#大佬观点

CEO of Phison disagrees with the CXMT memory scare and calls it a "ghost story from the market." He states next year "there will be a shortage of everything except orders." He is more worried about the shortage of materials causing them to be unable to deliver on time than about the visibility of orders. $MU $DRAM $EWY

@ShuttleAlmanac @astro_reid @Astro_Jeremy @Astro_Christina @NASAAdmin Dose, yes. Preclude flying again, no. I could have walked on the moon, but I’d rather help someone else do it. That’s my truth, not speaking for anyone else.

BG2 w/ @JensenHuang. Does AI Revenue Justify Capex, ‘27 AI Bottlenecks, Singularity, Open vs Closed & more. 🚀🇺🇸 @altcap @_clarktang @nvidia

Hosting an 816B-parameter model on air-cooled hardware? Intel delivers Day 0 support for @Meta's Muse Spark Open using four 160GB Intel GPU D-series cards alongside Intel Xeon processors for flexible, memory-intensive enterprise AI. It is the most capable U.S. open-weights model to date. Learn more: http://ms.spr.ly/6013at3KN

Lightmatter👍

Old friends are the best friends. Jensen rocks. The Star Mind computer being co-engineered by SpaceX and Nvidia is far better than almost anyone expects and will reach volume production next year. Working with the incredibly talented Nvidia engineering team is pure joy!

Blue Origin recently raised $10B at a $140B valuation, despite generating just $800M in revenue in 2025. New Glenn has already suffered a launch failure, and its year-end launch timeline looks optimistic. Basically, Neutron and New Glenn could both be operational around mid-2027, give or take 2–4 months. Yet $RKLB is trading at a $35B market cap, just 25% of Blue Origin’s valuation. Make it make sense. 🚀

TLDR; we will probably never get another ARR number from Anthropic, which is healthy. Should force the market to move away from extreme focus on Anthropic/OpenAI ARR numbers to hyperscale growth rates, which are a much better metric for AI at this point given they capture Muse, Grok, Gemini and Open-Source. Anthropic FCF positive in Q3 and reaccelerating in October on Opus 5.5 per third party data. Roadshow in several weeks will happen after this has been widely confirmed. Unit economics much better than expected given positive FCF with 75% of their compute going to training. All per public reporting.   OpenAI continuing to grow at the same pace per Sarah Friar interview after they took share vs. Anthropic in Q3. Means the sum of Anthropic/OpenAI growth is accelerating from the Q3 pace. OpenAI probably hits FCF positive in the next few months.   Open-source growing much faster than either Anthropic or OpenAI. Modal tripled since May and is 15x YoY per yesterday’s announcement. Open-source tokens generate more revenue and profit for the hyperscalers/neoclouds than frontier tokens. *Every* open source inference cloud I am aware of is growing faster both sequentially and YoY than either Anthropic or OpenAI. And their combined compute spend is becoming material.   Third party data pointing to hyperscalers continuing to accelerate in Q3. All report in the next two weeks. Acceleration should continue in Q4 and Q1 as installed base of compute slowly reprices higher closer to spot and new capacity comes online at higher prices. Continued acceleration in hyperscalers should help address external funding concerns.   10 year yield down in a straight line over the last 24 hours.   Some risk of escalation in Iran next few days, but earnings and mid-terms probably outweigh taking an ultra long-term view and looking out 30 days.   Biggest risk imo remains cyber and OpenAI/Anthropic dominating the model layer. Fragmentation, competition and lower margins at the model layer are good for everyone else in the ecosystem and for America. Slower for longer is much better than an overbuild and an actual bubble.

I’ll be speaking at the SF Humanoid Hub Conference tomorrow 10/15! Thanks @TheHumanoidHub for inviting me😆

Speakers from 1X, Dyna Robotics, Skild AI, Google DeepMind, Physical Intelligence and more. Humanoid robots, dexterous hands and more cool robotics demos on the floor. The robotics community in one floor, and four NVIDIA Jetsons to give away. Agenda:

Nathan Lambert of @trillium_labs says Chinese AI researchers' jaws drop to the floor when he tells them how much compute OpenAI has: "The Chinese labs are very technically excellent. They are more compute-starved." "Without a doubt, they have a comparable talent pool to draw on... To say that China is anything but equal on talent, you're gonna have a hard time because they just have so many people being trained at such a high level." "What they don't have is compute." "You talk to people there, and you're like, 'Oh, I heard an average OpenAI researcher has five thousand H100 equivalents that they can access at any time,' and like their jaw just falls to the floor. They're just like, 'I can't comprehend.'" @natolambert @lishali88