Anthropic leak reveals new model "Claude Mythos" with "dramatically higher scores on tests" than any previous model
Update: The leaked draft blog posts have surfaced online, revealing Anthropic's plans for a new model class above its existing Opus line. The documents show two possible name candidates, details about a deliberately slow release strategy, and a strong focus on cybersecurity. The article Anthropic le
Claude can control your computer now, openclaw and zenmux updated same day
Anthropic just dropped computer use for claude. not just api calls anymore, it literally opens apps, clicks buttons, scrolls pages, types stuff. mac only for now which sucks for windows people but the capability is real. Same day openclaw pushed a major update too. new plugin sdk, clawHub as offici
llama.cpp: Prefetching weights when offloading to CPU
Hello r/LocalLLaMA, I put up an experimental PR which prefetches weights when offloading to CPU. Long story short from results it helps dense + smaller MoE models for PP (prompt processing). Give it a try if you are ram-rich and gpu-poor like me. [https://github.com/ggml-org/llama.cpp/pull/21067](h
Llama.cpp with Turboquant, Heavy-Hitter Oracle (H2O), and StreamingLLM. Even more performance!
After the great work yesterday of TheTom's work on showing Turboquant working in Llama.cpp I added a few other things that added some more complimentary speedups to Llama.cpp. so far CPU and CUDA build and are fully usable. I'm seeing full speed token generation on my 16gb 4060ti up to 256k+ context
Skipping 90% of KV dequant work → +22.8% decode at 32K (llama.cpp, TurboQuant)
I’ve been working on an open source TurboQuant implementation for KV cache compression in llama.cpp and ran into a hard bottleneck: dequantization. At long context (32K on M5 Max), dequant alone was taking around 40 percent of decode time. I tried fixing it the usual way: - register LUTs - SIMD
How we monitor internal coding agents for misalignment
How OpenAI uses chain-of-thought monitoring to study misalignment in internal coding agents—analyzing real-world deployments to detect risks and strengthen AI safety safeguards.
The risk of AI isn't making us lazy, but making "lazy" look productive
Looking for a solid ChatGPT alternative for daily work
I was long juggling separate monthly subscriptions for Claude, Gemini, and GPT-4 until the costs and tab-switching became a total mess and I started paying over 100 bucks each mont. Then, I tried consolidating everything into a single hub, done that both locally and online, both api and openrouter a
I cut Claude Code's token usage by 68.5% by giving agents their own OS
Al agents are running on infrastructure built for humans. Every state check runs 9 shell commands. Every cold start re-discovers context from scratch. It's wasteful by design. An agentic JSON-native OS fixes it. Benchmarks across 5 real scenarios: Semantic search vs grep + cat: 91% fewer tokens
AI overly affirms users asking for personal advice
Anyway to get close to GPT4o on a local model (I know it’s a dumb question)
At the risk of getting downvoted to hell, I am a ND user and I used 4o for emotional and nervous system regulation (nothing nsfw). I am also a music pro and I need to upgrade my entire rig. I have roughly $15k to spend and I was wondering if there’s anything I can run that would be similar in style.
David Sacks is done as AI czar — here’s what he’s doing instead
David Sacks, the venture capitalist and tech billionaire who'd become Silicon Valley's primary advocate inside the White House and a key architect of its aggressive AI policy initiatives, revealed on Thursday that he was no longer a special government employee - and therefore no longer President Don
Spanish legislation as a Git repo
Folk are getting dangerously attached to AI that always tells them they're right
Gemma 4
Sharing this after seeing these tweets([1](https://xcancel.com/patelnamra573/status/2037892455841075514#m) , [2](https://xcancel.com/veermasrani/status/2037912954570698961#m)). Someone mentioned this exact details on twitter 2 days back.
CERN uses tiny AI models burned into silicon for real-time LHC data filtering
A simple explanation of the key idea behind TurboQuant
TurboQuant ([Zandieh et al. 2025](https://arxiv.org/abs/2504.19874)) has been all the rage in the past two days, and I've seen lots of comments here attempting to explain the magic behind it. Many of those comments boil down to "dude, it's polar coordinates!!!", and that's really misleading. The mos
Me waiting for TurboQuant be like
OpenAI’s “Spud” Pivot Could Be Bigger Than Sora Ever Was
# TLDR OpenAI appears to be making a major strategic shift around a new unreleased model called Spud. The company is reportedly killing Sora, redirecting resources toward stronger core AI systems, and focusing harder on infrastructure, agents, and robotics. The bigger idea is that OpenAI seems to
Anthropic’s Claude popularity with paying consumers is skyrocketing
Estimates for total Claude consumer users are all over the map (we've seen figures ranging from 18 million to 30 million). Anthropic hasn't disclosed this data, but a spokesperson did tell TechCrunch that Claude paid subscriptions have more than doubled this year.