#大佬观点

"Energy Capacity = Economic Capacity" Former Intel CEO Pat Gelsinger on why America's power grid is the ceiling on growth: "We went through 10 to 15 years where essentially I was taking coal offline at the rate I was adding renewables, and essentially the nation was flatlined in terms of overall energy capacity." "So essentially our economic capacity as a nation, flat for fifteen years." "Even with that, we've gone to maybe increasing our national energy capacity 4% per year. Going from essentially zero to one." "Nuclear as base load is a fabulous thing that we want to go build more of. Unfortunately all of our renewables have deep dependencies in China." "Energy capacity somewhat dampens how euphoric we can get on AI. Why build a new data center and buy the million GPUs if I can't power them?" @PGelsinger @RaghuRaghuram @appenz

"Energy Capacity = Economic Capacity" Former Intel CEO Pat Gelsinger on why America's power grid is the ceiling on growth: "We went through 10 to 15 years where essentially I was taking coal offline at the rate I was adding renewables, and essentially the nation was flatlined in terms of overall energy capacity." "So essentially our economic capacity as a nation, flat for fifteen years." "Even with that, we've gone to maybe increasing our national energy capacity 4% per year. Going from essentially zero to one." "Nuclear as base load is a fabulous thing that we want to go build more of. Unfortunately all of our renewables have deep dependencies in China." "Energy capacity somewhat dampens how euphoric we can get on AI. Why build a new data center and buy the million GPUs if I can't power them?" @PGelsinger @RaghuRaghuram @appenz

TypeSafe AI's Diogo Almeida on why Jev is called Jev, and what cheap intelligence finally changes about software: "It's wild that AI is so cool and software has been unchanged in 10 years... The most we can do is add a little chatbot in the side sometimes that can take actions, but not all actions." "TypeSafe is making AI for software. We want to make AI powerful, not just for humans in the loop, but to actually build real software." "It's about the laziness to spend 10 hours to do the five-minute task instantly and to never have to do it again. It should be an ROI decision for people who automate stuff. I would just like it to be automatable." "I think that people will just make new kinds of work, hence the Jev in Jevons. New kinds of work once that stuff is doable." "As we have lots of intelligence at lots of different cost and speed trade-offs, the super systems-y types will be making trade-offs. Jev's gonna be 1000x too smart for them. They just want an approximate guess to optimistically route here and there." Martin Casado: "The good news is we get to rebuild systems again. We have a new primitive. It's kind of a new way of thinking about doing software." @CompleteSkeptic @typesafeai @bhorowitz @martin_casado

The full walkthrough of our @nvidia Vera benchmark below.

launched a model accidentally served trillions of tokens a day 29.4% of the fortune 500 showed up raised a really big series A from @a16z it's been 3 weeks we would like to sleep now

Former Intel CEO Pat Gelsinger with a16z's Raghu Raghuram and Guido Appenzeller on the next wave of semiconductor innovation and the physical constraints shaping the AI buildout: Drawing on his experience designing Intel's 386 and 486 processors, Pat explains how AI could transform chip design, but also why faster design alone won't solve the industry's biggest problems. They examine the bottlenecks in manufacturing, memory bandwidth, advanced packaging, and power, and why today's explosion of specialized AI chips may eventually consolidate around a smaller number of architectures. They also discuss the potential for new memory technologies, the shift from copper to optical networking, and why energy capacity could become a major constraint on AI growth. Finally, they revisit Pat's VMware years to ask what virtualization might look like when infrastructure is built for agents rather than humans. YouTube: https://youtu.be/1Q_7yU7FZ1k 1:05 Hired by Intel at 18 3:50 Arguing with Stanford professors 7:25 Will AI design the next gen chips? 8:45 Designing faster than fabs can build 11:55 Why GPUs are stuck with bad memory 13:40 Why 100 AI chips will collapse to a few 19:15 Agents make new chips cheap to run 22:10 No new memory chip since the 90s 27:20 Why 16-layer chip stacks are a fantasy 32:15 The physics that keeps memory next to compute 34:55 "I declared the death of copper" 38:05 AI traffic breaks the internet's design 42:40 "Energy capacity equals economic capacity" 46:25 The 130-year-old power war AI reopened 48:50 VMware for agents @PGelsinger @RaghuRaghuram @appenz

Former Intel CEO Pat Gelsinger with a16z's Raghu Raghuram and Guido Appenzeller on the next wave of semiconductor innovation and the physical constraints shaping the AI buildout: Drawing on his experience designing Intel's 386 and 486 processors, Pat explains how AI could transform chip design, but also why faster design alone won't solve the industry's biggest problems. They examine the bottlenecks in manufacturing, memory bandwidth, advanced packaging, and power, and why today's explosion of specialized AI chips may eventually consolidate around a smaller number of architectures. They also discuss the potential for new memory technologies, the shift from copper to optical networking, and why energy capacity could become a major constraint on AI growth. Finally, they revisit Pat's VMware years to ask what virtualization might look like when infrastructure is built for agents rather than humans. YouTube: https://youtu.be/1Q_7yU7FZ1k 1:05 Hired by Intel at 18 3:50 Arguing with Stanford professors 7:25 Will AI design the next gen chips? 8:45 Designing faster than fabs can build 11:55 Why GPUs are stuck with bad memory 13:40 Why 100 AI chips will collapse to a few 19:15 Agents make new chips cheap to run 22:10 No new memory chip since the 90s 27:20 Why 16-layer chip stacks are a fantasy 32:15 The physics that keeps memory next to compute 34:55 "I declared the death of copper" 38:05 AI traffic breaks the internet's design 42:40 "Energy capacity equals economic capacity" 46:25 The 130-year-old power war AI reopened 48:50 VMware for agents @PGelsinger @RaghuRaghuram @appenz

