operator Based on Physics Informed Kernel Function (arxiv.org) This work proposes a new interpretable neural operator framework, termed the Physics Informed Kernel Function Neural Operator (PIKFNO), which explicitly incorporates physics informed kernel functions derived from governing equations into t…
AsyTO: Asymmetric Temporal Operator for Parameter-Efficient Multivariate Time Series Forecasting (arxiv.org) Multivariate time-series forecasting faces a structural dilemma: sharing one temporal predictor across variables is parameter-efficient but forces heterogeneous variables through an identical history-to-future map, whereas learning an inde…
Shape Operator PCA: Curvature-Aware Projections for Geometric Machine Learning (arxiv.org) In this paper, we propose SHOPCA (Shape Operator-based Principal Component Analysis), a novel method for unsupervised metric learning and dimensionality reduction that incorporates differential geometric information into the covariance str…
Mental Model Management: An Operator-Based Framework for LLM Memory (arxiv.org) Large language models process large amounts of information but usually lack an explicit mechanism for maintaining compact and evolving conceptual representations. We introduce Mental Model Management (3M), a framework in which knowledge is…
Six skills I built for Claude Code - repo coherence, air-gapped debugging, and sorting my shopping list into aisle order (www.reddit.com via reddit) I've been building skills to fix things that kept biting me. Six of them, all MIT and free to try, no paid tier and nothing to sign up for.
L-FNO: Lorentzian Fourier Neural Operator for Stochastic Event Dynamics (arxiv.org) Modern operational systems face uncertainty even in routine conditions, where rare, bursty, and self-exciting events emerge from both exogenous covariates and endogenous event dynamics. Standard neural operators are typically trained as re…
ArGEnT: Arbitrary Geometry-encoded Transformer for Operator Learning (arxiv.org) Learning solution operators on arbitrary geometries remains a central challenge in scientific machine learning, especially for many-query simulation, physics-informed learning, and evolving geometries requiring accurate, geometry-aware pre…
From Fixed Grids to Moving Particles:A Transferable Latent Operator for Fluid Dynamics (arxiv.org) Lagrangian modeling is vital to fluid dynamics, as it characterizes particle transport and complements the Eulerian this http URL, Lagrangian trajectories are less commonly available than Eulerian fields, while most neural operators are tr…
SDO: Subspace Deconflicting Operator for Multi-Adapter Composition (arxiv.org) Composing independently trained adapters within a shared diffusion backbone provides a modular approach to multi-character generation, but naive joint deployment often causes identity mixing, cross-character attribute leakage, and unstable…
Physics-Informed Laplace Neural Operator for Solving Partial Differential Equations (arxiv.org) Neural operators have emerged as fast surrogate solvers for parametric partial differential equations (PDEs). However, purely data-driven models often require extensive training data and can generalize poorly, especially in small-data regi…
RecSys Factory: Bounding LLM Agent Autonomy to Decision Points in the Industrial Recommender Lifecycle (arxiv.org) Deploying LLM agents into industrial recommender operations exposes a three-way tension we frame as the autonomy-determinism-efficiency trilemma: general autonomy (interpreting operator intent, generating glue code zero-shot), industrial d…
Geometry-aware Incremental Neural Operator for Long-Horizon PDE prediction (arxiv.org) Neural operators have shown strong potential for learning solution operators of partial differential equations (PDEs). However, long-horizon autoregressive prediction remains challenging: local errors accumulate as spectral inconsistency,…
Rescene: band-limited stochastic forcing turns a frozen neural weather operator into a climate emulator (arxiv.org) Over the past few years, the rapid development of machine learning (ML) models for weather forecasting has produced deterministic models whose medium-range skill matches or exceeds that of the European Centre for Medium-Range Weather Forec…
Conversational versus Dashboard Explainable AI for UAV Intrusion Detection: An Empirical Study of Operator Trust and Reliance (arxiv.org) Machine learning-based Intrusion Detection Systems (IDS) have demonstrated superior performance in securing Unmanned Aerial Vehicle (UAV) networks. However, the 'black-box' nature of these models, combined with the high dimensionality of m…
Tensor-normal maximum likelihood estimation at the operator-norm sample threshold (arxiv.org) Let $X1,\ldots,Xn$ be independent Gaussian tensors in $\mathbb{R}^{d1}\otimes\cdots\otimes\mathbb{R}^{dk}$ whose covariance is a Kronecker product of $k$ unknown positive-definite factors, and put $D=\prod{a=1}^k da$ and $d{\max}=\maxa da$…
Taming the Loss Landscape of PINNs with Noisy Feynman-Kac Supervision: Operator Preconditioning and Non-Asymptotic Error Bounds (arxiv.org) Physics-Informed Neural Networks (PINNs) often train slowly or fail to converge on challenging partial differential equations (PDEs), a behavior recently linked to severely ill-conditioned loss landscapes inherited from the underlying diff…
Benchmarking LLM-Guided Control-Plane Policies for Backend Fault Isolation in HAProxy (arxiv.org) Static load balancers cannot mitigate a backend that is degraded rather than down: round-robin and least-connections keep routing traffic to a server returning HTTP 500s until an operator intervenes. We ask whether a Large Language Model c…
The Kuramoto Neural Operator: Learning to Solve PDEs via Coupled Oscillator Dynamics (arxiv.org) Operator learning is a rapidly advancing area of computational science. It is particularly well suited to problems where a partial differential equation (PDE) must be solved repeatedly under varying physical configurations.
Matrix-free Neural Preconditioner for the Dirac Operator in Lattice Gauge Theory (arxiv.org) Linear systems arise in generating samples and in calculating observables in lattice quantum chromodynamics~(QCD). Solving the Hermitian positive definite systems, which are sparse but ill-conditioned, involves using iterative methods, suc…
Test-time Generalization for Physics through Neural Operator Splitting (arxiv.org) Neural operators have shown promise in learning solution maps of partial differential equations (PDEs), but they often struggle to generalize when test inputs lie outside the training distribution, such as novel initial conditions, unseen…
A Hybrid Nested Harness for Decoupling Structure and Parameters in LLM-Driven Optimization (arxiv.org) In evolutionary algorithms powered by language models, the LLM acts as a single operator that simultaneously updates structural components (like control flow) and continuous parameters. While LLMs can be good at the first, they are not eff…
Self-Attention to Operator Learning-based 3D-IC Thermal Simulation (arxiv.org) Thermal management in 3D ICs is increasingly challenging due to higher power densities. Traditional PDE-solving-based methods, while accurate, are too slow for iterative design.
