A CFO recently recommended we read DoorDash’s shareholder letters for a simple articulation of their capital allocation strategy and it’s now obvious to me why: this is such a user friendly way of explaining R&D investment in software and internet companies. Summary/notes: (1/)
We at @CapitalG are honored & proud to back @IsomorphicLabs in this funding round as their world-class team and category-defining AI drug design engine transform the future of medicine.
For decades, even as computing has grown exponentially faster and cheaper, the cost of bringing a single new medicine to market has climbed tremendously. The world's most disciplined and talented scientists have spent full careers chasing single impactful targets to no avail. In short, the complexity of biology has resisted the abstraction and compounding progress that built the rest of the modern technology stack.
Sir @demishassabis, @maxjaderberg, and the team at Isomorphic Labs are ushering in the AI era of drug development and changing this dynamic.
Isomorphic's AI drug design engine (IsoDDE) is a field-defining system pushing the frontier of what is possible in drug design, even for the most difficult and obscure targets. The world's most sophisticated R&D organizations already trust Isomorphic with their hardest challenges because they recognize this structural shift and the unique capabilities of IsoDDE and the Isomorphic team.
I'm grateful to play a small part in what their work will mean for the patients and the billions of lives that stand to be touched by what they build. Onward!
I’ve always believed the No.1 application of AI should be to improve human health.
That work started with AlphaFold, and now at @IsomorphicLabs with the mission to reimagine drug discovery and one day solve all disease!
We are turbocharging that goal with $2.1B in new funding.
Rippling AI was the most successful launch we've ever done. On the heels of this launch, Rippling's revenue is now growing 78% YoY (at ARR over $1 Billion). And this growth rate has now increased, every quarter, for three straight quarters.
Pi is quietly providing for robotics what foundation models did for software: a broadly accessible intelligence layer that allows teams to focus on their actual product and use case. The partner results here speak for themselves. Reach out if you're interested in collaborating!
General-purpose AI models are behind some of the most exciting applications we now can't live without. We envision that an analogous “physical intelligence layer” built with models like π0.6 will similarly spur a new wave of applications for the physical world.
We’ve recently begun working with a handful of companies that have deployed their robots to do real-world, useful things.
https://t.co/udVO9fV0PH
Incredible to see what people are building when they get their hands on @dreamer! So excited for what's to come now that AI agents are universally usable and accessible. Magical work from @dps, @hbarra, @alcor, and team!
We’re thrilled to announce that we have raised $300M at a $5B valuation. The round is led by IVP and CapitalG, both doubling down on their investment in Baseten, and joined by 01A, Altimeter, Battery Ventures, BOND, BoxGroup, Blackbird Ventures, Conviction, Greylock, and NVIDIA.
Read more here: https://t.co/cQi1re3vaW
We discovered an emergent property of VLAs like π0/π0.5/π0.6: as we scale up pre-training, the model learns to align human videos and robot data!
This gives us a simple way to leverage human videos. Once π0.5 knows how to control robots, it can naturally learn from human video.
NEW: AI robotics startup Physical Intelligence has raised $600m at a $5.6 bil valuation, w/ CapitalG leading, per sources.
Earlier this week, Pi released a new RL model that it says can help robots do tasks like fold laundry, pack boxes more quickly
https://t.co/SaSa62lqy3
We at @CapitalG are thrilled to partner with Tuhin, Amir, Philip, Pankaj, and the rest of the Baseten team as part of their $150M Series D!
The ceiling for what a delightful software experience can be has been blown open in the past few years by AI. Users of all software increasingly expect intelligence to be woven into every product they use, all the time. As it becomes increasingly clear that open source and custom models are critical components to building production-grade compound AI systems, it becomes even clearer that inference will be one of the largest market opportunities in all of AI.
In getting to know the Baseten team and the platform they've built, it became obvious to us why customers like Abridge, Clay, WRITER, and others love Baseten: they have built the most robust inference platform today and are building with tremendous foresight for where the world of AI will be tomorrow.