AI agents don't use the cloud like humans do. AWS CEO Matt Garman on rewiring AWS for its newest "users": "Increasingly we're seeing teams that want a cloud that is great to work with agents and not just with people." " We've doubled down on things like starting a database in three seconds and some capabilities that agents are excited about." "Many agents wanna create a database, do a little bit of work, and then have the database go away. You don't really need that database to have five nines of durability." "There are new building blocks that agents are gonna want that we just didn't really need before: compute sandboxes, gateways, agent permissions versus people or service role permissions." " A lot of those are things that we have built and are building and thinking actively about because they are just brand-new building blocks. It's not using the existing building blocks differently." @mattsgarman @RaghuRaghuram

.@POTUS presents the National Medal of Science to Sergey Brin, @JensenHuang, @elonmusk, and @LisaSu, and the National Medal of Technology and Innovation to @MichaelDell and @satyanadella.

AWS CEO Matt Garman 与 a16z 的 Raghu Raghuram 对谈：全球最大云提供商如何为智能体时代重构： 2026 年 2200 亿美元资本支出，订购 200 万块 NVIDIA GPU，AWS 自研 AI 芯片明年之前售罄，还推出无需信用卡、30 秒即可开通的 AWS 账户，让智能体立即动起来。 0:55 营收 1700 亿美元，增长 37% 2:40 30-40% 的营收最初来自初创公司 4:55 初创公司想要面向智能体的云 9:10 30 秒开通 AWS 账户 12:25 智能体不需要坚不可摧的数据库 16:30 为什么 AWS 不会把所有 GPU 卖给前沿实验室 22:00 为什么 Matt 不担心泡沫 24:45 为什么 AWS 自建电厂 27:45 为下一次供应短缺做规划 30:25 为一个县每位居民节省 5000 美元 33:10 AWS 如何打造自研芯片 40:05 是什么阻碍了企业级智能体 45:35 为什么 Bedrock 从不把你的数据发给模型 49:30 AWS 的新 AI 安全工具 51:50 为什么 AWS 的 10 人团队如今只需 3-4 人 YouTube: https://www.youtube.com/watch?v=rn_afJaPldg @mattsgarman @awscloud @RaghuRaghuram

As much as the $70B hockey sticks charts were fun to look at, $50B of OpenAI ARR implies a similar y/y growth rate to Jul and Aug (225%+ y/y), which makes more sense.

AWS CEO Matt Garman 与 a16z 的 Raghu Raghuram 对谈：全球最大云提供商如何为智能体时代重构： 2026 年 2200 亿美元资本支出，订购 200 万块 NVIDIA GPU，AWS 自研 AI 芯片明年之前售罄，还推出无需信用卡、30 秒即可开通的 AWS 账户，让智能体立即动起来。 0:55 营收 1700 亿美元，增长 37% 2:40 30-40% 的营收最初来自初创公司 4:55 初创公司想要面向智能体的云 9:10 30 秒开通 AWS 账户 12:25 智能体不需要坚不可摧的数据库 16:30 为什么 AWS 不会把所有 GPU 卖给前沿实验室 22:00 为什么 Matt 不担心泡沫 24:45 为什么 AWS 自建电厂 27:45 为下一次供应短缺做规划 30:25 为一个县每位居民节省 5000 美元 33:10 AWS 如何打造自研芯片 40:05 是什么阻碍了企业级智能体 45:35 为什么 Bedrock 从不把你的数据发给模型 49:30 AWS 的新 AI 安全工具 51:50 为什么 AWS 的 10 人团队如今只需 3-4 人 YouTube: https://www.youtube.com/watch?v=rn_afJaPldg @mattsgarman @awscloud @RaghuRaghuram

https://x.com/i/article/2108225380985536512

AWS CEO Matt Garman 与 a16z 的 Raghu Raghuram 对谈：全球最大云提供商如何为智能体时代重构： 2026 年 2200 亿美元资本支出，订购 200 万块 NVIDIA GPU，AWS 自研 AI 芯片明年之前售罄，还推出无需信用卡、30 秒即可开通的 AWS 账户，让智能体立即动起来。 0:55 营收 1700 亿美元，增长 37% 2:40 30-40% 的营收最初来自初创公司 4:55 初创公司想要面向智能体的云 9:10 30 秒开通 AWS 账户 12:25 智能体不需要坚不可摧的数据库 16:30 为什么 AWS 不会把所有 GPU 卖给前沿实验室 22:00 为什么 Matt 不担心泡沫 24:45 为什么 AWS 自建电厂 27:45 为下一次供应短缺做规划 30:25 为一个县每位居民节省 5000 美元 33:10 AWS 如何打造自研芯片 40:05 是什么阻碍了企业级智能体 45:35 为什么 Bedrock 从不把你的数据发给模型 49:30 AWS 的新 AI 安全工具 51:50 为什么 AWS 的 10 人团队如今只需 3-4 人 YouTube: https://www.youtube.com/watch?v=rn_afJaPldg @mattsgarman @awscloud @RaghuRaghuram