Runtime speaker lineup is live! We're bringing together experts covering AI infrastructure, applications of AI in science and robotics, the future of software engineering, and more.

Frontier models are simply too expensive and slow for the majority of use cases, so we see models like SWE-2 becoming the daily driver for most. Training trillion-parameter coding agents at scale isn't easy though: typically, each step launches thousands of rollouts, each with its own isolated environment. Cognition uses Modal's sandbox infrastructure for the rollouts behind SWE-2. Congrats on the launch! More on how we scale Sandboxes:

Lots of disdain in the comments. It’s honestly a bit unnerving to read people’s negative reaction to a harmless plea to continue prioritizing sharing discoveries and results, as humanity has done for millennia. Maybe it’s easy to think that the authors are operating from a place of ego and jealousy, if they are Fields medalists, and therefore the general public doesn’t trust them. So let me try explaining as someone who has no career achievements, no stake in the frontier labs, and no jealousy because my peers are all early-career like me 😆 Academics are stewards of history. We have 3 jobs. (1) to train people / teach them what has been done in the past. (2) we make some discoveries ourselves, and (3) we regularly interact with our peers to learn about their discoveries; what tomorrow’s history may be. Many people think we just do (2), but in fact all 3 are important; otherwise we would be highly inefficient in problem-solving over the long term (centuries, millennia). We cannot really make AI the stewards of history (there are capitalist and geopolitical incentives not to). If we rid the world of academic values, there may not be immediate consequences, but things will be very bad in the long term. Progress will stall. Eventually folks will realize we need a clear and continually-updating ledger of history (ie “memory” for the AI-pilled folks). It will take a lot of work to rebuild this culture from first principles On the optimistic side I think academics have a golden opportunity to figure out how we can harness AI in pursuit of our values. We can probably keep more information in our history, disseminate info more broadly, review and validate each others’ discoveries faster, etc. But, given that academics are powerless compared to these trillion dollar companies, we can only do the best we can—speak up; discuss; educate the public about academic values (which we haven’t really had to do since ww2); and, honestly, pray

DeepSeek v4.1-Flash, a new multimodal model from @deepseek_ai, is now available on Modal. v4.1-Flash uses DeepSeek's Causal Encoder-Decoder architecture, activating 16B parameters for input and 8B parameters for output to improve cost efficiency for input-heavy agentic workloads.