A surveillance state is not preferable to China "winning," and its also a false binary. America should be America; any descent into authoritarianism would be conceding defeat

In China, people almost never use standalone “AI” apps. There are basically AI-generation chat capabilities built into nearly every popular app in China. Not only that, but it’s integrated into almost every aspect of Chinese life— e.g. you’ll find photo booths everywhere with AI features and even coffee shops that take your picture and apply AI effects. This has become possible thanks to DeepSeek and other Chinese models continually improving their efficiency and cost, making it easier, more accessible, and cheaper to integrate these capabilities everywhere. This is what we should aim for.

Yesterday’s photo from the Wuzhen Internet Conference shows six founders from Hangzhou’s hottest tech startups on one stage. Unitree. DEEPRobotics. DeepSeek. They’ve been dubbed “The Six Little Dragons of Hangzhou.” The forum itself had little substance. Just another conference panel. What matters is what this image represents. Hangzhou flexing its tech muscle. How did a city without Beijing’s political clout or Shenzhen’s manufacturing base become home to China’s most interesting tech experiment? I wrote about this in October. It’s a free article. The piece examines how a city built on accidents created an ecosystem that now challenges assumptions about Chinese tech development. Alibaba’s shadow. DeepSeek’s moves against Nvidia. Government playing gardener. Networks that coordinate without a coordinator. Three questions drive the analysis. Where is innovation actually happening in China now? What matters more than individual breakthroughs? What happens when the capital cycle turns? Hangzhou offers one possible answer. Not a blueprint. A live experiment in whether improvised coordination can sustain itself.​​​​​​​​​​​​​​​​ hellochinatech.com/p/hangzho…

🚨 This might be the most mind-bending AI breakthrough yet. China just built an AI that doesn’t just explain how the universe works it actually understands why. Most of science is a black box of conclusions. We know the “what,” but the logic that connects everything the “why” is missing. Researchers call it the dark matter of knowledge: the invisible reasoning web linking every idea in existence. Their solution is unreal. A Socrates AI Agent that generates 3 million first-principles questions across 200 fields, each one answered by multiple LLMs and cross-checked for logical accuracy. What it creates is a Long Chain-of-Thought (LCoT) knowledge base—where every concept in science can be traced back to its fundamental truths. Then they went further. They built a Brainstorm Search Engine for inverse knowledge discovery. Instead of asking “What is an Instanton?”, you can explore how it emerges through reasoning paths that connect quantum tunneling, Hawking radiation, and 4D manifolds. They call it: “The dark matter of knowledge, finally made visible.” The project SciencePedia already maps 200K verified scientific entries across physics, math, chemistry, and biology. It shows 50% fewer hallucinations, denser reasoning than GPT-4, and traceable logic behind every answer. This isn’t just better search. It’s the first AI that exposes the hidden logic of science itself. Comment “Send” and I’ll DM you the paper.

🚨 Google just proposed training AI in space. Their new paper, “Towards a Future Space-Based, Highly Scalable AI Infrastructure System,” explores building orbital ML data centers powered directly by the Sun fleets of satellites running TPUs, networked by laser links. Why? Because AI compute demand is exploding faster than energy efficiency improves. The Sun outputs 100 trillion times humanity’s total electricity production and orbiting solar arrays get 8x more energy than Earth-based panels. Here’s what they actually tested: → TPUs in radiation - survived 5 years of equivalent cosmic exposure → Laser links - hit 1.6 Tbps in lab with off-the-shelf optics → Orbital design - 81-satellite cluster flying in 1 km formation, millisecond latency → Launch economics - with SpaceX’s learning curve, <$200/kg to LEO by 2035 makes space compute cost-competitive with Earth data centers The vision: autonomous satellite clusters forming solar-powered compute swarms - zero land, zero cooling water, full-Sun power. Google calls it a “moonshot for AI infrastructure.” The rest of us might be looking at the blueprint for the first interplanetary cloud.

🔵Tokyo Electron : The future of AI hardware will be defined by the convergence of physical scaling and heterogeneous integration. Transistor innovation alone is no longer enough. System performance now comes from co-optimizing logic, memory, interconnect, and advanced packaging as a unified architecture. GAA and CFET push logic scaling forward. Backside PDN improves power delivery. 4F² VCT and 3D DRAM continue density scaling. Yet the real breakthrough comes when everything is integrated: GPU/CPU cores surrounded by HBM, connected through 3DIC structures, and supported by ultra-flat wafers, known-good dies, and high-efficiency heat spreaders. This is the new era of AI semiconductors. The bottleneck has shifted from transistor count to how fast we can move data, stack memory, reduce thermal resistance, and pack heterogeneous functions into one compute engine. The next performance leaps won’t come from one domain. They will come from cross-domain integration. SemiVision

Didn't expect the post below to get so much attention. Actually, the robotics companies in the diagram are just a small part of a much bigger picture. Shenzhen alone is home to over 74,000 robotics-related companies.