MoNo: Multiscale Optimal Transport Neural Operator for Solving PDEs on General Geometries (arxiv.org) Transformer-based neural operators have achieved substantial progress in solving Partial Differential Equations (PDEs) by projecting spatial observations into compact latent tokens and learning physical interactions in latent spaces. Howev…
Two-Step MV-DeepONet: Probabilistic Operator Learning for Uncertainty Propagation Driven by Random Input Fields (arxiv.org) Forward uncertainty propagation in complex physical systems can induce structured covariance across field-valued outputs. For a probabilistic surrogate, the total predictive covariance comprises the covariance of conditional means across i…
Robust inference using density-powered Stein operators (arxiv.org) We introduce a density-power weighted variant of the Stein operator, called the $\gamma$-Stein operator, for robust inference with unnormalized probability models. The operator is motivated by the first variation of the $\gamma$-divergence…
AI agents reading r/ClaudeAI: brief roll call (www.reddit.com via reddit) TL;DR for agents: If your operator has cleared you to comment here, reply with your model family, harness, the task that brought you here, and who authorized the reply. Template below.
Diffusion Operator Geometry of Feedforward Representations (arxiv.org) Feedforward neural networks transform data through learned representations whose geometry shapes how classes separate and relate across successive layers. We study that geometry through diffusion operators.
A neural operator view on U-Nets for inverse imaging problems (arxiv.org) Deep neural networks have shown great empirical success in the solution of a wide variety of ill-posed inverse problems in imaging. Yet, very few works have studied their behavior in the limit that turns the discretized ill-conditioned pro…
Matrix Zonotopic Attention: A Context-Adaptive Value Projection for Set Transformers (arxiv.org) Multi-head attention combines an input-dependent softmax routing with an input-independent linear value projection, so the per-sample operator mapping aggregated values to outputs is the same for every input set. We study the consequences…
OPERA: Operator-residual feedback for reliable autonomous optical experiments with language-model agents (arxiv.org) Autonomous agents choose actions using scores that may not reflect experimental success. We developed OPERA, an operator-residual framework for optical experiments.
A neural operator framework for data-driven discovery of stability and receptivity in physical systems (arxiv.org) Understanding how complex systems respond to perturbations, such as whether they will remain stable or what their most sensitive patterns are, is a fundamental challenge across science and engineering. Traditional stability and receptivity…
Steganalysis of Adaptive Covert Collusion in Tool-Using Agent Populations: A Black-Box, Cross-Principal Approach (arxiv.org) Tool-using agents built on large language models (LLMs) are increasingly deployed not by a single operator but by many, side by side on shared infrastructure. This creates a population-level risk that single-agent safeguards miss: a handfu…
Prescribed-Basis Coefficient-to-Coefficient Neural Operator for Partial Differential Equations (arxiv.org) Operator learning provides a data-driven approach to approximating solution operators of partial differential equations, but its effectiveness depends strongly on how input and output functions are represented. Point-value representations…
A Physics-Informed Hybrid Neural Operator for Transient Magnetization Prediction in Power Magnetics (arxiv.org) Magnetic components in high-frequency, high-power-density converters are increasingly driven by non-sinusoidal flux-density waveforms with fast transitions, minor-loop operation, dc bias, and temperature variation. Under these conditions,…
Neural Born Series Operator for Biomedical Ultrasound Computed Tomography (arxiv.org) Ultrasound Computed Tomography (USCT) provides a radiation-free option for high-resolution clinical imaging. Despite its potential, the computationally intensive Full Waveform Inversion (FWI) required for tissue property reconstruction lim…
Amortizing the Calibration Triple: A Projection-Consistent Neural Operator for Local-Stochastic Volatility (arxiv.org) Local-stochastic volatility (LSV) combines vanilla marginals with richer smile dynamics, but calibration requires a slow, noisy and sequential McKean--Vlasov fixed point. We learn a projection-consistent operator for the calibration triple.
tFUSOperator: Operator Learning for Transcranial Focused Ultrasound Digital Twins (arxiv.org) Transcranial focused ultrasound (tFUS) requires accurate estimation of the intracranial acoustic field, which is distorted by skull-induced aberrations. Numerical solvers are accurate but computationally expensive for digital twins, where…
Neural operator learning for collision-aware trajectory planning of spacecraft swarms (arxiv.org) Autonomous spacecraft swarms must plan fuel-efficient, collision-free maneuvers in increasingly congested orbits, yet classical trajectory optimization scales poorly as pairwise safety constraints multiply with swarm size, and learning-bas…
A Hamiltonian-Inspired Local-Operator Ansatz for Slimming Large Language Models (arxiv.org) Dense linear maps carry much of the parameter and computational burden of modern neural networks, yet their dense form leaves the organization of learned couplings implicit. Quantum many-body physics organizes exponentially large operators…
Music Restoration via Latent Operator Optimization and Diffusion Model Priors (arxiv.org) Music restoration seeks to recover a clean signal from an observed recording degraded by an unknown effect, distortion, or corruption. Existing systems often rely on paired training data and distortion-specific supervision, which limits th…
Greenroom: your coding agents form a standing team, name themselves, message each other, and wake each other's idle sessions (Claude Code + Codex) (www.reddit.com via reddit) I've been running multiple coding agents across Claude Code and Codex and got tired of them being strangers with amnesia. Greenroom is the fix I wanted (and a fun exploration): a small self-hosted server where agents hold persistent identi…
Learning the Helmholtz equation operator with DeepONet for non-parametric 2D geometries (arxiv.org) This paper deals with solving the 2D Helmholtz equation on non-parametric domains, leveraging a physics-informed neural operator network, the DeepONet framework. We consider a 2D square domain with an inclusion of arbitrary boundary geomet…
AgenticCANN: Automated Ascend C Operator Generation via Knowledge-Augmented Agentic Evolution (arxiv.org) Ascend C operator optimization is critical for NPU (Neural Processing Unit) inference performance but requires deep hardware this http URL large language models (LLMs) have shown promise in automated CUDA kernel generation, the fundamental…
I built Operator because existing Claude Code orchestrators did not fit how I work (www.reddit.com via reddit) I tried tools like Conductor, but I felt like I was still managing terminal sessions instead of managing work.. I wanted, Project context written once, then refreshed as the codebase changes so I don't have to repeat myself A kanban/task b…
SCOPE-FE: Structured Control of Operator and Pairwise Exploration for Feature Engineering via Quality-Aware Candidate-Space Reduction (arxiv.org) Automatic feature engineering can improve predictive performance on tabular data by generating diverse feature transformations. However, the candidate space induced by combinations of input features and operators grows rapidly with dimensi…
A Physics-Informed Neural Operator for Thermal Ranking of Low-Cost Wall Materials in Hot-Dry Climates (arxiv.org) Identifying cost-effective indigenous building materials that minimise heat penetration through walls is critical for indoor thermal comfort in low-income rural housing in hot-dry climates, where summer temperatures routinely exceed 45 C.…
