For those who like to read, I wrote about frontier labs, open models, and the shifting incentives. 🔗 fareesh.com/post/the-moat-ju…

This is a *way* bigger deal than it seems... Frontier AI companies will *never* own the frontier again I kid you not... I've been waiting for someone to show this result for like 4 years... this is a huge deal. The short reason: combinations of models will *always* outperform individual models The long reason: this is the gateway to a million times more data... and huge leaps in compute efficiency. The AI scaling laws always win. More in article below 👇

the clanker and i in the google meet

1.5 billion people dwindling water supply 100% ethanol screenshot the tweet, return in 10 years

No one should be surprised by this. The USA is doing what any self-interested nation state would do. The real question is why are Europe, Canada, Australia, Korea, Japan and UK not able to compete seriously. That is the question everyone in government needs to answer. And no, having a couple of startups that have raised $1B or $2B is FAR from enough to compete with $100B American companies. The scale matters. Imagine your sword’s length is 1cm and your rival’s 1m — no match. Here is the harsh math (thanks to a poor version of Claude): •10,000 GB200 superchips ≈ ~278 NVL72 racks. •Each NVL72 rack costs roughly $3M–$3.5M. •That puts the full-system total around $830M–$970M, before networking, power, cooling, and datacenter buildout. That would enable you to train a model that was Sota 2 years ago. You need about 5 to 7 times this to compete today. So the starting bill is $5B, but even if you have this, here is the reality: there’s no available chips. So when you hear someone raised $1B, remember this is going back to American compute, and is simply not enough. The other two ingredients for AI are data and people. American startups pay better than European ones, so the people vote with their feet so they can pay their mortgage and send kids to school. An experienced AI engineer makes double the salary in Europe by working for an American startup (like Anthropic) than a European one, and about ten times more if they work for a USA corporation. There are however amazing European startups, but the money and ambition is lacking. The USA is far more relaxed with data and fair use - Canada is good too and @cohere is doing fine thanks to this. So American companies have a strong advantage over European ones. Brussels and the UK think they can hold the world to their questionable “ethical” views on data but they are just destroying the local AI industry, and in the process falling into a very precarious situation. They are partly responsible. Only the French minister has stood by their local LLM @MistralAI … and I guess more recently Germany has started to wake up. The hope is of course LLM startups like @MistralAI and @cohere which are a year or so behind but can provide personalised services, and amazing startups like @cusp_ai @IneffableLabs @nscale @Orbital_Ind @bfl_ai and a few others. But for all these, it’s incredibly hard to compete.

a brazilian municipal corporation fine-tuned a llm and you're laughing?

I get the impression that a lot of people, including many with advanced degrees, don’t know that if Elon Musk tried to sell all of his stock at once the value of the stock would go down. It’s like the people who think if we find a gold asteroid it’d be worth the current price of gold when brought to market.

kim k got hamilton on that anti aging regime and he's back to 2020 lewis

evergreen

Kimi 2.7 ranked 2nd after Fable 5 and before GPT-5 xhigh We have re-run our ErdosBench smoke test on 14 problems with Kimi 2.7, Qwen 3.7 Max, Grok 4.3 and compared it with the top performers from previous runs. Kimi 2.7 is amazingly good. More below.

Intelligence should be open, accessible, and ready to build with, empowering every developer, everywhere. GLM-5.2 is now available to all GLM Coding Plan users, including Lite, Pro, Max, and Team plans. docs.z.ai/devpack/latest-mod… As our new flagship model, GLM-5.2 delivers powerful coding capabilities, usable 1M-context support, and continued strengths in long-horizon tasks. API and Chatbot services will launch next week. The model will also be officially open-sourced next week under the MIT License. The future of AI is open, and it belongs to the people.

communist tries to do math on net worth

delusional to think any country is going to catch up to the USA or China in cutting-edge fields like frontier LLM development or GPUs will take 100-200 years it is sound game theory in the meantime to just cooperate and know your place in the world

kimi 2.5 was great kimi 2.6 was schizo kimi 2.7 is a return to greatness

Neil de Grasse Tyson is a psy-op, promoted by shallow materialists and 'gotcha' journalists. He replaced the cosmic wonder and scientific spirituality of Carl Sagan with shallow, glib, obnoxious pedantry He hated SpaceX every step of the way, resentful at success of another

this benchmark seems solid because it lines up with my experience kimi is goat tier glm also good minimax slightly worse nemo capable but lazy deepseek fast but decent for busywork

Meet Kimi-K2.7-Code 👀 Here’s what developers should know to fully unlock K2.7-Code potential：

person of interest is an underrated show jesus christ and ben from lost team up with big brother and the local police to save random people

me when i am c with the model

oh i have nemo ultra tokens lets go

out of tokens on literally everything