At Benchling we're rebuilding biotech for the AI era and today we're very excited to announce our partnership with Anthropic. Anthropic launched Claude for Life Sciences because AI in biotech will compress decades of biological progress into just a few years. Today we're advancing this vision even further. ✨ Now, scientists can ask Claude questions about their Benchling data, and get source-linked answers, analyses, and insights in minutes. Benchling customers can access Benchling AI agents directly in Claude, alongside other resources like Databricks, AWS, PubMed, BioRender, 10x Genomics, and more. Congrats to the teams at Anthropic and Benchling who worked on this partnership, and cheers to Anthropic for your Life Sciences launch! Learn more here: https://lnkd.in/gCqaGSAe

This “dark data” means that without structured context, LLM solutions miss relationships, fail to predict associations, and overlook insights your scientists already know. Watch Tom Woodcock explore how Elsevier's curated data plus SciBite's structuring capabilities can illuminate what's hidden.

Big news from portfolio company Manifold, now part of the Claude for Life Sciences launch from Anthropic. Together, they’re bringing AI agents into the life sciences ecosystem — enabling researchers to accelerate workflows, analyze data more efficiently, and transform how scientific discovery happens. Congratulations to Vivek Mohta, Vinay Seth Mohta, Sourav Dey, and the entire Manifold team on this collaboration! https://lnkd.in/exQ3HGGC

🔬🧫 The Company of Biologists has selected Hum's Alchemist Engage to help researchers find, share, and build on great science. Our AI will merge real-time audience signals with 100 years of pioneering biology research to serve laser-focused article recommendations, calls-for-papers, and outreach that steer readers towards their next eureka moment. “Alchemist Engage lets us understand both our global audience and content corpus at unprecedented depth, and translate that understanding into meaningful, community-driven impact," said Kirsty McCormack, Technical Operations Director. See how the Company is using AI to accelerate discovery and engagement: https://lnkd.in/eCKDphvM  

Caroline Uhler, a professor in MIT EECS and IDSS, describes biology and medicine as going through a “data revolution” with significant advancements in AI. She believes that “the current landscape of machine learning presents a unique opportunity to address problems across different levels of biological organization, from proteins to organisms.” Read more of her interview discussing machine learning in biology, areas that are ripe for problem-solving, and cutting-edge research coming out of the Eric and Wendy Schmidt Center, of which she is the director, at the link below. https://lnkd.in/ex-aTp_J

🧠 𝗡𝗲𝘄 𝗯𝗹𝗼𝗴 𝗽𝗼𝘀𝘁: 𝗔𝘂𝘁𝗼𝗻𝗼𝗺𝗼𝘂𝘀 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗶𝗻 𝗖𝗲𝗹𝗹 𝗕𝗶𝗼 In this post, we explore the final two stages of lab autonomy. Where experiments are no longer guided by human decision making, but rather by AI predicting the next best experiment. In this setting, the wet lab functions as a reinforcement learning environment to run experiments and update models with new data. Autonomous science in cell biology is built on top of automated cell culture, cell-centric data management, and industrialized cell development protocols. 👉 𝗧𝗵𝗲 𝗳𝘂𝗹𝗹 𝗯𝗹𝗼𝗴 𝗽𝗼𝘀𝘁 𝗮𝗻𝗱 𝗹𝗶𝗻𝗸 𝘁𝗼 𝗼𝘂𝗿 𝗻𝗲𝘄𝘀𝗹𝗲𝘁𝘁𝗲𝗿 𝗶𝗻 𝘁𝗵𝗲 𝗰𝗼𝗺𝗺𝗲𝗻𝘁𝘀.

AIRAQc represents a step forward in ensuring data integrity, diagnostic confidence, and operational efficiency across histopathology workflows. From detecting artefacts to improving scanner consistency, AIRAQc is redefining how labs maintain diagnostic-grade image quality.

Virtual labs? AI teams of virtual expert scientists, bioengineers, data scientists, toxicologists and clinical scientists brainstorming to solve the next pandemic, antimicrobial resistance, rare diseases? 🔎😶🌫️🤯🦠 Let's explore our strange tech-AI-human future that at this point seems inevitable - what could it bring good and bad? Questions I seem to be asking myself everyday working at the Centre for Future Generations.

🔬 If you’re curious what Superbio can do... When you click “Build Pipeline” on Superbio, you’ll see three main categories: Protein Design, Structural Biology, and Computational Chemistry. Each opens into subfields, from binder and enzyme generation to docking, folding, and property prediction — so that every scientific question gets matched with the right AI models automatically. It’s our way of making the vast landscape of AI for biology intuitive. You don’t have to know every model or method — just what you’re trying to do. Try it yourself at app.superbio.ai and comment below what other categories and sub-categories we should develop next👇

future of manufacturing: Transition from the 4th generation industry to the 5th generation industry - Smarter monitoring leads to more reliable production of vital product. - what industrial problems can this AI + Quantum team solve next? It's very awesome and promising news.