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, and now Bristol Myers Squibb. Many of the world’s leading biopharma companies are now using our models to go after diseases. Scientific discovery is the domain where access to frontier AI matters the most. At Chai Discovery, we’ve seen first hand how our latest model generations can make the difference between discovering a molecule and not. We’re excited to work with Bristol Myers Squibb to break new ground in medicine and science.show more

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.show more

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! 🧪show more

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:show more

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.show more

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 1/2show more

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.show more

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.show more

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:show more

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.show more

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!show more

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: #JPM2026show more

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 #SandboxAQshow more

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.show more

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 Advocacyshow more

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)show more

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.show more

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:show more

🌠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👇show more

It’s time for a change. A big one, in... fact, as we’re embarking on the next chapter of our journey, focused on groundbreaking implementations of AI both in trading and on-chain. We’ve been building behind the scenes for a while, and now it’s time to reveal all-new products that go above and beyond our previous roadmap. To reflect this, we’re also revamping our brand identity and becoming Numerico. The token ticker $NWC and contract addresses will remain the same, but the name has been changed. We’re incredibly grateful for your support all these years as the NewsCrypto community, and we’re excited to have you with us at We are determined and ready to reshape the way we implement AI, with groundbreaking applications both in trading and on-chain. Exciting times ahead!show more