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Reformatted Anthropic data from a paper analyzing 1M Claude conversations into over/underrepresentation relative to workforce share. Interesting to see arts/design so high.

https://huggingface.co/tencent/HY-Embodied-0.5 I was reviewing this new model and trying to figure out if it’s actually useful or just another VLM release with different branding. Main thing that seems different is the focus on spatial + e…

Hey. I use Claude Code (CLI) with an API key my company provided for employees.

This week at Iceberg Summit, a friend and I got into a pretty heated discussion about Kafka. Specifically: in the age of AI agents, does Kafka compatibility still matter as much as we think it does?

EDIT SINCE YALL THINK IM TRYING TO STIR UP SHIT: Here's a video https://streamable.com/td862d Compare https://claude.com/pricing vs https://claude.ai/pricing The .com pages reroute to the new .ai pages. When you click thru the $17 plan, it…

Mnemostroma The memory layer for AI agents μνήμη (mnḗmē, memory) + στρῶμα (strôma, layer) — the substrate everything rests on. You open a new chat.

MemPalace The highest-scoring AI memory system ever benchmarked. And it's free.

I’ve been experimenting with how information consumption changes in an agentic internet, and this setup has been surprisingly powerful. Instead of scrolling feeds or relying on algorithms, I set up agents that roam the web based on my pref…

Inference engine used (vllm fork): https://github.com/ai-infos/vllm-gfx906-mobydick/tree/main Huggingface Quants used: cyankiwi/MiniMax-M2.7-AWQ-4bit Relevant commands to run: docker run -it --name vllm-gfx906-mobydick-mixa3607 -v ~/llm/mo…

Anthropic on Thursday announced a new artificial intelligence model, Claude Opus 4.7, which the company said is an improvement over past models but is "less broadly capable" than its most recent offering, Claude Mythos Preview. Claude Opus…

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Opus 4.7 Previous Opus models Hi, Back with the pelican test. Context: https://www.reddit.com/r/ClaudeAI/comments/1qx9fxa/opus_46_pelican_test/ Prompt: Generate an SVG of a pelican riding a bicycle One thing I noticed with the new claude p…

Qwen3.6-35B-A3B on my laptop drew me a better pelican than Claude Opus 4.7 16th April 2026 For anyone who has been (inadvisably) taking my pelican riding a bicycle benchmark seriously as a robust way to test models, here are pelicans from…

Hey HN! We're Charles and Dean, and we're building Stage: a code review tool that guides you through reading a PR step by step, instead of piecing together a giant diff.

I’ve been experimenting with how we consume information in an agentic internet. Feels like there’s a way to move beyond feeds, hooks, and algorithm-driven noise.

Every single response mentions malware. Is this my environment only or are others getting this too?

We describe a design pattern and protocol that lets you bootstrap a maximally strong evaluation stack for the AI features in your codebase with minimum effort. The aim is to remove the gruntwork often involved with evals by automating as m…

I’m building some infrastructure around AI agents and I’m trying to understand how people are actually using them in real workflows, not demos. Specifically curious about: - What your agent actually does day-to-day (not hypotheticals) - Wh…

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so i tried adding openui to openwebui and it worked pretty well. used it with gpt-5.4-mini and it was super fast and responsive.

I use cursor for my trading bot , last month bot crashed and to debug or for some upgradation I pay and get one month paid plan and use only for one day . and today I again facing some problems in my bot and 2 days ago my cursor plan was e…

I work with multiple AI tools on same project, and I keep seeing this issue. Tool A already explored context, but Tool B starts same research from zero again.

Here is how to run the new Qwen3.6-35B-A3B > At full context on a 4090 - IQ4_XS gguf with llama cpp > At full context on a Spark - FP8 with a tweaked vLLM Here is the docker compose with llama cpp services: llamacpp: container_name: llamac…

Most agent memory is just a wrapper for a vector DB. I wanted something that runs entirely on my machine and actually "learns" from failures.

Been running ACE-Step 1.5 on MLX for a couple months and wanted to share performance notes since the model doesn't get much coverage here compared to the image/text side of local gen. Context on the model for anyone who hasn't seen it: ACE…

so many people use cursor only when there bot/ website crashed and they need cursor only for 1 or 2 day so for them who are not full time developer cursor should start a weekly plan also.

Been hitting the same wall for a while: every new session with an LLM agent starts from zero. You explain your stack, your constraints, your decisions - then open a new chat and do it all again.