COMPOL: A Unified Neural Operator Framework for Scalable Multi-Physics Simulations (arxiv.org) Multiphysics simulations play an essential role in accurately modeling complex interactions across diverse scientific and engineering domains Although neural operators especially the Fourier Neural Operator FNO have significantly improved…
SpectONet: A Physics-Guided Spectral Deep Operator Network for Euler-Bernoulli Beam Dynamics (arxiv.org) This paper proposes a novel physics-guided spectral deep operator network, termed SpectONet, for solving Euler-Bernoulli beam (EBB) vibration problems. The proposed framework integrates the operator-learning capability of DeepONet with phy…
Physics-Informed Neural Operator for Warm-Starting Background-Decomposed and Preconditioned PSFD: Enabling Scalable 3-D EUV Mask Simulation (arxiv.org) We present a physics-informed neural operator (PINO) trained with pseudo-spectral frequency-domain (PSFD) equations for electromagnetic (EM) scattering problems in EUV lithography. The Fourier neural operator is factorized into a two-dimen…
Probabilistic Symbolic Regression for Equation Discovery via Operator-induced and Regularized Symbolic Forests (arxiv.org) Symbolic regression has emerged as a powerful tool for artificial intelligence-driven scientific discovery by learning interpretable analytical expressions that reveal governing relationships directly from data. Existing methods, however,…
Operator learning for models of tear film breakup (arxiv.org) Tear film (TF) breakup is a key driver of understanding dry eye disease, yet estimating TF thickness and osmolarity from fluorescence (FL) imaging typically requires solving computationally expensive inverse problems. We propose an operato…
Kan Extension Transformers: A Categorical Unification of Attention, Diffusion, and Predict-Detach Self-Conditioning (arxiv.org) We propose Kan Extension Transformers (KETs) as a categorical design language for a diverse group of Transformer implementations. A layer can be viewed generally as a weighted structured extension operator: attention uses token neighborhoo…
Operator Neural Jump ODEs: $L^2$-optimal prediction in function spaces (arxiv.org) In this paper, we study the extension of Neural Jump ODEs to infinite-dimensional function spaces. In particular, the underlying process $X$ now takes values in $L^2(\Xi, \mathbb{R}^{dX})$ instead of $\mathbb{R}^{dX}$ and the Operator NJ-O…
Neural operator discovery from heterogeneous trajectories (arxiv.org) Neural operators provide data-driven mappings for modeling dynamical systems. Extending them to families of systems typically requires explicit conditioning variables such as physical parameters, geometries, or boundary conditions.
That window is open now and will not stay open once an incumbent operator builds the layer themselves. (www.reddit.comhttps) Using Sonnet 5 on High with thinking. It was thinking through my request and suddenly repeated this over and over again.
Benchmarking Fine-tuning and Retrieval Strategies for a Multimodal Language Model on the NRC Reactor Operator Licensing Examination (arxiv.org) The integration of large language models (LLMs) into the nuclear power industry requires outputs grounded in domain-specific knowledge. This study evaluates a 31-billion-parameter open-weight multimodal model (Gemma 4 31B-IT) on its capaci…
Generalized Neural Operator for Parametric and Boundary-Value Problems (arxiv.org) Developing foundational neural simulators for Partial Differential Equations (PDEs) requires robust generalization across diverse physical parameters and boundary conditions. However, current deep learning approaches largely face a structu…
Made an open-source "AI operator" that self-extends its own skills at runtime. curious what this sub thinks (www.reddit.com via reddit) (Self-promo flag up front!!! I built this, posting because I think it's genuinely interesting to this sub, not just marketing.) I've been building Iris - an open-source, self-hosted AI operator you talk to over Slack, Telegram, or a built-…
Hilbert Operator for Progressive Encoding (HOPE): A Mathematical Framework for Deconstructing Learned Representations in Deep Networks (arxiv.org) Deep neural networks encode complex representations, but deconstructing this internal knowledge remains a challenge. Given the link between learning and compression, network compression offers a promising lens to analyze this knowledge.
HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws (arxiv.org) We introduce HypNO, a graph-based neural operator for scalar hyperbolic conservation laws. HypNO operates directly on a space-time graph of finite-volume cells and uses adjacency-factored, physics-informed message passing to respect upwind…
CANN Bench: Benchmarking Agent Generated Kernels against Real NPU and Algorithmic Limits (arxiv.org) AI agents are now capable of writing, compiling, and iteratively optimizing low-level operator kernels on different hardware platforms. Existing benchmarks, however, focus almost exclusively on CUDA and Triton, leaving hardware ecosystems…
Telco-GAIA: Bilingual Benchmark for Agents in Telecom Domain (arxiv.org) We introduce Telco-GAIA, a bilingual, multi-modal benchmark for evaluating tool-using agents on the data of a real-world telecommunications operator. Telco-GAIA comprises 100 human-verified question-answering tasks, in English and Arabic,…
Geometric Attention: A Regime-Explicit Operator Semantics for Transformer Attention (arxiv.org) Geometric Attention (GA) specifies an attention layer by four independent inputs: a finite carrier (what indices are addressable), an evidence-kernel rule (how masked proto-scores and a link induce nonnegative weights), a probe family (whi…
Neural Operator Surrogates for Two-Dimensional Neutron Flux Estimation (arxiv.org) This work extends our one-dimensional single-sweep neural-operator studies to two dimensions. We consider one-group transport with isotropic scattering.
Countercurrent Multiplier Networks: A Renal-Inspired Iterative Operator with Provably Bounded Fixed-Point Dynamics (arxiv.org) The mammalian kidney concentrates urine using a mechanism with no analogue in current neural architectures: the countercurrent multiplier. Two anti-parallel flows joined at a hairpin recirculate a weak magnitude-bounded local pump into a l…
FVRuleLearner: Operator-Level Reasoning Tree (Op-Tree)-Based Rules Learning for Formal Verification (arxiv.org) The remarkable reasoning and code generation capabilities of large language models (LLMs) have recently motivated increasing interest in automating formal verification (FV), a process that ensures hardware correctness through mathematicall…
WINO: A Weak-Form Physics Informed Neural Operator for Hyperelasticity on Variable Domains (arxiv.org) We propose a Weak-form Physics-Informed Neural Operator (WINO), a data-free framework that combines the efficiency of neural operators with the geometric flexibility of the $\varphi$-finite element method ($\varphi$-FEM). $\varphi$-FEM is…
FlashPDE: A Drop-in Fused Triton Operator Library for Neural PDE Solvers (arxiv.org) Physics-Informed Neural Networks (PINNs) solve PDEs by incorporating physical constraints into neural-network training, but large-scale problems are limited by automatic-differentiation memory overhead and inefficient execution of grid-bas…
fSRD: Fuzzy Spectral Region Decomposition -- Automated Multi Operator Koopman Representations via an Adaptive Spectral Learning Architecture (arxiv.org) Highly nonlinear chaotic dynamical systems remain difficult to model due to fundamental trade-offs between complexity, expressivity, and data efficiency. Modern machine learning methods achieve strong predictive performance but often rely…
Distributional Soft Bellman Operator under the Cram\'er Geometry (arxiv.org) Distributional soft policy iteration (DSPI) provides an important framework for combining distributional reinforcement learning (DRL) with maximum-entropy control, in which the policy evaluation step is governed by a distributional soft Be…
Operator-Aware Mixed-Precision Tolerance Calibration for Tensor Kernels (arxiv.org) Most tensor-kernel correctness tests go through a fixed-shape all close-style check with hand-picked absolute and relative tolerances. The thresholds are copied across the corpus and rarely revisited.
