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AI + lab robotics will change experimental science. 1. Data (both positive and negative results) shared daily among a team of AI agents pursuing different hypothesis 2. Lab robotics running 24/7 with lab experiments written in code that are easily reproducible Human scientists can shepherd the whole process with...

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Jason Kelly

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22,629 просмотров • 3 месяцев назад •via X (Twitter)

ОбразованиеНаука и технологии
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Awesome being on the Sequoia Capital Training Data podcast with Pat Grady and Sonya Huang 🐥. Topic links in the 🧵 The most human part of intelligence is curiosity, and science is formalized curiosity. If we want AGI — doing the work of science is the training set. Fun to talk history of Ginkgo Bioworks, our project with OpenAI where GPT-5 ran our Autonomous Lab, what new biotech apps are coming, and more. Also — you (or your moltbot) can order experiments from Ginkgo Bioworks Cloud Lab if you don't have your own lab or buy our robots to make your own autonomous lab. Technical details of our OpenAI partnership also in 🧵
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Awesome being on the Sequoia Capital Training Data podcast with Pat Grady and Sonya Huang 🐥. Topic links in the 🧵 The most human part of intelligence is curiosity, and science is formalized curiosity. If we want AGI — doing the work of science is the training set. Fun to talk history of Ginkgo Bioworks, our project with OpenAI where GPT-5 ran our Autonomous Lab, what new biotech apps are coming, and more. Also — you (or your moltbot) can order experiments from Ginkgo Bioworks Cloud Lab if you don't have your own lab or buy our robots to make your own autonomous lab. Technical details of our OpenAI partnership also in 🧵

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A team of researchers at EPFL's Reconfigurable Robotics Lab developed an origami-like robot that can change shape, move, and interact with objects and people.
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A team of researchers at EPFL's Reconfigurable Robotics Lab developed an origami-like robot that can change shape, move, and interact with objects and people.

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Math is the essential part of reasoning. When we teach a model to do math, we are incepting the ability to reason. Sonya Huang 🐥 and I had the pleasure of speaking to Tudor Achim and Vlad Tenev about Harmonic, an AI research lab with the goal of pushing the frontiers of human knowledge through Mathematical Superintelligence (MSI)
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Math is the essential part of reasoning. When we teach a model to do math, we are incepting the ability to reason. Sonya Huang 🐥 and I had the pleasure of speaking to Tudor Achim and Vlad Tenev about Harmonic, an AI research lab with the goal of pushing the frontiers of human knowledge through Mathematical Superintelligence (MSI)

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Automating the lab bench is the best thing we can do for AI in biology. Most experiments are still run by hand. Every biologist's handiwork is unique and every lab is a little different. So, biology faces widespread reproducibility issues. But, AI will demand more reproducible data than we can produce, and generate more ideas than we can test. Experiments must be communicated and executed in a standardized way to generate reproducible data. So, Tetsuwan is building a lab where users specify experiments in an exact syntax. These experiments are executed by an automated platform to generate transparent, reproducible output. The user never needs physical access to a lab. This is a biology lab you can use like a computer. Our platform, built and tested with pilot labs over the past two years, lets users configure automated workflows rapidly & precisely. Later this year, we will bring our first services online, focusing on functional screens for protein design. Alex and I met at Caltech, where she was one year my senior. We're building this company because we were little kids who wanted to be biologists that grew up into adults who resented the lab bench. We want biology to be about asking questions, not the painful and frustrating manual process of asking them. For those looking to receive updates on our pilot services, looking for a meaningful job, or just to learn more about our work, see the links in the comments!
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.Argonne National Lab's Center for Nanoscale Materials and The University of Chicago CASE scientist Jie Xu created a self-driving lab using #AI and robotics to free up scientists, streamline experiments, save resources and accelerate the pace of discovery. More at
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.Argonne National Lab's Center for Nanoscale Materials and The University of Chicago CASE scientist Jie Xu created a self-driving lab using #AI and robotics to free up scientists, streamline experiments, save resources and accelerate the pace of discovery. More at

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Introducing the USC Physical Superintelligence (PSI) Lab ( We are rebranding to better reflect our current focus. From here on out, we are tackling one thing: solving robotics and physical intelligence with every model, every bug, and every line of code. And yes, we are hiring at all levels, especially PhDs in this cycle and potential PostDocs who are excited about robotics. We hope you can join us in this journey! 1/9
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Introducing the USC Physical Superintelligence (PSI) Lab ( We are rebranding to better reflect our current focus. From here on out, we are tackling one thing: solving robotics and physical intelligence with every model, every bug, and every line of code. And yes, we are hiring at all levels, especially PhDs in this cycle and potential PostDocs who are excited about robotics. We hope you can join us in this journey! 1/9

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We are launching a new Open Physical AI Lab to solve the generalization in robotics. Discussion with Caroline Hyde and Ed Ludlow on Bloomberg Tech this morning -
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Trained by a robotics lab at Southern University of Science and Technology (SUSTech) in Shenzhen.
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Trained by a robotics lab at Southern University of Science and Technology (SUSTech) in Shenzhen.

