AI 2027

Summary

Late 2025: The World’s Most Expensive AIOpenBrain is building the biggest datacenters the world has ever seen.(To avoid singling out any one existing company, we’re going to describe a fictional artificial general intelligence company, which we’ll call OpenBrain. We imagine the others to be 3–9 months behind OpenBrain.)Agent-1 (3 x 10^27 FLOPS)ai-2027.comGPT-4 required 2⋅10252\cdot 10^{25}2⋅1025 FLOP of compute to train. OpenBrain’s latest public model—Agent-0—was trained with 102710^{27}1027 FLOP. Once the new datacenters are up and running, they’ll be able to train a model with 102810^{28}1028 FLOP—a thousand times more than GPT-4. Other companies pour money into their own giant datacenters, hoping to keep pace.Although models are improving on a wide range of skills, one stands out: OpenBrain focuses on AIs that can speed up AI research. They want to win the twin arms races against China (whose leading company we’ll call “DeepCent”) and their US competitors. The more of their research and development (R&D) cycle they can automate, the faster they can go. So when OpenBrain finishes training Agent-1, a new model under internal development, it’s good at many things but great at helping with AI research. By this point “finishes training” is a bit of a misnomer; models are frequently updated to newer versions trained on additional data or partially re-trained to patch some weaknesses.The same training environments that teach Agent-1 to autonomously code and web-browse also make it a good hacker. Moreover, it could offer substantial help to terrorists designing bioweapons, thanks to its PhD-level knowledge of every field and ability to browse the web. OpenBrain reassures the government that the model has been “aligned” so that it will refuse to comply with malicious requests.Modern AI systems are gigantic artificial neural networks. Early in training, an AI won’t have “goals” so much as “reflexes”: If it sees “Pleased to meet”, it outputs “ you”. By the time it has been...