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Frontier drug discovery programs require frontier capabilities. Today, we’re excited to share that BMS will be using Chai’s models to support the discovery of new therapeutics. Since rolling out Chai-3 to partners at the start of this year, we’ve partnered with Eli Lilly and Company, Novartis, Pfizer Inc., argenx,...

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Joshua Meier

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80,140 görüntüleme • 1 ay önce •via X (Twitter)

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2025 = breakthrough research in AI for drug discovery; 2026 = the year of deployment at scale. Today we share that @ChaiDiscovery is partnering with Eli Lilly and Company to accelerate biologics discovery.
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2025 = breakthrough research in AI for drug discovery; 2026 = the year of deployment at scale. Today we share that @ChaiDiscovery is partnering with Eli Lilly and Company to accelerate biologics discovery.

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Excited to announce our partnership with dsm-firmenich to bring Boltz's latest AI models to the discovery and design of new scent and flavor molecules! 🧪
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Excited to announce our partnership with dsm-firmenich to bring Boltz's latest AI models to the discovery and design of new scent and flavor molecules! 🧪

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Scientific breakthroughs demand infrastructure that performs at the highest level. From Frontier, the world’s fastest supercomputer, to LUMI and Discovery, AMD and HPE bring supercomputing design and high-performance compute together to help researchers push boundaries in climate science, drug discovery, fusion energy, and AI. See how the most trusted companies trust AMD:
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Scientific breakthroughs demand infrastructure that performs at the highest level. From Frontier, the world’s fastest supercomputer, to LUMI and Discovery, AMD and HPE bring supercomputing design and high-performance compute together to help researchers push boundaries in climate science, drug discovery, fusion energy, and AI. See how the most trusted companies trust AMD:

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We’re proud to share that Tamarind Bio has been selected to build, host, and operate the inference infrastructure layer for TuneLab2.0, the next evolution of the platform. Eli Lilly and Company TuneLab is a first-of-its-kind, collaborative AI/ML drug discovery platform, bringing models trained on over $1B worth of Lilly proprietary data to the biotech ecosystem. Tamarind will power TuneLab’s scalable drug discovery workflows and model inference.
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We’re proud to share that Tamarind Bio has been selected to build, host, and operate the inference infrastructure layer for TuneLab2.0, the next evolution of the platform. Eli Lilly and Company TuneLab is a first-of-its-kind, collaborative AI/ML drug discovery platform, bringing models trained on over $1B worth of Lilly proprietary data to the biotech ecosystem. Tamarind will power TuneLab’s scalable drug discovery workflows and model inference.

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We've been defining the actual frontier of AI for science: - created the most powerful agents and generative models of our biomolecular world - coupled with the most accurate models of state - proved again and again ability to break novel ground in drug design >>> now I'm looking for those who want to push frontier LLMs even further, in an environment where you see the impact on real science the next day 1/2
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We've been defining the actual frontier of AI for science: - created the most powerful agents and generative models of our biomolecular world - coupled with the most accurate models of state - proved again and again ability to break novel ground in drug design >>> now I'm looking for those who want to push frontier LLMs even further, in an environment where you see the impact on real science the next day 1/2

Max Jaderberg

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Join us in the run-up to the release of our music program per day, which we'll share today at 15:00. But first, let us extend our discovery. We’re adding nine new names to our program. From new and exciting, to experienced and brilliant, check it out now, with more to come.
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Join us in the run-up to the release of our music program per day, which we'll share today at 15:00. But first, let us extend our discovery. We’re adding nine new names to our program. From new and exciting, to experienced and brilliant, check it out now, with more to come.

Best Kept Secret

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Today we're dropping the "beta" tag from Adaptyv, launching our new website and announcing our $8M seed round. When we started Adaptyv a few years ago, our core belief was: AI models for biology are only as good as the experimental data they're trained on and the hypotheses they can test in the real world. Now, after a year of working with many great partners, we’ve scaled our infrastructure to the point that we're now open to anyone who wants to use our platform! Overall, this year, over 30 companies started using Adaptyv to validate their protein designs - from some of the biggest pharmas to frontier AI labs to many, many techbio startups. We've run hundreds of experiments, tested well over 10,000 proteins this year and are generating the data that validates the best AI models currently in development.
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Today we're dropping the "beta" tag from Adaptyv, launching our new website and announcing our $8M seed round. When we started Adaptyv a few years ago, our core belief was: AI models for biology are only as good as the experimental data they're trained on and the hypotheses they can test in the real world. Now, after a year of working with many great partners, we’ve scaled our infrastructure to the point that we're now open to anyone who wants to use our platform! Overall, this year, over 30 companies started using Adaptyv to validate their protein designs - from some of the biggest pharmas to frontier AI labs to many, many techbio startups. We've run hundreds of experiments, tested well over 10,000 proteins this year and are generating the data that validates the best AI models currently in development.