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AI Scientists are starting to actually do science. Not just answer questions. Not just run workflows. Introducing AutoScientists: a decentralized team of AI agents that can generate hypotheses, design experiments, write code, test ideas, analyze failures, and revise strategy as evidence accumulates. Because real research is not a to do list of tasks. It is a living search process. Leads emerge, failures matter, teams form around what works, and priorities shift when evidence changes. Much like how a lab of scientists would work on cutting edge research together. Across GPT training optimization, biomedical ML, and protein fitness prediction, this decentralized structure consistently does better research. Learn more 👇 Shanghua Gao Marinka Zitnik Kempner Institute at Harvard University DBMI at Harvard Med Harvard University
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AI Scientists are starting to actually do science. Not just answer questions. Not just run workflows. Introducing AutoScientists: a decentralized team of AI agents that can generate hypotheses, design experiments, write code, test ideas, analyze failures, and revise strategy as evidence accumulates. Because real research is not a to do list of tasks. It is a living search process. Leads emerge, failures matter, teams form around what works, and priorities shift when evidence changes. Much like how a lab of scientists would work on cutting edge research together. Across GPT training optimization, biomedical ML, and protein fitness prediction, this decentralized structure consistently does better research. Learn more 👇 Shanghua Gao Marinka Zitnik Kempner Institute at Harvard University DBMI at Harvard Med Harvard University

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AI has solved software. Biology is the next frontier. We're hiring across every team at Adaptyv. We’ve built the best automated lab for protein designers to experimentally test their AI-designed proteins. Today, the most advanced protein design companies run their wet-lab work on Adaptyv, from the biggest biopharmas to frontier AI labs to dozens of virtual biotech startups. Demand has grown faster than we have, so we’re hiring across the board: • Bio: Research associates, scientists and lab technicians to develop and run new assays at scale. • Lab automation: Engineers and interns to onboard new lab instruments and scale our automation infrastructure. • Software: Product and backend engineers to scale LabOS, our internal lab orchestration platform, our API for agents and the data pipelines that turn messy physical-world data into clean results. • Partnerships, customer success and operations: Building partnerships with AI & pharma labs, making sure customers understand their data and can run more campaigns, making sure the company operations run smoothly

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Today we’re launching Coco Robotics’ new Physical AI Lab led by Bolei Zhou, one of the world’s most cited AI researchers, and our new Chief AI Scientist. Our fleet faces unpredictable environments daily. That real world data is the key to advancing physical AI.

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AI is not on track to eradicate disease in our lifetime. Scientists need to generate more data, but they’re physically limited by how fast they can work. That’s why we’re launching Medra: Physical AI in the lab, doing and optimizing real experiments. Thread👇
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AI is not on track to eradicate disease in our lifetime. Scientists need to generate more data, but they’re physically limited by how fast they can work. That’s why we’re launching Medra: Physical AI in the lab, doing and optimizing real experiments. Thread👇

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Take a look inside the lab where AI helps run the experiments. 🧪 FutureHouse combines AI with robotics and biology tools to automate scientific discovery—testing new ideas faster than any human team could. Andrew White 🐦‍⬛ Sam Rodriques

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Robotics: coding agents’ next frontier. So how good are they? We introduce CaP-X: an open-source framework and benchmark for coding agents, where they write code for robot perception and control, execute it on sim and real robots, observe the outcomes, and iteratively improve code reliability. From NVIDIA Berkeley AI Research CMU Robotics Institute Stanford AI Lab 🧵

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Sequoia partner Grady Buchanan says systems of record SAAS like Workday, Salesforce, and ServiceNow are safer from AI. The risk sits with workflow apps in the middle, as AI agents become the new layer that does the work on top of core data.
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Sequoia partner Grady Buchanan says systems of record SAAS like Workday, Salesforce, and ServiceNow are safer from AI. The risk sits with workflow apps in the middle, as AI agents become the new layer that does the work on top of core data.

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Was fortunate to ribbon-cut the first Autonomous Lab as part of the Genesis Mission with Secretary Chris Wright. Scientists should direct autonomous labs to do their lab work 24/7 in our national labs! This is how the US keeps our lead in science - amazing leadership from U.S. Department of Energy, Director Michael Kratsios, Darío Gil, and Sriram Krishnan 🇺🇸 Excited to see how the autonomous labs program expands!
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Was fortunate to ribbon-cut the first Autonomous Lab as part of the Genesis Mission with Secretary Chris Wright. Scientists should direct autonomous labs to do their lab work 24/7 in our national labs! This is how the US keeps our lead in science - amazing leadership from U.S. Department of Energy, Director Michael Kratsios, Darío Gil, and Sriram Krishnan 🇺🇸 Excited to see how the autonomous labs program expands!

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1/ Cherry AI Robotics is building the world’s first data layer for robotics. Every autonomous robot needs a neural network to operate, which requires massive domain-specific data. Cherry AI Robotics has an entire ecosystem of products with 200k+ communities and 800k+ users. These products generate large amounts of data, which is parsed to create valuable data sets for robotics. Learn more:

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1/ We are speed running industrial robotics. It took us just 19 days from the first day of data collection to filming a 2.5-hour continuous run of our model autonomously breaking down industrial containers — zero human intervention. The data efficiency of our DVA model is fundamentally changing how fast we bring robots out of the lab and into the factory. Autonomous operation with 3 hours of data collection at a customer factory.
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1/ We are speed running industrial robotics. It took us just 19 days from the first day of data collection to filming a 2.5-hour continuous run of our model autonomously breaking down industrial containers — zero human intervention. The data efficiency of our DVA model is fundamentally changing how fast we bring robots out of the lab and into the factory. Autonomous operation with 3 hours of data collection at a customer factory.

Rhoda AI

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but how can the AI do science if science has lots of messy atoms and stuff?!? SCIENCE ROBOTS!!! (technical term) this was an incredibly fun conversation with Jason Kelly of Ginkgo Bioworks and Sonya Huang 🐥
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but how can the AI do science if science has lots of messy atoms and stuff?!? SCIENCE ROBOTS!!! (technical term) this was an incredibly fun conversation with Jason Kelly of Ginkgo Bioworks and Sonya Huang 🐥

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34,557 просмотров • 3 месяцев назад