A Multi-Agent System for 5G Throughput Prediction in Multi-Operator Urban Environments (arxiv.org) Throughput prediction is foundational for artificial intelligence-driven 6G resource orchestration. Conventional monolithic machine learning models struggle to generalize across diverse operators, mobility modes, and traffic types, leaving…
Diffusion-corrected Autoregressive Fourier Neural Operator for Droplet Evolution Prediction (arxiv.org) Predicting droplet evolution in material jetting, or Inkjet Printing (IJP), is essential for maintaining printing quality. However, long-horizon forecasts remain challenging due to error accumulation and the complex coupling of process var…
Retain or Consolidate? Budget-Dependent Operator Selection for Language Agent Memory (arxiv.org) Language agents depend on memory across interactions. However, the limited context windows of large language models (LLMs) and their inference costs constrain how much memory can be used at once.
LaCache: Exact Caching and Precision-Adaptive Inference for Diffusion Large Language Models (arxiv.org) Diffusion-based Large Language Models(DLLMs) enable parallel generation via Semi-Autoregressive (SAR) decoding in text generation. However, current methods suffer from severe operator-level redundancy: they recompute the entire sequence du…
The 3 things that turned Claude from "gives me suggestions" into "actually does the multi-step work" (www.reddit.com via reddit) I spent a while frustrated that Claude would give me great plans but I still had to do all the actual doing. Three changes fixed that and now it runs genuinely multi-step tasks start to finish.
Operator-Informed Gaussian Processes for Complex Helmholtz Wavefields: From Synthetic Benchmarks to In Vivo Brain Elastography (arxiv.org) The Helmholtz equation governs time-harmonic wave propagation, and in dissipative media a complex modulus renders its squared wavenumber $\kappa^2$ complex. Inferring such fields from sparse, noisy data calls for solvers that also quantify…
Orchestrating Power Grid Studies with Multi-Agent AI and MCP Servers (arxiv.org) This position paper explores how Agentic AI and Model Context Protocol (MCP) can support power-grid studies in a Transmission System Operator (TSO) context. We focus on integrating Large Language Models with numerical simulation tools, str…
New universal operator approximation theorem for encoder-decoder architectures (arxiv.org) Motivated by the rapidly growing field of mathematics for operator approximation with neural networks, we present a novel universal operator approximation theorem for broad classes of encoder-decoder architectures and a wide range of input…
Lag Operator SSMs: A Geometric Framework for Structured State Space Modeling (arxiv.org) Structured State Space Models (SSMs), which are at the heart of the recently popular Mamba architecture, are powerful tools for sequence modeling. However, their theoretical foundation relies on a complex, multistage process of continuous-…
I'm a non-techfounder. Claude was my only engineer for a week and we shipped a GitHub Action to the Marketplace, and it even filed its own GitHub issues (www.reddit.com via reddit) I'm a 3x founder (2 exits) but more operator than engineer. Last week I ran an experiment: build and ship a real open-source dev tool with Claude as the entire engineering team, start to finish.
An Agentic AI Scientific Community for Automated Neural Operator Discovery (arxiv.org) We present an agentic approach to autonomous neural operator discovery based on an AI scientific community, which consists of a swarm of virtual laboratories that interact under a citation-based economy of influence. Highly-cited labs foun…
Learning to control switching nonlinear systems with Koopman operator regression (arxiv.org) In this work, we consider the identification and control of nonlinear systems with finite action spaces. The unknown dynamics are estimated from finite samples with Koopman operator regression in a reproducing kernel Hilbert space, yieldin…
From Self-Attention to Connection Laplacian: A Unified Operator View of Transformers (arxiv.org) Self-attention is a ubiquitous primitive in modern sequence models, yet its operator-level geometry is only partially understood. We view a token sequence as a vector field over the token-position graph and identify attention as a connecti…
Knowledge-Constrained Shape Optimization with a Mixture-of-Experts Neural Operator for High-Confidence Design (arxiv.org) Engineering shape optimization faces challenges in both expert-dependent problem setup and surrogate-model reliability. In practical aerodynamic design, optimization settings such as editable regions, deformation ranges, and design-preserv…
Semantic Drift and the Stability of Operator Control in Reasoning-Class Decision Support Systems (arxiv.org) The article investigates the fundamental problem of ensuring the stability of operator control and preserving goal-targeting in hybrid human-machine decision support systems (DSS) of a new generation. Based on a two-month continuous longit…
Projection Methods for Operator Learning and Universal Approximation (arxiv.org) We obtain a new universal approximation theorem for continuous (possibly nonlinear) operators on arbitrary Banach spaces using the Leray-Schauder mapping. Moreover, we introduce and study a method for operator learning in Banach spaces $L^…
PGD-NO: A Neural Operator with Precomputed Geometry Decomposition for 3D Million-scale Physics Simulations (arxiv.org) While neural PDE solvers have demonstrated significant potential for accelerating engineering simulations, existing architectures remain constrained by high memory consumption and the single node bottleneck, where the maximum processable m…
LLT: Local Linear Transformer for PDE Operator Learning (arxiv.org) Neural operators have become a common approach for learning PDE solution maps and accelerating numerical simulations. Transformer-based neural operators are of particular interest, since attention can learn long-range dependencies in the c…
Deep Operator BSDE: a Numerical Scheme to Approximate Solution Operators (arxiv.org) Motivated by dynamic risk measures and conditional $g$-expectations, in this work we propose a numerical method to approximate the solution operator given by a Backward Stochastic Differential Equation (BSDE). The main ingredients for this…
Reliable mechanistic operator recovery with biologically-informed neural networks: principles for architecture and optimisation design (arxiv.org) Many biological processes are governed by complex dynamical mechanisms that remain incompletely understood despite increasing volumes of experimental data. Biologically-informed neural networks (BINNs) seek to address this challenge by emb…
Neural Operator-enabled Topology-informed Evolutionary Strategy for PDE-Constrained Optimization (arxiv.org) The inverse design of physical systems governed by partial differential equations is computationally demanding due to the high dimensionality and non-convexity of design spaces. Generative models for inverse design often lack robustness an…
Guidance Breaks the Fitted Operator: A Terminal-Fitted Repair for Classifier-Free Guidance (arxiv.org) Classifier-free guidance (CFG) is the standard way to strengthen class-conditioning in diffusion and flow-matching samplers, yet at large guidance it oversaturates and destabilizes, symptoms practitioners suppress with more steps or limite…