The system is set up to extract wealth from Millennials and Gen Z and give it to Boomers: - NIMBY housing laws that make it impossible for first time homebuyers to afford a home. - Student debt that can't be paid off or discharged, leading to permanent wage depression. - State governments in unsustainable levels of debt to civil service pension funds while canceling those benefits for new hires. California pays an average of 102% of final earnings to retiring civil servants. - Proposition 13 lets longtime homeowners pay significantly less property tax than new ones. - Both Medicare and Social Security will not be fully funded starting in 2033. - Politicians are terrified of calling this out because 9 out of 10 people who go to their town halls are Boomers. I talked to one US Congressman who said "coming out too hard against Boomers is an almost sure way to lose an election". They're happy to call out billionaires but terrified to call out Boomers. Once you see it the first time, you see it everywhere.

Half of investors seem to think we are in a bubble. The other half do not. For reference, this is what valuation multiples looked like during the dot com bubble:

Chinese robotaxis are coming to Europe. Baidu’s Apollo Go launching this year in Switzerland. Pony.ai working with Stellantis to launch next year. Notably, these firms are working closely with European partners.

I have a hunch that current LLMs might make it easier to launch a brand new programming language, provided you can describe it in a few thousand tokens and ship it with a compiler and linter that coding agents can use simonwillison.net/2025/Nov/7…

Ok, chart updated with the latest info I could track on who has the power. Would be super interesting to layer the @SemiAnalysis_ cluster max ratings on top of this :) More bare metal deals coming from the big hyperscalers.

What the f*ck... 🤯 Cloudflare just open-sourced an entire AI coding platform that lets anyone build and deploy apps with natural language. VibeSDK is basically Replit/Cursor but you can deploy your own version in one click. Here's how it works:

I am currently researching Ray Kurzweil's biography for a longer article in my newsletter. And the more I read about Kurzweil, the more I am convinced that the faster we achieve ASI, the faster we move towards singularity, the better it will be for humanity. Instead of over-regulating AI and slowing it down, we should accelerate it even more, invest even more capital in data centres, and allocate even more resources to its development.

New @AIatMeta paper explains when a smaller, curated dataset beats using everything. Standard training wastes effort because many examples are redundant or wrong. They formalize a label generator, a pruning oracle, and a learner. From this, they derive exact error laws and sharp regime switches. With a strong generator and plenty of data, keeping hard examples works best. With a weak generator or small data, keeping easy examples or keeping more helps. They analyze 2 modes, label agnostic by features and label aware that first filters wrong labels. ImageNet and LLM math results match the theory, and pruning also prevents collapse in self training. ---- Paper – arxiv. org/abs/2511.03492 Paper Title: "Why Less is More (Sometimes): A Theory of Data Curation"

'The four lead banks have enlisted other banks and will now sell the debt to additional banks and institutional investors through a retail syndication process, with commitments expected by late November'

As many have already shared some great slides, I finally went through the full report. Fantastic work by @LBNL @TheBrattleGroup teams! Factors Influencing Recent Trends in Retail Electricity Prices in the United States 🧵. Read if you want to know what's going on with US electricity prices in a non-fear mongering or engagement bait way! Largest drivers of price increases - replacement & hardening of aging T&D, price movement of nat gas, extreme weather, state RPS

I’m also writing a science fiction novel with the Kimi K2 Thinking model, chapter by chapter. As a big sci-fi fan, I’d rate its creativity and prose at least four out of five stars! Great job, @Kimi_Moonshot!

If judged based on consumer adoption, AI chatbots are the most popular technology ever. If judged based on poll numbers, they are the least popular. How to explain this? A big part of it is the Doomer Industrial Complex — hundreds of astroturfed organizations that have spread doomer narratives about AI. Writer Nirit Weiss-Blatt (@DrTechlash) has analyzed this ecosystem and traced its funding to just a few Effective Altruism billionaires. Namely Dustin Moskovitz, Jaan Tallinn, Vitalik Buterin, and Sam Bankman-Fried (yes, the convicted felon). Collectively they have donated over a billion dollars to the cause of catastrophizing AI. Those repeating the memes should understand the source. Full article: aipanic.news/p/the-ai-existe…