Post by Proximal

Today, we are announcing Proximal. We are excited about a world in which coding agents can autonomously run for multiple weeks, solve the hardest technical problems and discover novel ideas that advance progress in various domains of science and engineering. We believe that we are not far from this future, but that the biggest bottleneck preventing us from achieving it is training data. Many companies work on training data, but almost all of them are approaching it the wrong way. Historical capability breakthroughs were the result of creative engineers discovering scalable data collection methods in specific domains, rather than thousands of contractors manually writing task demonstrations and graders. Inevitably, the potential impact of human data will become smaller and smaller as model capabilities increase: agents are already outperforming most humans in many domains - the number of experts that are capable of judging model outputs shrinks with every new model release. To name examples: LLMs are making significant progress in GPU Kernel engineering because KernelBench showed us that we can scalably generate kernel optimization problems from scratch. We are seeing breakthroughs in AI for theorem proving because Lean gives us a playground where mathematical proofs can be formally verified without human grading. CodeI/O and Synthetic-1 showed that we can improve models’ abilities to reason about code through synthetic output prediction tasks. These are just a few examples of great ideas - many more were discovered throughout the last few years, and significantly more are yet to be discovered. We believe that the process of discovering and executing on these ideas can be drastically accelerated by a data engine that shares infrastructure, abstractions, and learnings across domains, rather than reinventing the stack from scratch in dozens of isolated efforts. Proximal is a new data company: Our core belief is that data which is complex enough to teach today’s frontier models is not bottlenecked by domain experts, but by great ideas and excellent software. We are not a recruiting firm or a talent marketplace, but a research and engineering organization that treats data as a problem which deserves the same level of rigor as work on training algorithms and model architectures. We think that this is the most impactful work towards agents that can autonomously solve complex technical problems, and intend to share our research and progress in the open. Join Us We are a team of engineers and researchers from companies like Cursor, Prime Intellect and Jane Street - our team members have published papers at leading research conferences, built highly popular open source software and successfully sold their own companies before. We want to work with engineers and researchers that are excited about pushing the frontier of AI capabilities. If you would like to talk, please reach out to [email protected] Full blog: https://lnkd.in/gn3G4B2K