Adaptyv Bio

11,636 görüntüleme • 1 yıl önce

The future of drug discovery is here. Formation Bio is joining our Billion Cell Atlas program to help redefine what’s possible in AI-driven drug development, advancing the next generation of therapeutics. By addressing key bottlenecks across the drug discovery continuum, the Atlas can help accelerate the journey from biological insights to approved drugs — bringing greater precision to how we understand what works, why it works, and which patient populations are most likely to benefit. Together, we’re helping bring more precision medicines to life and reimagine what’s possible in biology. Discover the next era:
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The future of drug discovery is here. Formation Bio is joining our Billion Cell Atlas program to help redefine what’s possible in AI-driven drug development, advancing the next generation of therapeutics. By addressing key bottlenecks across the drug discovery continuum, the Atlas can help accelerate the journey from biological insights to approved drugs — bringing greater precision to how we understand what works, why it works, and which patient populations are most likely to benefit. Together, we’re helping bring more precision medicines to life and reimagine what’s possible in biology. Discover the next era:

Illumina

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Next Frontier: Predictions 📈 Our goal is for MobyScreener to become the home for all types of onchain discovery. We started by reshaping token discovery with MobyScreener and Whale Watch by Moby Now, we’re expanding into Prediction Markets with the launch of Smart Money Feeds natively on This live feed tracks the top traders on Polymarket, showing you exactly what they’re buying and selling in real time. Our algorithm identifies the most profitable bettors onchain and surfaces their trades in a clean, actionable UI. Smart Money Feeds is just the beginning of a new wave of features designed to transform how traders win with Prediction Markets.

Moby

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AI has two modes in drug discovery. Accelerate: moving faster through the existing playbook. Unlock: opening frontiers that weren't possible before. Excited to announce Profluent is partnering with Eli Lilly, the global pharma powerhouse, to unlock breakthrough medicines for patients. It's a big deal beyond the numbers ($2.25B + royalties): we’ll get to use our frontier AI models and foundational datasets to design proteins focused on large gene insertion, a therapeutic moonshot. Proteins govern almost everything in biology. We've built a generalizable AI platform to design all proteins. Onward!
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AI has two modes in drug discovery. Accelerate: moving faster through the existing playbook. Unlock: opening frontiers that weren't possible before. Excited to announce Profluent is partnering with Eli Lilly, the global pharma powerhouse, to unlock breakthrough medicines for patients. It's a big deal beyond the numbers ($2.25B + royalties): we’ll get to use our frontier AI models and foundational datasets to design proteins focused on large gene insertion, a therapeutic moonshot. Proteins govern almost everything in biology. We've built a generalizable AI platform to design all proteins. Onward!

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Today we’re releasing SAIR, the Structurally Augmented IC50 Repository. SAIR is the Largest Open-Sourced Binding Affinity Dataset with Cofolded 3D Structures. It includes more than 5 million protein-ligand structures, generated using our Large Quantitative Models and labeled with binding affinity data. By providing this unprecedented scale of structure-activity data, we aim to enable researchers to train and evaluate new AI models for drug discovery, bridging the historical gap between molecular structures and drug potency prediction. The SAIR dataset was created using the NVIDIA DGX Cloud and is now publicly available on the Google Cloud Platform. Access and build with SAIR today! 📰Read the Press Release: 📥Learn More and Download the Dataset at #DrugDiscovery #LQMs #SAIR #AIforScience #SandboxAQ
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Today we’re releasing SAIR, the Structurally Augmented IC50 Repository. SAIR is the Largest Open-Sourced Binding Affinity Dataset with Cofolded 3D Structures. It includes more than 5 million protein-ligand structures, generated using our Large Quantitative Models and labeled with binding affinity data. By providing this unprecedented scale of structure-activity data, we aim to enable researchers to train and evaluate new AI models for drug discovery, bridging the historical gap between molecular structures and drug potency prediction. The SAIR dataset was created using the NVIDIA DGX Cloud and is now publicly available on the Google Cloud Platform. Access and build with SAIR today! 📰Read the Press Release: 📥Learn More and Download the Dataset at #DrugDiscovery #LQMs #SAIR #AIforScience #SandboxAQ

