Data for the Real World Diana & Austin Tindle AI has become superhuman at code, language, and images because it has enormous amounts of data to learn from. But our understanding of the physical world is still limited by sparse sensors and models built largely on intuition. Cheaper sensors... and better foundation models could unlock entirely new datasets for energy, agriculture, logistics, construction, and the climate. Once you can accurately model the physical world, you can begin to control it.show more

The Best Time to Build in Crypto @nemild Crypto is in a bear market, but the underlying technology is becoming more useful than ever. Stablecoins are spreading across financial institutions, tokenized assets are reshaping trading, fintech companies are quietly building on crypto rails, and AI agents may rely on them to transact. The hype may be down, but the opportunity to build is not.

New Operating Systems for the Physical World @charliewarren Most of the global workforce does not sit at a desk, but the software used to manage physical work has barely changed in decades. The next operating systems will coordinate humans, robots, and AI agents together. The companies that build them could manage far more than software workflows. They could manage the labor itself.

AI for the Aging Population @maxkolysh By 2030, one in five Americans will be over 65, and there are nowhere near enough caregivers to support them. AI could help older adults live safely and independently through better voice interfaces, monitoring, robotics, and tools for family caregivers. It is one of the world’s largest and most underserved markets, and it is growing every day.

AI-Powered Consumer Products for a Billion People @raphaelschaad Every major platform shift creates new consumer giants. But three years into the AI era, ChatGPT is still the only new icon on most people’s home screens. As intelligence gets better and dramatically cheaper, nearly every consumer category opens up again: education, health, finance, entertainment, transportation, and how we connect with each other. Consumer is going to be so back.

Compute at Sea @FrancoisChauba1 AI is running out of compute, and data centers are running out of electricity and land. One possible solution is to move compute offshore. The ocean offers abundant space, sunlight, and natural cooling, opening the door to fleets of modular data centers operating together as a global cloud.

Multiplayer AI @aaron_epstein The best work tools became more powerful when they became multiplayer. But AI is still mostly trapped in private chats, with agents working in sessions that teammates can’t join or influence. The next generation of AI tools will let teams work with agents together in real time: watching, redirecting, and handing off work across engineering, sales, support, legal, finance, and more. AI’s multiplayer moment is coming.

A Cloud for Small Software @koomen Agents make it easy to build personal tools for yourself or your team. But deploying, securing, and sharing that software is still far more complicated than creating it. A cloud built for small software could remove that complexity and make bespoke tools as easy to share with a colleague as a Google Doc.

The Future of American Defense @SecArmy Warfare is at an inflection point, and the Army is replacing the old playbook with commercially developed, modular technology that can be deployed and improved quickly. We're looking for founders building low-cost interceptors, next-generation sensors, drones, resilient logistics, advanced manufacturing, and hardware that can survive the world’s harshest environments.

The Primer @amiklas The best education has always come from one-on-one tutoring, but that privilege has historically been reserved for very few people. AI could give every child a patient, adaptive tutor that grows with them over the years, beginning with reading, writing, and arithmetic, and eventually helping them learn to think and reason. For the first time, Neal Stephenson’s Primer is starting to feel possible.

AI is moving into the physical world. We're excited about a new wave of startups rebuilding the systems that power the real world, from education and healthcare to defense, finance, infrastructure, and work itself.

Proving You’re Human @maxkolysh A finance worker recently wired $25 million after joining a video call with his CFO and colleagues. Every other person on the call was a deepfake. As voice and video become easier to fake, the internet needs a new trust layer: a private, reliable way to verify that there is a real human behind a call, message, review, or transaction.

AI-Native Compliance Infrastructure @DaivikGoel Financial compliance still runs on spreadsheets, disconnected software, and growing teams of specialists. As companies expand into new markets, the cost and complexity of staying compliant can grow faster than the business itself. AI could monitor regulatory changes, flag anomalies, generate reports, and maintain audit trails in real time. The opportunity is not just to automate compliance work, but to rebuild the entire compliance stack around AI.

Self-Maintaining APIs @GaddipatiHarsha APIs change constantly, but the way providers communicate those changes is still broken. Breaking updates go unnoticed, new features get buried in changelogs, and customers often find out only after something stops working. Coding agents make a better model possible. Instead of announcing a change, an API provider could find every affected use in a customer’s codebase and open the pull request itself.

If you’re interested in working on any of these ideas, you should apply to YC. The deadline for applying to the Fall batch is July 27th at 8pm PT:

@sdianahu @_austintindle Building exactly this. Nearly all video in the training corpus was shot by humans at human height. Ground-level locomotion data barely exists. We put sensors on dogs and horses to collect it. 12 petpin units deployed with K9 handlers and working horses now.

This is exactly where @OVRtheReality becomes extremely relevant. AI needs real-world data — and OVER is building a machine-readable 3D map of the physical world through city-scale mapping, VPS, Gaussian Splats and spatial data. But the most powerful part is the connection with OVRLands: geolocated NFTs @AdamWeitsman that create an ownership layer over real-world coordinates. Once the world is mapped, those locations can become programmable spaces for AR experiences, digital art, NFT galleries, quests, brand activations, tourism, education and future smart-glasses interactions. Data maps the world. OVRLands create the ownership layer. AR brings it to life. 🌍🚀

@sdianahu @_austintindle @GEODNET @mikeahorton the best one

@sdianahu @_austintindle The main gap is see is in the workflow data. Code, text, images, that's all public and everywhere. But the messy internal steps your team actually takes to close a ticket or ship a fix? That stuff lives in nobody's dataset, so agents have no way to learn it.

@sdianahu @_austintindle Isn't this already happening everywhere else?