Today, we’re excited to announce our $150M Series D, led by BOND, with Jay Simons joining our Board. We’re also thrilled to welcome Conviction and CapitalG to the round, alongside support from 01 Advisors, IVP, Spark Capital, Greylock Partners, Scribble Ventures, and Premji Invest.
The last eighteen months have been a whirlwind; as the AI application layer has taken off, we've been proud to play a small part supporting world class companies run their production workloads. Thanks to all our customers including Abridge, Bland, Clay, Gamma, Mirage, OpenEvidence, Sourcegraph, WRITER, and Zed Industries.
We’re just getting started. If you’re building the next generation of AI products, we’d love to work with you.
Congrats to @mikedelbalso, @kevinmstumpf, and @TectonAI team who have blazed the trail on production AI & ML since their Uber days! I’m grateful to have worked with & learned from you, and even more fortunate that such a talented team found a home at @CapitalG portco @databricks.
We're excited to share that @TectonAI will soon join Databricks, providing enterprises with fast, reliable, real-time data for deploying AI agents.
Tecton’s technology helps enterprises leverage their mission-critical data to power AI agents for critical use cases.
Bringing Tecton into Databricks will unite the best in online data serving with Databricks’ Agent Bricks, empowering customers to build, deploy and scale AI agents faster and more confidently than ever before.
We're excited to see what you build. https://t.co/xeysUiSxiX
People sometimes say that the 12 most dangerous words in investing are "the 4 most dangerous words in investing are 'this time it's different'" but then I also wonder whether the 20 most dangerous words in investing are "the 12 most dangerous words in investing are "the 4 most dangerous words in investing are 'this time it's different'"".
How will AI impact credentialed professions like medicine and law? One interesting framework comes from Paul Starr’s “The Social Transformation of American Medicine”.
Social authority is what we normally think of as authority, i.e. you and others do what the Dr says to do given their expertise.
Cultural authority, which is equally if not more important, is the idea that only the Dr can interpret your situation & diagnose your condition.
Cultural authority in this sense likely began eroding long ago with the advent of web search (see: WebMD) but is likely to fall off a cliff now given how difficult it is to navigate the American healthcare system and how easy it is to get a cogent, engaged, and reasonably accurate diagnostic response from AI. Social authority, on the other hand, is unlikely to erode nearly as quickly due to systemic, regulatory, and societal reinforcement (i.e. legal liability and authority for billing unlikely to shift away from Dr’s anytime soon given all that is at stake).
So what could US healthcare (or law) look like in a world of lower cultural authority but equal social authority? Is it a continuation on the path of shrinking the role of generalists and even more volume to specialists? What does a largely confirmatory medical workflow (like in Radiology) look like across specialties? Fun frames to think about when evaluating new products & companies serving professional end markets.
Announcing the newest releases from Meta FAIR. We’re releasing new groundbreaking models, benchmarks, and datasets that will transform the way researchers approach molecular property prediction, language processing, and neuroscience.
1️⃣ Open Molecules 2025 (OMol25): A dataset for molecular discovery with simulations of large atomic systems.
2️⃣ Universal Model for Atoms: A machine learning interatomic potential for modeling atom interactions across a wide range of materials and molecules.
3️⃣ Adjoint Sampling: A scalable algorithm for training generative models based on scalar rewards.
4️⃣ FAIR and the Rothschild Foundation Hospital partnered on a large-scale study that reveals striking parallels between language development in humans and LLMs.
Read more ➡️ https://t.co/4kggBhnRKu
McDermott’s ability to storytell & sell are jumping off the page here for $NOW, along with a solid print. The whole call has nice nuggets on layering in AI & navigating macro, but not sure how instructive that is for the rest of the sw universe given their “privileged position.”
Ryan Coogler, the director of Black Panther and Creed, breaks down each film format and the many ways you can see Sinners on the big screen. Sinners, shot on KODAK 65mm film is only in theaters April 18. #SinnersMovie