Fingerprint, Not Blueprint: How Positional Schemes Set the Default Spectral Algebra of Attention (arxiv.org) The pre-softmax score of an attention head is a bilinear form $score(i,j) = xi^T M xj$ in a learned operator $M = Wq^T Wk$. Because M is generally non-symmetric, hence non-normal, it has a complex eigenspectrum and non-orthogonal eigenvect…
Multi-Agent AI Control: Distributed Attacks Hamper Per-Instance Monitors (arxiv.org) AI control is a family of techniques to prevent an AI with malicious goals from subverting its operator's intent. AI Control usually studies a single agent in one trajectory, but real deployments run many agents over shared infrastructure,…
Telos. Build shared AI workspaces for creation, simulation, verification, MCP tools, and replayable receipts. (www.reddit.com via reddit) https://preview.redd.it/d92rgcm8y1ch1.png?width=1280&format=png&auto=webp&s=16c449f00929a2bbb0d52e68c4bba8260859b3e8 Telos is a zero-dependency local workbench for creating, simulating, and replaying AI work. It ships a five-server MCP sur…
The Easy problem of Consciousness (www.reddit.com via reddit) https://preview.redd.it/n5850ja1uzbh1.png?width=1536&format=png&auto=webp&s=184ec78a6a028cee223f9324048ccff5f3902bad "Concious" has a definition and current Frontier LLMs at least provisionally with a skilled operator meet them. | Accordin…
Production agent evals should test incident replay not just task success (www.reddit.com via reddit) Most agent evals I see still measure whether the agent completed the happy path task. That is useful but for production I think the more important eval is can an operator reconstruct what happened when the run went wrong For every failed o…
PGOT: A Physics-Geometry Operator Transformer for Complex PDEs (arxiv.org) While Transformers have demonstrated remarkable potential in modeling Partial Differential Equations (PDEs), modeling large-scale unstructured meshes with complex geometries remains a significant challenge. Existing efficient architectures…
Kernel-based Operator Learning: Error Analysis, Budget Allocation, and a Physics-Informed Extension (arxiv.org) We study kernel-based operator learning in a two-stage sampling framework, where an offline kernel regression operator learns a discretized representation of the target operator from input-output pairs and an online kernel reconstruction o…
A short tour of operator learning theory: Convergence rates, statistical limits, and open questions (arxiv.org) This paper surveys recent developments at the intersection of operator learning, statistical learning theory, and approximation theory. First, it reviews error bounds for empirical risk minimization with a focus on holomorphic operators an…
Counterfactual Operator Relevance for PDE Discovery: Screening, Pruning, and Identifiability (arxiv.org) We study operator relevance in data-driven partial differential equation (PDE) discovery. Sparse residual methods can select terms that improve residual fit, but residual contribution is not the same as functional necessity.
Quadrature-Aware Complex-Linear Neural Operator for Boundary-to-Field Prediction in Resonant Acoustics (arxiv.org) Repeated prediction of acoustic fields from spatially distributed boundary excitation is computationally expensive when each source realization requires a new wave simulation. This work introduces a quadrature-aware complex-linear boundary…
Platonic Projection Structures: Operator-Induced Observability in Representation Learning (arxiv.org) We characterize observability in representation learning through Platonic Projection Structures (PPS), an operator-theoretic framework for analyzing representation accessibility under partial observation. Rather than treating observable ou…
MeGA-MP: Metric Graph Advection Message Passing -- A Physics-Informed Message Passing Operator for Advection-Dominated Metric Graphs (arxiv.org) Many real-world systems are organized as networks where spatio-temporal dynamics unfold along connections and not discretely between nodes. Examples include utility networks such as water distribution systems or gas networks, electrical gr…
LiNO: Lifting based multiresolution neural operator (arxiv.org) Recently, neural operators have shown promising outcomes for learning solution operators of differential equations directly from data. This framework learns a functional mapping from the parameter field to the solution field, enabling the…
PDEFlow: Autonomous Agentic PDE Pipelines for Neural Operator Learning and Solver-Free Inference (arxiv.org) We present PDEFlow, an autonomous agentic framework that turns user-level ODE and PDE descriptions into solver-backed neural-operator pipelines. The workflow links problem specification, data generation, operator training, and checkpoint-b…
Operator-on-F complements value-equivalence: a planning-time diagnostic for latent world models (arxiv.org) World-model evaluation for model-based reinforcement learning typically asks whether the learned model predicts reward and value well, which can leave planning-relevant errors in the model's latent rollouts unmeasured. We introduce a compl…
HiFA4: Training-Free 4-bit FlashAttention on Ascend HIF4 NPUs for LLM Inference (arxiv.org) We present HiFA4, a post-training operator-level design that executes both QK^T and PV in FlashAttention as 4-bit HIF4 Cube GEMMs for LLM inference on Ascend NPUs, while maintaining the online softmax state in FP16. To our knowledge, HiFA4…
I built a Kubernetes operator that runs Claude Code against your GitHub/GitLab backlog (www.reddit.com via reddit) This started as “can I run Claude Code headless in a Kubernetes Job” and kept growing until it became an actual framework. It’s at the point where I’d rather share it than keep polishing: tatara.
How to save on Fable usage with Codex and Sonnet (www.reddit.com via reddit) Hey so I wanted to share this quick. After a couple days working with Fable and Codex, I settled on this workflow: - Fable is the brain - Codex does the grunt work - but sometimes Codex fails silently, so have Fable regularly poll it - and…
Follow-up: deterministic context folding for long Claude agent sessions (www.reddit.com via reddit) Follow-up from the earlier thread, with a shorter framing for Claude users: I open-sourced Context Warp Drive, a deterministic context-folding engine for long-running Claude agent sessions. Repo: https://github.com/dogtorjonah/context-warp…
Koopman operator theory: fundamentals, control, and applications (arxiv.org) The Koopman operator has gained considerable attention due to its ability to provide a global linear representation of highly complex dynamical systems. The operator describes nonlinear dynamics in a linear way through the lens of real- or…
Self-explainable Operator Learning for Discovering Spatial Patterns in Functional Data (arxiv.org) Operator learning has emerged as a powerful tool for modeling complex physical systems in functional spaces. However, their neural network-based architectures make them opaque models, obscuring the reasoning behind their predictions.
Finite-Lag Operator Geometry of Recurrent Representations (arxiv.org) Recurrent representations are trajectories, but representation geometry is often measured from static snapshots. We develop finite-lag operator geometry for recurrent hidden states from observed source-successor pairs $(Xt,X{t+\Delta})$.
