Transforming chip development requires not only the best researchers, but also the dedicated compute and unwavering focus that pushing the boundaries of AI demands. That's why we started Ricursive. Grateful to be featured in @Bloomberg by @byJuliaLove alongside other daring founders.
https://t.co/dvMF2wGs7e
Chips are the fuel for AI. By using AI to design, optimize, and automate chip design, we can close the recursive self-improving loop between AI and its physical substrate.
Our co-founders @annadgoldie and @Azaliamirh took the stage at @sequoia AI Ascent 2026 to share more about Ricursive’s vision to accelerate and democratize chip design.
Proud of the progress our world-class team has already made. And we’re just getting started!
Ricursive has raised Series A! @annadgoldie and I had the chance to discuss our vision and the latest fundraise with @CadeMetz at @nytimes.
https://t.co/OdyblsVJDl
We are so grateful to our investors for their support as we build toward our vision of recursive self-improvement via AI for Chip Design and Chip Design for AI.
Thrilled to announce our $300M Series A at a $4B valuation!
Chips are the fuel for AI. At Ricursive Intelligence, we are using AI to design better chips faster, closing the recursive self-improving loop between AI and hardware.
Exclusive: AI startup Ricursive, founded by former Google researchers, wants to remake the $800 billion chip industry and it raised $35 million with backing from Sequoia https://t.co/q4EGYyiGyh
Excited to announce that @Azaliamirh and I are launching @RicursiveAI, a frontier AI lab creating a recursive self-improving loop between AI and the hardware that fuels it.
Today, chip design takes 2-3 years and requires thousands of human experts. We will reduce that to weeks.
This will be incredibly hard.
For context: Go has a search space of 10^360. A simplified version of chip placement—only one part of the design process—has a search space of 10^9000.
But we are the right team to solve it.
We co-founded the Machine Learning for Systems team at Google Brain. There, we built AlphaChip—an RL agent for chip placement. AlphaChip has been used to design four generations of TPUs, data center CPUs, autonomous vehicle chips, and mobile phone chips. These chips are running in data centers and devices all over the world.
Our immediate goal is to dramatically accelerate chip design.
Next, we plan to design chips end-to-end given an ML workload, unlocking a Cambrian explosion of custom silicon.
Finally, we will close the recursive loop. We will build our own chips, train our own models, and co-evolve them on the path to superintelligence.
AI designs better chips 🔄chips train better AI
We sat down with @WSJ’s @Berber_Jin1 to discuss Ricursive: https://t.co/DZ17BuecQt
Thrilled to share that @annadgoldie and I are launching @RicursiveAI, a frontier lab enabling recursive self-improvement through AIs that design their own chips.
Our vision for transforming chip design began with AlphaChip, an AI for layout optimization used to design four generations of TPUs, data center CPUs, and smartphones. AlphaChip offered a glimpse into a future where AI designs the silicon that fuels it. Ricursive extends this vision to the entire chip stack, building AI that architects, verifies, and implements silicon, enabling models and chips to co-evolve in a tight loop.
We sat down with WSJ’s @berber_jin1 to discuss Ricursive: https://t.co/oCdLmbB06X
Introducing Ricursive Intelligence, a frontier AI lab enabling a recursive self-improvement loop between AI and the chips that fuel it.
Learn more at https://t.co/cSpbrQwwEn