SandboxAQ

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1 billion cells. One atlas. Today, Illumina introduces the Billion Cell Atlas, creating the most comprehensive map of human disease biology — and unlocking unparalleled speed and scale in AI for drug discovery. The Atlas will help researchers, including founding participants AstraZeneca, Merck, and Eli Lilly and Company study the effect of switching on and off all 20,000 genes in cells linked to diseases that have been historically difficult to decode. Learn how the Atlas will elucidate the biological pathways behind some of the world’s most devastating diseases: #JPM2026
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1 billion cells. One atlas. Today, Illumina introduces the Billion Cell Atlas, creating the most comprehensive map of human disease biology — and unlocking unparalleled speed and scale in AI for drug discovery. The Atlas will help researchers, including founding participants AstraZeneca, Merck, and Eli Lilly and Company study the effect of switching on and off all 20,000 genes in cells linked to diseases that have been historically difficult to decode. Learn how the Atlas will elucidate the biological pathways behind some of the world’s most devastating diseases: #JPM2026

Illumina

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Today Amazon Web Services is pushing the frontier of agent development with the launch of Strands Labs—a new GitHub org for experimental agentic AI projects. Push the frontier of agentic development and get started with one of three agent development projects in our new Git organization ➡️ Excited to see what you'll build with Strands Labs.
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Today Amazon Web Services is pushing the frontier of agent development with the launch of Strands Labs—a new GitHub org for experimental agentic AI projects. Push the frontier of agentic development and get started with one of three agent development projects in our new Git organization ➡️ Excited to see what you'll build with Strands Labs.

Swami Sivasubramanian

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Wintermute is officially on the ground in the US With 2,500 counterparties globally, we're already one of the biggest players in the US market Now we’re excited to share that we’ve opened a New York office and brought on Ron Hammond as Head of Policy and Advocacy
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Wintermute is officially on the ground in the US With 2,500 counterparties globally, we're already one of the biggest players in the US market Now we’re excited to share that we’ve opened a New York office and brought on Ron Hammond as Head of Policy and Advocacy

Wintermute

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We are rolling out access to Runway Aleph, our new in-context video model, setting a new frontier for multi-task visual generation. Aleph has the ability to perform a wide range of edits and generations on existing videos. Here are a few of the things Aleph is capable of doing. (1/7)
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We are rolling out access to Runway Aleph, our new in-context video model, setting a new frontier for multi-task visual generation. Aleph has the ability to perform a wide range of edits and generations on existing videos. Here are a few of the things Aleph is capable of doing. (1/7)

Runway

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Today we’re launching a new homepage at that showcases the evolution of our product. Learn more about Artifact’s AI-powered feed and how it keeps you up-to-date with the information and inspiration that matters most to you.
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Today we’re launching a new homepage at that showcases the evolution of our product. Learn more about Artifact’s AI-powered feed and how it keeps you up-to-date with the information and inspiration that matters most to you.

ARTIFACT

150,248 görüntüleme • 2 yıl önce

We’re excited to introduce ShinkaEvolve: An open-source framework that evolves programs for scientific discovery with unprecedented sample-efficiency. Blog: Code: Like AlphaEvolve and its variants, our framework leverages LLMs to find state-of-the-art solutions to complex problems, but using orders of magnitude fewer resources! Many evolutionary AI systems are powerful but act like brute-force engines, burning thousands of samples to find good solutions. This makes discovery slow and expensive. We took inspiration from the efficiency of nature. ‘Shinka’ (進化) is Japanese for evolution, and we designed our system to be just as resourceful. On the classic circle packing optimization problem, ShinkaEvolve discovered a new state-of-the-art solution using only 150 samples. This is a big leap in efficiency compared to previous methods that required thousands of evaluations. We applied ShinkaEvolve to a diverse set of hard problems with real-world applications: 1/ AIME Math Reasoning: It evolved sophisticated agentic scaffolds that significantly outperform strong baselines, discovering an entire Pareto frontier of solutions trading performance for efficiency. 2/ Competitive Programming: On ALE-Bench (a benchmark for NP-Hard optimization problems), ShinkaEvolve took the best existing agent's solutions and improved them, turning a 5th place solution on one task into a 2nd place leaderboard rank in a competitive programming competition. 3/ LLM Training: We even turned ShinkaEvolve inward to improve LLMs themselves. It tackled the open challenge of designing load balancing losses for Mixture-of-Experts (MoE) models. It discovered a novel loss function that leads to better expert specialization and consistently improves model performance and perplexity. ShinkaEvolve achieves its remarkable sample-efficiency through three key innovations that work together: (1) an adaptive parent sampling strategy to balance exploration and exploitation, (2) novelty-based rejection filtering to avoid redundant work, and (3) a bandit-based LLM ensemble that dynamically picks the best model for the job. By making ShinkaEvolve open-source and highly sample-efficient, our goal is to democratize access to advanced, open-ended discovery tools. Our vision for ShinkaEvolve is to be an easy-to-use companion tool to help scientists and engineers with their daily work. We believe that building more efficient, nature-inspired systems is key to unlocking the future of AI-driven scientific research. We are excited to see what the community builds with it! Learn more in our technical report:
0:11

