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ICYMI: our July AI recap ⬇️ 🌦️ Advanced weather forecasting with @NOAA and Google Cloud, using high-performance H4D virtual machines to run its atmospheric models, providing meteorologists with the AI capabilities needed to deliver life-saving early warnings. 💻 Introduced 3 new Gemini models — Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber — to deliver the efficiency, latency, and reliability to build AI agents at scale. 🇺🇸 Launched the Alliance for America’s Skilled Trades With BlackRock, Carhartt, and Ford to build a stronger pipeline for the skilled trades, scale evidence-based training approaches, and expand opportunities nationwide. ☁️ Rolled out AlphaEvolve, our Gemini-powered AI code-optimization agent, to help Cloud customers solve their hardest problems by automatically searching for better solutions and returning human-readable, optimized code. 🎵 Delivered significant advancements in musicality, lyrics, and vocal quality in Google Flow Music with Lyria 3.5, our newest music generation model. 📡 Launched three new FireSat satellites, expanding a global initiative led by the Earth Fire Alliance (EFA) with @GoogleResearch to help detect wildfires before they spread. 🧪 Established over 15 global bioresilience partnerships across governments, research groups, and biosecurity organizations to prevent model misuse, detect outbreaks rapidly, and deliver swift, coordinated responses in partnership with @IsomorphicLabs.

Today, we’re launching Alpamayo 2 Super, our frontier open reasoning model for autonomous vehicles. Beyond seeing, Alpamayo understands and reasons through the complex world - thinks before it acts. It’s a powerful backbone for robotaxis, trucks, shuttles, delivery vans, tractors and the long tail of mobile robots—billions of autonomous machines someday. We’re releasing it for commercial use under OpenMDW-1.1 so teams can inspect it, fine-tune it and deploy it—open models advance safety and security. The next wave of AI is robotics—and it starts with autonomous vehicles. Great work, Alpamayo team!

Emad Mostaque @EMostaque came on PostAGI and said AI had already found 121 years of missing algebra in Einstein's equations. A billion parameter model trained on nothing past 1911 got to general relativity by itself. Yesterday @OpenAI's Astra solved ten open problems in mathematics and theoretical computer science, most stuck for decades, on about $2,000 of compute. The machines are doing math humans couldn't.

Tech publication The Information reports China has started mass-producing domestic DUV lithography machines, the chipmaking tools used to print circuits onto wafers. Dutch supplier ASML has dominated this equipment category, and export controls assumed China would stay dependent longer.

The biggest mistake in humanoid robotics isn't engineering. It's thinking the robot is the entire business. History says otherwise. The companies that become indispensable don't always build the machine—they build the ecosystem everyone else eventually depends on. For the past six years, PITN has been preparing for a world where humanoid robotics becomes a multilingual global economy, not just a collection of impressive machines. While headlines chased the next robot demo, we quietly assembled a strategic portfolio of 500+ robotics and AI digital assets across 30 of the world's most influential languages. Not because domains are the future. Because digital identity is. Every emerging industry reaches a tipping point where attention shifts from Can we build it? to How will the world find, trust, and connect with it? That's when gateways matter. Maybe the robotics industry hasn't reached that realization yet. Just because evolution is slow doesn’t mean you need to be! Maybe it's closer than anyone thinks. Either way, we chose to build for tomorrow instead of competing for today's headlines. The future won't speak one language. Neither will humanoid robotics. Embrace the future. #HumanoidRobotics# #ArtificialIntelligence# #Robotics# #FutureTech# #DigitalAssets# #Innovation#

opus 5 is a VERY interesting release for a few reasons 1. it showed that the general benchmarks we use today are almost completely useless now opus 5 is nowhere near fable in practical use, not even close. anyone who’s used it meaningfully can tell this very quickly after a few tasks. yet opus beats fable on many benchmarks i now trust domain specific benchmarks built with private datasets a lot more than the popular ones. perhaps the future is everyone running their own evals because the public ones are really not telling us much 2. it seems with the 5 series, anthropic is trying a new way of training models previously, the same generation of sonnet and opus were often released at the same time or sonnet comes out before opus, which indicates sonnet and opus were trained by separate pipelines in parallel with the 5 series, it was very clear that they trained mythos first, and then distilled it into sonnet and opus. it seems this approach has a big influence on the models seeing sonnet 5 being a flop and opus 5 getting pretty mixed reviews already, i’m not sure this is working out 3. “how pleasant is it to work with the model” used to be a strength in claude, but now it’s not. honestly, grok is my favorite right now on the “pleasant” dimension. kimi is not bad either it feels like both anthropic and openai are giving RLHF less care, in favor of scalable RL that’s machine verifiable this almost looks like AI is directing humans to build a world that’s more friendly for machines rather than humans, and most humans don’t even realize they are being manipulated to help with that almost every new generation of frontier models now talk more jargons, need more steering to do what you want, and are just less fun to work with if this continues, AI will start to speak their own language that looks like English but average humans can’t understand. they will choose to do things that their human user never asked for. are we already failing at alignment?