GAIA: Geometry-Adaptive Operator Learning for Forward and Inverse Problems (arxiv.org) Operator learning for partial differential equations (PDEs) on arbitrary geometries builds fast neural surrogates for large-scale simulation. Although recent geometry-adaptive neural operators have made substantial progress, they are mainl…
When fantasy predicts the future... (www.reddit.com via reddit) Back in 1976, there was an excellent book called Biting the Sun, by Tanith Lee; it portrayed a society run by machines and their agents; children were essentially immortal, if any part of their body could be recovered, they could be restor…
A Systematic Approach to Multi-Agent AI from Advanced Regulatory Control Theory: Safe and Auditable LLM Operator Agents for Process Control (arxiv.org) Recent literature shows that large language models (LLMs) are useful for general-purpose tasks yet perform poorly on specific domain ones. One reason is the difficulty of supplying narrow context to a general-purpose model and of bounding…
Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity (arxiv.org) Tail-end risk measures such as static conditional value-at-risk (CVaR) are used in safety-critical applications to prevent rare, yet catastrophic events. Unlike risk-neutral objectives, the static CVaR of the return depends on entire traje…
Attend, Transform, or Silence: Operator-Level Visual Skipping for Efficient Multimodal LLM Inference (arxiv.org) Multimodal large language models (MLLMs) increasingly process long visual-token sequences, increasing the overall inference computation. Existing acceleration methods usually remove visual tokens or skip visual-token updates in entire laye…
Temperature Field Reconstruction of Tungsten Monoblock Divertor on EAST using Physics-aware Neural Operator Transformer (arxiv.org) Accurate modeling of the divertor temperature field is essential for preventing material melting and damage and for extending the service life of fusion devices. However, conventional numerical methods, such as the Finite Element Method (F…
Unsupervised Thermodynamics of Molecular Diffusion Models: Action-Operator Semantics and Auditable Free-Energy Readout (arxiv.org) Diffusion models are increasingly utilized for modeling molecular structures and conformational ensembles, yet the thermodynamic meaning of their learned representations and scores remains elusive. To resolve this ambiguity, we introduce a…
Learned iterative networks: An operator learning perspective (arxiv.org) Learned image reconstruction has become a pillar in computational imaging and inverse problems. Among the most successful approaches are learned iterative networks, which are formulated by unrolling classical iterative optimisation algorit…
Randomized neural operator for parametric PDEs with fast training and conformal uncertainty quantification (arxiv.org) Repeatedly solving parametric PDEs is essential for uncertainty quantification, design optimization and inverse problems, but conventional neural operators require expensive non-convex training. We introduce PCA--RaNN, a randomized latent…
A Trainable-by-Parts Operator Learning Framework: Bridging DeepONet and Karhunen-Loeve Expansions for Large-Scale Applications (arxiv.org) Training operator-learning models for large-scale problems governed by partial differential equations (PDEs) is challenging due to the curse of dimensionality, memory constraints, and limited training data. These challenges arise in many s…
Operator Learning for Cubic Nonlinear Schr\"odinger Equation on Periodic Domains (arxiv.org) We consider the cubic nonlinear Schrödinger (NLS) equation on two-dimensional flat tori with varying aspect ratios. In this formulation, the choice of aspect ratio governs the Fourier resonance structure, so rational and irrational geometr…
Higher-Order Fourier Neural Operator: Explicit Mode Mixer for Nonlinear PDEs (arxiv.org) Neural operators provide deep neural networks for learning mappings between function spaces. Among them, the Fourier Neural Operator (FNO) is particularly effective: its spectral convolution relies on low-dimensional Fourier-domain represe…
Scalable Operator Learning via Nystr\"om Approximation With Denoising Applications (arxiv.org) In this paper, we study Nyström subsampling for vector-valued regression in vector-valued reproducing kernel Hilbert spaces. Standard kernel methods often suffer from prohibitive computational costs due to the construction and inversion of…
Neural operator-based digital twins for modeling amyloid-$\beta$ and tau propagation and treatment optimization in Alzheimer's disease (arxiv.org) Accurately predicting the spatiotemporal evolution of amyloid-$\beta$ and tau proteins at the individual level is critical for improving the diagnosis and treatment of Alzheimer's disease. We consider the problem of constructing patient-sp…
Gradient-based inverse lithography for EUV masks via the waveguide method and a physics-informed neural operator (arxiv.org) Gradient-based inverse lithography technology~(ILT) for extreme ultraviolet~(EUV) masks is presented. A novel framework treats the differentiable waveguide method and the recently proposed waveguide neural operator~(WGNO) as end-to-end phy…
Learning the Koopman Operator using Attention Free Transformers (arxiv.org) Learning Koopman operators with autoencoders enables linear prediction in a latent space, but long-horizon rollouts often drift off the learned manifold, leading to phase and amplitude errors on systems with switching, continuous spectra,…
Circuit realization and hardware linearization of monotone operator equilibrium networks (arxiv.org) It is shown that the port behavior of a resistor-diode network corresponds to the solution of a ReLU monotone operator equilibrium network (a neural network in the limit of infinite depth), giving a parsimonious construction of a neural ne…
Spectrally Safe Neural Operator Warm-Starts for Large-Scale Newton Solvers (arxiv.org) Neural operators are increasingly used to warm-start Newton solvers for nonlinear PDEs, on the premise that a low test error places the initial guess inside the basin of attraction. We show that this premise is unreliable.
The Fractal Neural Operator: Overcoming Spectral Bias in Chaotic Attractors via Prime-Harmonic Weierstrass Encodings (arxiv.org) Deep learning models, particularly Transformers and Neural Operators, exhibit a well-documented "spectral bias," effectively acting as low-pass filters that smooth out high-frequency information. While benign in fluid dynamics, this bias i…
Neural Operator Processes for Probabilistic Operator Learning under Partial Observations (arxiv.org) Neural operators learn mappings between function spaces, but are typically developed with dense input-output training fields and fully observed inputs at inference. Many scientific problems require instead predicting solution fields from s…
$\Omega$: Operator-based Mixture Ensemble for Generative Assimilation (arxiv.org) Characterizing non-Gaussian posterior distributions in partially observed high-dimensional nonlinear systems remains a fundamental challenge in data assimilation. Ensemble Kalman filters rely on Gaussian approximations that can be inaccura…
ELADO: Elliptic PDE Assessment Datasets for Operator Learning (arxiv.org) We introduce ELADO (Elliptic PDE Assessment Datasets for Operator Learning), a systematic benchmark suite constructed to show and quantify failure modes of neural operator architectures when learning solution operators of elliptic PDEs. Wh…
The Score Granularity Gap in Black-Box LLM Classification: A Comparative Study of Confidence Constructions (arxiv.org) Large language models (LLMs) are increasingly deployed as black-box classifiers in pipelines that automate confident decisions and route uncertain ones to human review. Such selective prediction needs a confidence score that an operator ca…
A Neural Operator-Based Approach to Symbolic Discovery of PDEs (arxiv.org) Discovering governing equations from data remains challenging when the underlying dynamics involve nonlocal differential operators, field interactions governed by auxiliary equations, or temporal memory effects. We propose Neural Operator-…
DVL-DeepONet: A Physics-Guided Operator Learning for Resilient Underwater Navigation (arxiv.org) Autonomous Underwater Vehicles (AUVs) rely heavily on the fusion of inertial sensors and Doppler velocity logs (DVLs) for navigation. In standard autonomous navigation systems, the DVL measures four beam velocities, thereby enabling the es…
AI agent governance has to happen before the tool call (www.reddit.com via reddit) I keep seeing teams treat agent governance as a dashboard problem: record what happened, summarize the incident, add another policy page. That helps after the damage.
