Hey sir. We are not asking you to open source Anthropic. Just don’t lobby the government to shut down others who do. Jensen never framed other chips as “dangerous” or decides who can use CUDA based on who’s “safe”.

What Kimi K3 means for USA AI: 1. FYI Kimi K3 is open weight and will be released on July 27, 2026. 2. When the best open weight model exceeds the best closed-source model, how does @AnthropicAI justify its Fable pricing? Why would anyone pay for that? Not to mention the Mythos drama and dumbing down for "safety reason". Kimi doesn't care about "safety", 3. Kimi's most recent funding round values the company at $20 Billion as of 2 months ago. Anthropic is worth almost 1 Trillion, 50x. Why? 4. If enterprises get to use best frontier model while keeping their data in house, why would they EVER use Anthropic and give away their data? 5. If China can build better models in-house with chip blockage, why the fuck did we ban @nvidia from selling their best chips. What's scarier is if Huawei became the status quo for chips. Nightmare. 6. China has way more frontier labs than USA: Kimi, GLM, Deepseek, Alibaba, Bytedance, Kling etc. Not to mention for multimodal models like video gen, China has dominated the rank for a while. Meanwhile, we only see OpenAI & Anthropic performing even close. What does it mean for USA to keep its tech advantage?

Why do you think Chinese labs only got there by distilling alone and lack all other methods? Did you know the top researchers in Chinese labs went to the same top university with similar GPAs as the top researchers in OpenAI/anthropic, which are mostly Chinese as well?

My bet: @thinkymachines will soon make more money than @AnthropicAI. Not by winning the race to build one standardized frontier model. By becoming the Palantir FDE for enterprise custom models. The playbook: 1. Release the best American open-weight model. 2. Drive widespread enterprise adoption. 3. Charge the largest companies 7–9 figures to post-train and run custom models behind their own firewall. The model rests on three bets: 1. Large enterprises will increasingly demand their own models with their own data, and this is how they differentiate and win. 2. Enterprises won’t need just one model. They’ll continuously need new models for different workflows, departments, and proprietary datasets. That creates extremely sticky, recurring revenue. 3. Autoresearch will make custom model development increasingly scalable. Tinker can become the interface enterprises use to post-train their own models—with @thinkymachines providing the expertise and infrastructure behind it. FDE, infra, everything, huge contracts. 4. Eventually, maybe everyone wants their OWN model, and autoresearch and training inside tinker on top of @thinkymachines's base model will make it happen. Meanwhile, Henry-ford-styled, standardized models will makes no margins. OpenAI and Anthropic will have their API margins squeezed by Deepseek/GLM/Grok/Meta etc, and their consumer subscriptions are loss centers. The fat margin will move to customization: proprietary data, post-training, evals, deployment, and infrastructure. If this thesis is right, @thinkymachines isn’t building just another frontier lab. It’s building the highest-value layer between frontier research and enterprise model ownership. Turns out, the best business model for enterprise is NOT to sell commodity API access. Sell them their own models. I’m extremely bullish on this approach. @miramurati may be the most commercially savvy frontier-lab leader. I have to admit it.

PG&E doesn't cut off your electricity because it disagrees with the websites you visit. If intelligence is becoming a utility like electricity or water, why should we let Claude decide what's ok? - Everyone should have access to this basic utility. - No single company or party should be able to arbitrarily revoke that access simply because they don't like it. - Claude has never clearly explained what "safety" means in practice or how its standards relate to existing laws. They consistently issued arbitrary bans on who can use it, what they can use it for, and how to use it. I respect Dario and can see him standing alongside Thomas Edison, James Watt etc. in history (coding is the foundation of agents). That's why he cannot run Claude like a private membership club in NYC.

If you compare @openrouter's ranking July 2025 v.s. July 2026, Claude and Gemini was dominating in 2025 but today top 5 are all Chinese models, and Gemini was no where to be found in the ranking. Total token usage grew from 2.3T a day to 46.7T a day, 20x in a year and Chinese models quickly gained market share.

Turns out Elon is right again. The shittiest layer in AI is the model layer. The real money in AI is in compute, energy, and applications. Elon has all 3. Without Chinese open weight models, OpenAI and anthropic would have been happy oligopolies and made trillions. Now, they hired the best talents, burned billions and built the newest model, only to have Chinese free models wiping out all your margins. Every other layer is making money except for you, even though you invented the whole thing. That must feel shitty as hell.

The worst case scenario for USA AI: 1. Chinese open sources keep gaining market share. China owns the model layer. 2. Those models were trained and inference-optimized on Huawei chips instead of NVIDIA. China also owns the chip layer. 3. US doesn't build data centers fast enough to keep up with the demand of compute, storage and energy. China meanwhile exports the inference and training layer(for continual training it will happen along with inference) Export control is not the right strategy here. Simply banning "open source from China" doesn't solve the issue here. USA must invest in open source models, hopefully get Chinese models to use NVIDIA, and invest in nuclear asap.

American and European enterprises will ditch OpenAI and anthropic and adopt Chinese models. Here’s why: 1. They can host Chinese models under their own GPUs so it’s still compliant and they would argue they have more control. 2. they will post train with their own data on top of Chinese models. That’s how they build data moat. 3. They will not trust anthropic who will retain their data at any time for “safety” concerns like how they did with Fable and then try to build the same thing like how anthropic did with healthcare and legal. 4. They need to justify their AI spend and ROI. The cure is a reliable America open source model but there is none. After all, if giving away all your data and AI control at the mercy of anthropic and OpenAI means you care about safety and compliance, you are outright stupid.

China’s AI playbook: kill OpenAI and anthropic with free great models. Make it free. Then use cheap electricity to export compute as well. Currently the blocker is chip but Hauwei would catch up soon. Imagine a world where instead of paying hundreds of billions to OpenAI and anthropic, you pay almost zero to similar level of intelligence with cheap cheap inference. What’s gonna happen?

Most solo companies fail for the same reason: no real unfair advantage. AI can cover your weaknesses to a 60/70 level. Better than random hires who cost you equity and leave. But it CAN'T invent your edge. That 90/100 skill, network, or insight — that's still on you. Once you have it though: AI learns how you operate and scales it. Your strengths get amplified. Your gaps get covered. And the game changes entirely. Used to take years to test one idea. Now it takes hours. So stop betting on one thing. Test 100. Kill the losers fast. Double down on what works. That's the one-person company playbook.