🦔AI companies are bulk-buying rare books, scanning them through high-speed machines that cut the spines off, and shredding the originals. A service called ISBNdb facilitates orders of up to a million books and keeps buyers anonymous. Pre-2022 books are premium because they're free of AI-generated text. A federal judge ruled the practice is fair use because eliminating the original means only one copy exists at a time. Anthropic hired the former head of Google Books partnerships to obtain "all the books in the world." My Take This got to me. A bookseller told 404 Media that rare books with almost no surviving copies are being fed into this pipeline. Books that survived wars, fires, and centuries of handling are being shredded so an AI can learn to write a better marketing email. ISBNdb's website literally says "'AI company destroys two million books' is not a headline that generates sympathy," and they still built an entire business around making it happen quietly. They offer NDAs as a feature. They coach clients to call it "digital preservation." I've covered AI companies scraping the internet, torrenting libraries, and stealing music. This is worse because it's irreversible. You can re-upload a website. You can reprint a bestseller. You can't replace the last three copies of an 18th-century botanical text once someone shreds them for training data. And the judge said it's legal. So it's going to accelerate. "We shred rare books and offer NDAs so nobody finds out" is a legitimate business model in 2026. What a timeline. Hedgie🤗

Most founder events are built around a stage. [O]pen House is built around access. This autumn, R[3]sidency opens the door to candid zero-to-one conversations, a focused room of builders and the network within reach. Keep your eyes on the door. Opening soon. 🚪

We're losing too many talented & ambitious people in the UK but barely any data tells us why. Introducing the Brain Drain Wall: an interactive microsite built to solve this problem.

Today, we launched GPU compute forward curves derived from our prediction market prices. Forward curves are now available on Nvidia B200. H200, and A100 chips. Forward curves track implied future prices. They are how mature commodity markets form expectations, allocate capital, and manage risk. Energy, interest rates/SOFR, FX, metals, and agricultural markets all rely on market-implied forward prices. Despite becoming one of the key inputs in the global economy, compute has lacked that market-derived infrastructure. Compute right now is where oil was before NYMEX — traded only via OTC deals, just like oil used to trade OTC between producers and refiners. As compute becomes as fundamental to the economy as energy, the industry will need a similar derivative market to promote efficient price discovery. Prediction markets are uniquely suited to this problem. Compute is not one uniform commodity and spans many chips, grades, tenors, locations, and contract structures. A live prediction market can aggregate those dispersed views into transparent prices that reflect market expectations for different maturities. The opportunity is big. Hyperscalers are spending over $700B on compute this year and the market is expected to grow to $7-10T by 2030. If this market behaves like traditional commodity markets, a liquid derivative market could be 10-20x bigger than the underlying spot market. Compute is still not uniform enough, but this is a step towards standardization as forward curves will help us see the rise and fall of different model prices and how they correlate. The forward curve is a first step. Up next: futures and perps.

It's been interesting and puzzling to witness the problems with accuracy in UK economic statistics over the past few years. (See the links in the next tweet for more.) It seems that the Office for National Statistics, ONS, now struggles to effectively measure basic figures such as employment, trade, and inflation. This resulted in a quite scathing government report published last summer, where Robert Devereux, a former permanent secretary, concluded that "most of the well-publicised problems with core economic statistics are the consequence of ONS’s own performance." There's a lot of discussion about the travails facing the UK these days (including this big piece in The Atlantic a few weeks ago[1]), and the problems with the ONS feel like an unsettling microcosm of diffuse decline in broader institutional competence. Anyhow: at Stripe, we became curious about the UK's published entrepreneurship data. While we observe a boom in many parts of the world, official figures don't show a similar increase in the UK. In the latest Stripe Economics post, we dug into the data, and, as far as we can tell, the official figures are probably misleading. The good and the bad news (mostly good, I think!) is that the UK is almost certainly witnessing an unmeasured boom in entrepreneurship: UK-specific issues aside, I suspect that this measurement question is illustrative of forthcoming econometric challenges. Keeping the world's macro indicators up-to-date in response to the faster-than-usual changes wrought by AI will be both increasingly difficult and increasingly important in the coming years. [1]

The best way to understand what's next is to spend time where it's being built. So we headed to Bristol to visit @formacity, where @LataPersson hosted a R[3]sidency workshop. We also sat down with founders to hear what they're building & what they really think about accelerators. Come behind the scenes with us ↓

The UK can once again be the most dynamic country in the world. Today we launch the UK Dynamism Fund, a new philanthropic fund to support the believers and the builders of UK dynamism. Apply now:

The most contrarian bet in tech right now: European talent. Everyone midcurves it. Too regulated, too slow, no upside. Meanwhile Europe remains one of the deepest talent pools in the world, and some of the most asymmetric outcomes I’m seeing are coming out of exactly the place everyone loves to write off. Bottom is in, and most people likely just won’t admit it for another few years.

The next generation of category-defining companies will be built by founders with conviction. Introducing R[3]sidency × Construct. R[3]05 is for standout founders building the Machine Economy across Crypto, Fintech, AI, Robotics and Quantum. Built by Fabric Ventures and @wintermute_t, with @solana and continued support from @coinbase. → $300k investment → 12 weeks in London → Demo Day & investor roadshow in New York We don't fund trends. We fund conviction. Apply →

Kicking off London Tech Week with our annual Fabric Summit. We’re only halfway through the day, but it’s already been packed with conversations on AI, stablecoins, digital assets & the machine economy. Looking forward to sharing the highlights soon.