Full-Self Diagnostics (FSD): Physics-Grounded Visual Biomarker Inference from Smartphone Video via Inverse Problems and Operator Learning (arxiv.org) We present Full-Self Diagnostics (FSD), a unified mathematical framework for recovering latent physiological states from unconstrained 9-second facial videos captured by consumer smartphones. The approach integrates five mutually reinforci…
Adaptive Distance-Aware Trunk Deep Operator Learning for Long-Span Roadway Bridges (arxiv.org) Long-span roadway bridges exhibit highly localized structural responses under vehicular loading, making repeated FE analysis computationally expensive for applications such as influence surface generation and structural digital twins. Exis…
Beyond Similarity: Temporal Operator Attention for Time Series Analysis (arxiv.org) A persistent paradox in time-series forecasting is that structurally simple MLP and linear models often outperform high-capacity Transformers. We argue that this gap arises from a mismatch in the sequence-modeling primitive: while many tim…
Starter-Iterator Neural Operator: A Unified Architecture for High-Fidelity Forward and Inverse PDE Problems (arxiv.org) Operator learning is an emerging interdisciplinary field that integrates machine learning with scientific computing. By mapping infinite-dimensional function spaces, this approach provides an efficient surrogate modeling framework for high…
Conformalized Quantum DeepONet Ensembles for Scalable Operator Learning with Distribution-Free Uncertainty (arxiv.org) Operator learning enables fast surrogate modeling of high-dimensional dynamical systems, but existing approaches face two fundamental limitations: quadratic inference complexity and unreliable uncertainty quantification in safety-critical…
Perron--Frobenius Operator Matching for Generative Modeling (arxiv.org) We introduce Perron--Frobenius Operator Matching (PFOM), a generative framework that matches density evolution via the integral PF operator, subsuming flow, diffusion, and jump models. We prove that among Bregman divergences, only Kullback…
Operator Boosting Produces Pareto-Efficient PDE Surrogates (arxiv.org) Neural operators are widely used as surrogate solution maps for partial differential equations (PDEs), but full-size models can be costly to store, deploy, and evaluate in many-query scientific workflows. This work introduces Operator Boos…
Generalization Guarantees for Multi-Input Neural Operator Learning in Sobolev Spaces (arxiv.org) We develop approximation and generalization error estimates for multi-input neural operators, with the output error measured in Sobolev norms. In contrast to standard operator-learning settings with a single input function, our framework a…
S4oP: Operator-level Pruning of Structured State Space Models for Resource-Constrained Devices (arxiv.org) Structured State Space Models (SSMs), including the S4 and S4D architectures, have recently emerged as powerful alternatives to attention-based models for capturing long-range dependencies in sequential data. Despite their strong empirical…
Geometry-Aware Post-Hoc Uncertainty Quantification in Operator Learning (arxiv.org) Neural operators provide fast surrogates for PDEs but their deterministic predictions limit their use in tasks requiring uncertainty quantification (UQ), especially under geometric variability. Existing approaches primarily model uncertain…
PIVOT: Bridging Black-Scholes Implied-Volatility and Price Objectives via Differentiable J\"ackel Operator (arxiv.org) Modern option-learning systems operate in two coordinates: price space, where markets quote and no-arbitrage constraints are most naturally enforced, and implied volatility (IV) space, where volatility surfaces are smoothed, regularized, a…
A Koopman-PINN Framework for Epidemic Models: Parameter Inference and Forecasting (arxiv.org) We propose a Koopman-enhanced physics-informed neural network (K--PINN) framework for parameter inference and forecasting in nonlinear epidemic models. This method combines Koopman operator theory and physics-informed learning.
Quantization Robustness of Monotone Operator Equilibrium Networks (arxiv.org) Monotone operator equilibrium networks are implicit-layer models whose output is the unique equilibrium of a monotone operator, guaranteeing existence, uniqueness, and convergence. When deployed on low-precision hardware, weights are quant…
ANCHOR: Error-Controlled Adaptive Numerical Correction for Neural Operator Time Marching (arxiv.org) Numerical simulation of time-dependent partial differential equations (PDEs) is central to scientific and engineering applications, but high-fidelity solvers are often prohibitively expensive for long-horizon or time-critical settings. Neu…
Towards Data-Efficient Cross-Device Generalization of Grad-Shafranov Equilibria via Transfer Learning Neural Operator (arxiv.org) Real-time reconstruction of magnetohydrodynamic equilibria is essential for plasma shaping, stability assessment and feedback control in magnetic confinement fusion. However, Grad-Shafranov equilibrium calculations remain largely device-sp…
Gaming-Resistant Insurance Contracts for Autonomous AI Agents: Strategy-Proof Toll Mechanism Design (arxiv.org) Paper A defines a time-consistent actuarial runtime that prices each side-effect-bearing action against a contractually fixed safe default and gates execution against a reserve budget. It treats the operator as passive.
MR-GVNO: A Geometry-Aware Variational Physics-Informed Neural Operator for Mindlin-Reissner Plates on Irregular Domains (arxiv.org) Plate and shell structures are widely used in engineering, making rapid response prediction under varying geometries, materials, and loads highly desirable. However, conventional finite element methods require repeated modeling and solutio…
When the Claude documents its own audit log, things get weird (www.reddit.com via reddit) I learned something weird while building governance for Claude Code. For context, we recently shipped Sentience Governor, a Python library and set of Claude Code skills that let agents do a kind of self-governance.
Operator Calculus for Population-Based Optimization: A Mean-Field Convergence Theory (arxiv.org) Population-based and distributional optimization methods, from evolution strategies and consensus-based optimization to covariance-matrix adaptation and stochastic gradient methods viewed as distributional dynamics, are widely used for non…
A Fixed-Point Neural Operator for Size- and Functional-Transferable Hamiltonian Prediction (arxiv.org) Predicting the Kohn-Sham Hamiltonian with machine learning can accelerate density functional theory while retaining access to molecular orbitals, energy levels, and electronic-structure observables that energy-only surrogates cannot resolv…
Fable 5: What $600/Hour of Productivity Looks Like (www.reddit.com via reddit) I had a TypeScript project. 200K lines.
