Aman

how life with cursor tab felt

Over the past 2 weeks, we’ve onboarded a few thousand businesses and developers from our waitlist per capacity to try Ultramarine 1 Flash. We were thrilled to see the variety of use cases and grateful for rich feedback to support future generations of the model. We’re excited to share that we’re releasing the weights and launching the model with early partners, including @FireworksAI_HQ and @baseten, to broaden access.

Cloud coding agents are a surprisingly hard infra problem, and it’s been awesome working with @mlejva and team to deliver fast, reliable coding agents in niteshift.dev on @e2b!

We are releasing Ultramarine 1 Flash, a frontier-class model built for knowledge work. It is open-source and achieves similar performance to Fable 5, while being 60x cheaper. It was post-trained by a team of 5 for ~$300k all-in. Available on API now, with weights releasing in 2 weeks.

Introducing Decision-Bench, a new industry standard for measuring model capabilities in making ROI-positive decisions on messy enterprise data. Every enterprise has slowed AI investments due to no ROI; AIs still fail at complex decisions, and pricing second order effects.

Today we're announcing that Modal has crossed $1B in annualized run rate, as well as raised a $750M Series D at a $15.75B valuation, led by @Accel. Since our Series C, usage has tripled and we’ve grown more than 15x year-over-year. We are deeply grateful to the developers and companies building on Modal. There's still so much more to build, and we can't think of a better time to be building software.

Proximal builds infrastructure that enables AI to improve from real-world experience. In the past year, we have grown to more than $200M in annualized revenue helping frontier labs and enterprises improve coding agents. Now, we are expanding beyond software engineering. Recent progress in mathematics demonstrates what happens when models are trained in domains with massive amounts of public data and easy verifiability, making it easy to find weaknesses, generate training tasks, and iterate quickly. We build infrastructure that enables this feedback loop in other domains: we are excited about a world in which AI systems design targeted drugs, accelerate chip design, and rewrite legacy software that still runs hospitals, power grids, governments, and other critical infrastructure. Since starting, we have assembled a small team of researchers and engineers and built world-class infrastructure for post-training and synthetic data research to overcome the challenges of scaling manual data curation. Our team comes from Cursor, Google DeepMind, Meta Superintelligence, Prime Intellect, Citadel, and Jane Street. More than half are former founders. We’re fortunate to be backed by investors who share that vision, including @generalcatalyst who led our $15M Seed Round at a $300M valuation, as well as @chemistry, @svangel, @dvlamoen and individuals like @LiamFedus, @kevinweil, and @bernhardsson

Agents are using legacy Python packages to edit Word, Excel, and PowerPoint files, hitting API gaps, dropping into raw OOXML, and creating silent corruptions. We fix that today with OSS Paper Office:

GPT-Live-1 is now available in the API. Bring ChatGPT’s natural back-and-forth to your app, with voice agents that listen while they speak and work with the models and harness you choose.