@chaidiscovery scholar @neo, prev HFT, @MaticRobots, @schoolhouse_edu
Joined December 2017
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Jinay retweeted
Tune in to @latentspacepod to hear @Mattmcpartlon1 and @realdealpatil talk about the transformational moment bio AI is going through, and why you don't need a background in biology to make an impact in the space.
Chai Discovery's BioAI Phase Shift: Chai-3, Photoshop for Molecules, One-Shot Drug Design, & Engineering Biology latent.space/p/chai-discover…
@chaidiscovery cofounder @Mattmcpartlon1 and product lead @realdealpatil explain why AI drug design has crossed the threshold from impressive demos to pharma-trusted tools, how Chai-2 and Chai-3 are pushing toward one-shot therapeutic-grade molecules, how Chai’s CAD-like design suite lets scientists precisely engineer antibodies and binding sites, why faster model-to-lab feedback loops could turn pharma’s waterfall discovery process into an iterative loop, and how better models, validation, compute, and infrastructure are turning biology from trial-and-error science into an engineering discipline.
Jinay retweeted
To date, finding a drug has been a process of guess & check… screening millions of molecules hoping one binds.
@chaidiscovery is changing the paradigm… describe the molecule you want, and the model designs it.
@joshim5 and @Mattmcpartlon1 took antibody hit rates from roughly 1 in 1,000 to 1 in 7. That's the jump from search to engineering.
On this episode of Training Data, they get into where the field actually is, why 2024 was the moment to start, what drug discovery looks like when the computer does the design, and more.
00:00 Introduction
01:52 From Discovery to Design
03:25 Protein AI Breakthroughs Timeline
06:04 Why Start in 2024
10:13 Diffusion Models Intuition
11:41 Building the Avengers Team
15:22 Hit Rates and Scaling Laws
25:01 Molecular CAD Vision
25:24 Faster Design Loops
26:32 Future Drug Discovery
28:37 Platform Business Model
31:14 Partnering Reality Check
33:44 Data Flywheel Explained
37:16 Staying Ahead at Scale
39:44 Culture and What's Next
Jinay retweeted
Work that traditionally took weeks or months now takes days, and @jinaycodes says that means researchers can stop deciding on one idea upfront and instead try all of them.
"With these image generation models, you can now generate so many more ideas. It opens up a whole new problem space and ways of thinking about drug design that isn't just about the condensed time period."
"Something that traditionally would take weeks or months, you can now do on the order of days. A lot of times you would just have to decide that beforehand, but now with Chai, you can just try all these things."
"Previously with GPT-2 or 3, you would have these things generating almost like a stream of consciousness of any idea they have. It's not really that useful until you can start asking it questions and having it do exactly what you want. That's what we're trying to do here."
Jinay retweeted
What a week at @chaidiscovery.
In the last 3 days:
- Unveiled our collaboration with @Novartis
- Announced our $400M Series C
- A new agreement with @argenxglobal
We’re delighted to announce our third agreement this week, this time a collaboration with @argenxglobal.
argenx has built one of biotechnology’s most productive antibody engines. We’ll be putting Chai’s frontier molecular design platform into the hands of their scientists.
Jinay retweeted
nature is about to lose several longstanding advantages
Tomorrow's medicines should be designed with the precision and scale of modern engineering.
I'm thrilled that @ChaiDiscovery has raised a $400M Series C at a $3.8B valuation from @IndexVentures @KleinerPerkins @Sequoia @_DimensionCap to accelerate progress towards that goal.
Jinay retweeted
We’ve raised $400M at a $3.8B valuation to further advance AI-driven molecular design. The round was led by @IndexVentures, alongside @KleinerPerkins, @Sequoia, @_DimensionCap, and others.
Jinay retweeted
We’re delighted to announce our collaboration with @Novartis.
Building on a year-long technical engagement, we’re expanding our collaboration with Novartis to support broader deployment of our technology across multiple therapeutic programs.
Novartis will gain access to our latest models for prediction and design, including Chai-3.
Jinay retweeted
Incredibly proud of the Chai team. It's a privilege to wake up every day and go to work on models that are actively used by some of the world’s leading pharma companies, as they go about designing the medicines of the future. There is no higher calling.
I’m delighted to announce @chaidiscovery's collaboration with @pfizer. Their scientists will deploy our AI platform to accelerate drug discovery, including early access to our latest frontier model Chai-3.
You can learn more about this partnership and our momentum in @amyfeldman's feature in @Forbes out today
forbes.com/sites/amyfeldman/…
Jinay retweeted
I’m delighted to announce @chaidiscovery's collaboration with @pfizer. Their scientists will deploy our AI platform to accelerate drug discovery, including early access to our latest frontier model Chai-3.
You can learn more about this partnership and our momentum in @amyfeldman's feature in @Forbes out today
forbes.com/sites/amyfeldman/…
Jinay retweeted
Today we are announcing our collaboration with Pfizer to put Chai's frontier AI—including our latest model, Chai-3—directly into the hands of one of the world's leading pharmaceutical teams.
Jinay retweeted
"We have this long term vision of turning biology from something which is trial and error and experimental and make it something that looks more like an engineering discipline in the next century."
New Episode with @jackdent !
0:00 Intro
02:28 Inside @stripe w/ @patrickc, at <100 People
08:45 @sama role in @chaidiscovery origin
16:20 Chai-2 Antibody Breakthrough
19:24 Approaching biology as an engineering problem
24:45 Using AI models to treat people on an individual scale
26:52 Robotics in labs
27:22 Pharma industry today
29:49 The clinical trial bottleneck
32:53 Personalized biology models & cancer vaccines
36:24 Longevity, peptides, and trillion-dollar drugs
39:02 Does it matter that the government cut exploratory science grants?
41:00 What next-gen Chai models will do
42:08 Can frontier AI labs build this themselves?
43:26 Biology is hard
Jinay retweeted
Visualizing UMich classes in 3d space: kvnshu.github.io/course-mani…
Came across soarxiv.org a while back from @jinaycodes and got inspired to do something similar with the classes offered at my university:
Jinay retweeted
after months of antibody design papers that only work on single chains, we are seeing much-needed progress on full IgG
congrats to the chai team!
Jinay retweeted
Most AI systems today follow the same predictable pattern: they're built for specific tasks and optimized for objectives rather than exploration.
Meanwhile, humans are an open-ended species—driven by curiosity and constantly questioning the unknown. From inventing new musical genres to imagining life beyond our universe, we continuously push the boundaries of what’s possible.
What if AI could be as endlessly creative as humans or even nature itself?
I wrote a blog post diving into the world of open-ended AI, exploring how embracing open-endedness might help us break the limits of today’s AI systems 👇
richardcsuwandi.github.io/bl…
Jinay retweeted
Thinking about how my research ideas evolve over time, so I made this visualization
Interesting that there are both small steps and bigger jumps. What surprised me was that there wasn't a clear overall direction in how the ideas developed