We’re excited to introduce ShinkaEvolve: An open-source framework that evolves programs for scientific discovery with unprecedented sample-efficiency. Blog: Code: Like AlphaEvolve and its variants, our framework leverages LLMs to find state-of-the-art solutions to complex problems, but using orders of magnitude fewer resources! Many evolutionary AI systems are powerful but act like brute-force engines, burning thousands of samples to find good solutions. This makes discovery slow and expensive. We took inspiration from the efficiency of nature. ‘Shinka’ (進化) is Japanese for evolution, and we designed our system to be just as resourceful. On the classic circle packing optimization problem, ShinkaEvolve discovered a new state-of-the-art solution using only 150 samples. This is a big leap in efficiency compared to previous methods that required thousands of evaluations. We applied ShinkaEvolve to a diverse set of hard problems with real-world applications: 1/ AIME Math Reasoning: It evolved sophisticated agentic scaffolds that significantly outperform strong baselines, discovering an entire Pareto frontier of solutions trading performance for efficiency. 2/ Competitive Programming: On ALE-Bench (a benchmark for NP-Hard optimization problems), ShinkaEvolve took the best existing agent's solutions and improved them, turning a 5th place solution on one task into a 2nd place leaderboard rank in a competitive programming competition. 3/ LLM Training: We even turned ShinkaEvolve inward to improve LLMs themselves. It tackled the open challenge of designing load balancing losses for Mixture-of-Experts (MoE) models. It discovered a novel loss function that leads to better expert specialization and consistently improves model performance and perplexity. ShinkaEvolve achieves its remarkable sample-efficiency through three key innovations that work together: (1) an adaptive parent sampling strategy to balance exploration and exploitation, (2) novelty-based rejection filtering to avoid redundant work, and (3) a bandit-based LLM ensemble that dynamically picks the best model for the job. By making ShinkaEvolve open-source and highly sample-efficient, our goal is to democratize access to advanced, open-ended discovery tools. Our vision for ShinkaEvolve is to be an easy-to-use companion tool to help scientists and engineers with their daily work. We believe that building more efficient, nature-inspired systems is key to unlocking the future of AI-driven scientific research. We are excited to see what the community builds with it! Learn more in our technical report:

Sakana AI

360,508 görüntüleme • 1 yıl önce

And now Anthropic’s Claude Mythos will soon be available in select H1 Platform products. We’re making frontier cyber AI models and the creativity and adversarial expertise of our security researcher community available to defenders. Because staying ahead takes both. To reiterate: HackerOne does not use or permit use of confidential researcher submissions or customer vulnerability data to train, fine-tune, or otherwise improve generative AI models. Check out the latest announcement:
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And now Anthropic’s Claude Mythos will soon be available in select H1 Platform products. We’re making frontier cyber AI models and the creativity and adversarial expertise of our security researcher community available to defenders. Because staying ahead takes both. To reiterate: HackerOne does not use or permit use of confidential researcher submissions or customer vulnerability data to train, fine-tune, or otherwise improve generative AI models. Check out the latest announcement:

HackerOne

14,002 görüntüleme • 13 gün önce

🌠Today, we’re excited to relaunch Airtable as the AI-native app platform, combining the magic of vibe coding business apps with real production-readiness and scalability, and embedding them with an army of agents that automate thousands of hours of work in seconds. Instead of just adding more AI capabilities to our existing platform, we treated this as a refounding moment for the company. We started with a clean-slate imagining of the ideal form factor for building apps in the agentic era. (If you want to skip all the backstory and just try it out, you can just go to All new signups get the new AI experience, and existing accounts can switch over using this link: Thread and demos below👇
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🌠Today, we’re excited to relaunch Airtable as the AI-native app platform, combining the magic of vibe coding business apps with real production-readiness and scalability, and embedding them with an army of agents that automate thousands of hours of work in seconds. Instead of just adding more AI capabilities to our existing platform, we treated this as a refounding moment for the company. We started with a clean-slate imagining of the ideal form factor for building apps in the agentic era. (If you want to skip all the backstory and just try it out, you can just go to All new signups get the new AI experience, and existing accounts can switch over using this link: Thread and demos below👇

Howie Liu

17,156,506 görüntüleme • 1 yıl önce