I just cancelled my $200 Claude Max plan and replaced it with SuperGrok Heavy. I've been a Claude alpha user years now. Fable 5, Opus 5, Sonnet 5 have all gotten slow and lazy. Yesterday Fable 5 took 25 minutes to restyle a dropdown menu. This has made the model unusable in my workflow. Grok 4.6 is the most balanced model right now on cost, speed, and intelligence combined.

going to world cup games is always awesome, but watching the USA win in the USA during USA birthday week was just incredible

Microbiome research meets AI! Nature explores how AI can decode microbial ecosystems, accelerating discoveries. For Agentic Engineering, this means smarter bio-AI agents. Ready to build the future? Join our #AgenticEngineering Training! #AI #LLM Read more: news.google.com/rss/articles…

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We're partnering with SpaceX to improve Composer. cursor.com/blog/spacex-model…

Coffee breaks in Abu Dhabi. ☕️ What's your Abu Dhabi POV? Post it with in Abu Dhabi

Claude Opus 4.7 is BenchMaxed. 75% of the BridgeMind community says so. #1 on BridgeBench overall. But the vibe coders who actually use it every day say it's not that much better than Opus 4.6. Great benchmarks. Same rate limits. Reduced security. The community isn't buying the hype.

Claude Opus 4.7 vs Claude Opus 4.6 Which lava lamp is better?

Claude Opus 4.7 is 26% faster than Opus 4.6. 116.4 tokens per second vs 92.2. Time to first token cut in half. 852ms vs 1,922ms. Cost per task dropped from $2.80 to $0.93. Faster. Smarter. Cheaper per task. Anthropic actually delivered on this one. Still not faster than Grok 4.20 at 243 t/s though. Speed crown still belongs to xAI. bridgebench.ai

This robotic hand can be 3D printed by anyone and assembled in under 8 hours. Researchers at ETH Zurich created the Orca hand, fully open-sourced with artificial bones and tendons. For context, advanced robotic hands cost over $100,000 and require constant maintenance... Orca costs under $2,000. 50x less (!) A self-calibration system maps every motor to every joint, eliminating the manual tuning that tendon-driven hands usually need. Each fingertip has built-in tactile sensors covered by silicone skin. The hand can actually feel when it touches something, giving it feedback to grip objects without crushing them or letting them slip. It can hold over 20 lbs, learn tasks by watching human demonstrations, and transfer skills trained in simulation directly to the real world. The team proved its durability by having it pick up and place a cube over 2,000 times across 7 hours with no human intervention. The full design files and source code are open source, so any robotics lab in the world can start building one today.

I think it's a good direction (for Read endpoints, not for Write), I tried to use it for a project ~2 weeks ago but about 30 minutes of hacking around cost me $200, the pricing is imo really excessive. The docs were hard to ingest into agents because it's a lot of individual short pages, I think a big intro markdown doc, or a few of them behind simple curl locations. Also, the current version of docs seems to have no mention of XMCP? Or at least the Search / Grok Assistant seems to say there are 0 mentions of such a thing anywhere in the docs.

Something I've been thinking about - I am bullish on people (empowered by AI) increasing the visibility, legibility and accountability of their governments. Historically, it is the governments that act to make society legible (e.g. "Seeing like a state" is the common reference), but with AI, society can dramatically improve its ability to do this in reverse. Government accountability has not been constrained by access (the various branches of government publish an enormous amount of data), it has been constrained by intelligence - the ability to process a lot of raw data, combine it with domain expertise and derive insights. As an example, the 4000-page omnibus bill is "transparent" in principle and in a legal sense, but certainly not in a practical sense for most people. There's a lot more like it: laws, spending bills, federal budgets, freedom of information act responses, lobbying disclosures... Only a few highly trained professionals (investigative journalists) could historically process this information. This bottleneck might dissolve - not only are the professionals further empowered, but a lot more people can participate. Some examples to be precise: Detailed accounting of spending and budgets, diff tracking of legislation, individual voting trends w.r.t. stated positions or speeches, lobbying and influence (e.g. graph of lobbyist -> firm -> client -> legislator -> committee -> vote -> regulation), procurement and contracting, regulatory capture warning lights, judicial and legal patterns, campaign finance... Local governments might be even more interesting because the governed population is smaller so there is less national coverage: city council meetings, decisions around zoning, policing, schools, utilities... Certainly, the same tools can easily cut the other way and it's worth being very mindful of that, but I lean optimistic overall that added participation, transparency and accountability will improve democratic, free societies. (the quoted tweet is half-ish related, but inspired me to post some recent thoughts)

Excited to launch Gemma 4: the best open models in the world for their respective sizes. Available in 4 sizes that can be fine-tuned for your specific task: 31B dense for great raw performance, 26B MoE for low latency, and effective 2B & 4B for edge device use - happy building!

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