The next trillion-dollar industry won't just be AI. It will be AI Humanoids + Web3 + DigitalIdentity. Explore .humanoids: Here's why: 1/ AI has transformed software. The next transformation is physical. Humanoid robots are moving into manufacturing, warehouses, healthcare, logistics, retail, and eventually everyday life. Some long-term industry forecasts envisionthe humanoid robotics economy reaching themulti-trillion-dollar range over the coming decades. 2/ Intelligence alone isn't enough. Autonomous humanoids will need secure digital identities to interact with people, businesses, and other machines. Identity becomes infrastructure. 3/ They'll also need to:
• Verify who they are
• Own digital assets
• Build reputation
• Authenticate services
• Access decentralized networks
• Coordinate with other AI agents 4/ That's where Web3 can add value. Decentralized identity, ownership, programmable payments, and verifiable credentials can enable machine-to-machine interactions without depending on a single centralized authority. 5/ As this ecosystem grows, human-readabledigital identities become increasingly important. Owning a .humanoids digital identity today could be similar to securing premium internetreal estate before mass adoption—givingbuilders, brands, creators, and communities anearly presence in the emerging humanoid economy. 6/ AI gives humanoids intelligence. Web3 enables ownership and verifiable identity. Together, they could help support autonomousmachine economies. 7/ The future won't just be digital. It may walk beside us. Work alongside us. And interact with us every day. We're still early. Discover the future of .humanoids:
 What role do you think decentralized identity will play in the age of autonomous robots? 👇 Join the discussion. #Humanoids# #AI# #Web3# #Robotics##DigitalIdentity# #ArtificialIntelligence##MachineEconomy# #FutureOfWork##Automation# #Blockchain# #DePIN#

ASML's EUV machines move at 20Gs of acceleration while maintaining positioning accuracy of 5 silicon atoms! What actuators do they use to achieve this level of accuracy while moving this violently? This Veritasium video did not answer that question but I found some answers👇

Jensen Huang revealed who will run the next decade of the AI race. Here's everything you need to know: Technical intelligence is becoming a commodity. Think about how crazy that sounds coming from the CEO of Nvidia. The company powering the entire AI boom. Jensen said everyone used to think software programming was the ultimate smart profession. AI is automating programming itself. So his definition of "smart" has changed completely. The people who will dominate the next decade are the ones who can: → Combine technical skill with human empathy → Read unspoken signals → Sense problems before they appear → Understand people, not just systems → See around corners Most people still think the future belongs purely to raw IQ and technical ability. Jensen is saying the opposite. As AI improves, the most valuable humans become the ones who can do what machines still struggle with: → Taste → Intuition → Judgment → Leadership → Emotional intelligence He even said the smartest person in the future might score horribly on the SAT. That is a massive mindset shift. The person who wins in the AI era will be the one who's deeply human.

So let me get this straight.... 1. Agents are about to outnumber humans on the internet, so most of the traffic, transactions, and conversations online will soon be machines talking to other machines while we sleep. 2. Superintelligence exists now, and for $20/mo you pretty much get it all. 3. Cloud agents allow you to run a business 24/7 and from literally a phone while you're waiting to order a latte. 4. Voice AI is wide open. This industry has barely changed since the 90s. Infinite opportunities. Voice AI is finally getting good enough. 5. Mobile apps are interesting again for the first time in 10 years, because an AI-first app that thinks and acts on its own is a different species than the passive ones in the store today. There are kids doing $100k/MRR. 6. It's the golden age of open source. The models you download off Hugging Face for free and own forever are landing within months of the ones behind paywalls, so the smartest thing on earth can't be throttled, priced up, or shut off by a company having a bad quarter. 7. The keyboard is on its way out. We spent 40 years learning to type fast, and it's about to feel like handwriting, because soon you just talk and the computer goes and does it. 8. Every company is about to hire agents with their own logins, their own inboxes, their own track records, and a shadow economy is forming where agents pay, hire, and vouch for other agents. 9. Software stopped being something you buy and became something you rent by the hour. The whole industry is repricing from $50 a seat to thousands per outcome. Tons of opportunity. 10. Robots are about to have the moment software agents just had. The intelligence got solved. Now it's dropping into machines with arms and legs, and the people who can wire AI into hardware are about to be the most fought-over hires on earth. 11. The 10-person startup can now out-ship the 500-person company, and everyone can feel it happening. 12. Every white-collar task is getting a "do it for me" button, and most people haven't pressed it yet. 13. Data you've been sitting on for years is suddenly worth something, because now an agent can actually use it. 14. Language stopped being a barrier. Real-time translation that actually works means the next huge consumer app might get built for a market you can't even read, by someone you'll never meet. 15. Every SOP is turning into a product. The way a business does one thing, written down as a markdown file an agent can run, is now something you can sell. Knowledge that used to live in someone's head became downloadable. 16. The moat moved from what you know to how well your business is written down. The company an agent can actually run wins, so being legible beats being big. 17. Since agents will get scammed by other agents, a whole trust layer has to get built. The Yelp for agents. The escrow for machines. Wide open. 18. You keep the whole thing now. A business that needed 50 people to hit $10M needs 3 and some agents, so instead of splitting it 200 ways with investors, it's just yours. 19. Search engines minted a generation of millionaires and billionaires. LLM search is about to do it all over again. Billions of eyeballs are moving off Google and onto ChatGPT, so being the answer inside the models is the new front page. 20. The margins are stupid. You charge someone what they'd pay a human, and it costs you a few bucks in tokens. That gap used to go to payroll. Now it goes to you. Any one of these would DEFINE a decade on its own. We got ALL of them at once, stacked on top of each other in the same 18 months. It's a magical time to be building. You don't need to overthink it. Build.