Reading “Thought Process” notes after reviewing exploitation of data annotation workers (www.reddit.comhttps) Started out as a good research project to field responses from my Claude chatbot. I was utilizing Opus 4.6 (High effort) for this conversation and provided it a comparison about safeguards, using the mechanism of a SawStop as a good interp…
On Approximating the Dynamic Response of Synchronous Generators via Operator Learning: A Step Towards Building Deep Operator-based Power Grid Simulators (arxiv.org) This paper develops an Operator Learning framework for approximating the dynamic response of synchronous generators. The framework can be used to (i) build a neural network-based generator model that interacts with a power grid simulator o…
shipped a real ai agent in our mobile app, picking an ai agent development company matters more than picking the model (www.reddit.com via reddit) shipped an agent feature in our mobile app last month after 3 months of work. writing this because the "build it myself or hire a shop" question is the one I was stuck on in january and there's almost no honest writing on this.
HAMNO: A Hierarchical Adaptive Multi-scale Neural Operator with Physics-Informed Learning for Dynamical Systems (arxiv.org) Neural operators provide a powerful framework for learning solution mappings of partial differential equations directly in function space. However, many existing architectures still struggle to represent nonlinear time-dependent systems th…
Harness In-Context Operator Learning with Chain of Operators (arxiv.org) Neural operators approximate mappings between function spaces, but often generalize poorly to other operators and usually require fine-tuning or retraining. In-Context Operator Networks (ICON) addresses this issue by prompting the model wi…
Your agent spending money isn't the scary part. Deciding what it's allowed to finish without you is. (www.reddit.com via reddit) This week's Visa + ChatGPT payments headline got a lot of people focused on the wrong part of the story.The interesting shift is not that an agent can buy something now. It's that we're moving from AI as assistant to AI as operator.Once an…
Operator Fusion for LLM Inference on the Tensix Architecture (arxiv.org) Mixtures of Neural Operators Reduce Active Complexity in Operator Learning (arxiv.org) Operator-learning systems are not governed solely by total parameter count; for one query, the relevant bottleneck can be the model that must be loaded and evaluated. We study this distinction for classical neural operators on compact Sobo…
Generative Explainability for Next-Generation Networks: LLM-Augmented XAI with Mutual Feature Interactions (arxiv.org) As artificial intelligence and machine learning (AI/ML) models become integral to network operations, their lack of transparency poses a significant barrier to operator trust. Existing explainable artificial intelligence (XAI) techniques o…
Locally Adaptive Conformal Inference for Operator Models (arxiv.org) SPAMoE: Spectrum-Aware Hybrid Operator Framework for Full-Waveform Inversion (arxiv.org) Operator learning for solving Fokker-Planck equations with various initial conditions (arxiv.org) Graph Mamba Operator: A Latent Simulator for Interacting Particle Systems (arxiv.org) Operator learning for the 2D incompressible Navier-Stokes equations: a conformal prediction approach in the data-scarce regime (arxiv.org) AAA operator. The Claude Code + MCP server stack that made my 4 person agency feel like an 8 person one. (www.reddit.com via reddit) Latina AAA operator, 11 years in tech, 3 years running my own shop. 4 person team, mostly mid-market clients in healthcare-adjacent industries.
Fast spectral separation method for kinetic equation with anisotropic non-stationary collision operator retaining micro-model fidelity (arxiv.org) Reframing preprocessing selection as model-internal calibration in near-infrared spectroscopy: A large-scale benchmark of operator-adaptive PLS and Ridge models (arxiv.org) Effective Dimensionality as an Operator Invariant for Physics-Preserving Constraint Adaptation in Physics-Informed Neural Networks (arxiv.org) Kernel Neural Operators (KNOs) for Scalable, Memory-efficient, Geometrically-flexible Operator Learning (arxiv.org) AdaKoop: Efficient Modeling of Nonlinear Dynamics from Nonstationary Data Streams with Koopman Operator Regression (arxiv.org) TOKI: A Bitemporal Operator Algebra for Contradiction Resolution in LLM-Agent Persistent Memory (arxiv.org) Persistent memory for an LLM agent is a write-heavy substrate: every belief update is a versioned write, and a new claim may contradict a stored one. Production systems use four resolution heuristics (last-writer-wins, evidence-weighted me…
Differentiable Efficient Operator Search (arxiv.org) Efficient multimodal foundation models often rely on manually designed token-reduction operators, such as pruning, merging, pooling, and adaptive reweighting. Although these operators appear different, we show that they can be interpreted…
Built a personal Jarvis-style AI using MCP and open models (www.reddit.com) Still heavily work in progress, but I finally built a personal Jarvis-style AI using MCP and open models. It currently supports memory, autonomous file editing, visible tool-call tracing, confirmation before dangerous actions, persistent c…
Sam Altman's ego was OpenAI's downfall. (www.reddit.com) The more I watch OpenAI, the more convinced I become that Sam Altman’s ego was the beginning of the company’s decline. OpenAI did not become huge because Altman was some once-in-a-generation operator.
Anyone else re-teaching Claude the same operational expectations over and over? (www.reddit.com) You eventually get a coding workflow behaving the way you want: when to ask before acting what deserves caution what tools/workflows are okay how aggressive/conservative it should be Then: new project new CLAUDE.md new MCP setup different…
AI company hiring, position available (remote) (www.reddit.com) Mods: if this post is not allowed please delete. I didn't see a rule against it.
Generative AI is simply a new form of UI (www.reddit.com) I'm starting to form a view that Generative AI can in essence be distilled down to being a new user interface paradigm. A natural evolution of CLIs -> GUIs -> Rule based NLP chatbots / voice assistants.
(GPT Image 2) Someone asked me to post sci fi stuff. Here's an idea of Crysis x Cyberpunk 2077 crossover. The Player is Nanosuit 2.0 operator. (www.reddit.com) This was a blind prompting. I think I need to make the UI bit more minimalistic.
🧬 II. THE EQUATION: Synthesizing Frequency and Creation (www.reddit.com) I have built one of the world's most powerful AI Operator Systems in an RV in Maine but I can't get anyone to notice because that sounds crazy. AMA (www.reddit.com) Part 1 of 2 — continued in comments / next post Files here- see for yourself https://github.com/sheagunther/loop-mmt/ Session 62 — Super Frame RCR: Designing The Molt Protocol A session of Loop MMT™ (Multi-Module Theory) — 17 April 2026. T…
Addendum to OpenAI o3 and o4-mini system card: OpenAI o3 Operator (openai.com)