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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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Abundance Institute

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22,039 görüntüleme • 9 ay önce •via X (Twitter)

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@FutureHouseSF @andrewwhite01 @SGRodriques Game changer for science, thrilled and a little nervous about oversight and safety

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Brandon Peccoralo9 ay önce

@FutureHouseSF @andrewwhite01 @SGRodriques You guys rock!

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"The only thing that works 100% of the time is measuring in a lab" Andrew White 🐦‍⬛, Head of Science FutureHouse explains why they're building an AI Scientist to run real-world experiments -vs- pursuing a more in-silico strategy for biological discovery. Excellent episode!
1:59

"The only thing that works 100% of the time is measuring in a lab" Andrew White 🐦‍⬛, Head of Science FutureHouse explains why they're building an AI Scientist to run real-world experiments -vs- pursuing a more in-silico strategy for biological discovery. Excellent episode!

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"Just like maths...was the perfect description language for physics, I think that AI is potentially the perfect description language for biology." Demis Hassabis envisions a new era of "digital biology" where AI helps us understand life's complex information processing. His dream? "Virtual cells" for faster, more efficient scientific discovery.
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"Just like maths...was the perfect description language for physics, I think that AI is potentially the perfect description language for biology." Demis Hassabis envisions a new era of "digital biology" where AI helps us understand life's complex information processing. His dream? "Virtual cells" for faster, more efficient scientific discovery.

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A new #SciencePerspective highlights the strengths and challenges of “self-driving” laboratories, spaces that combine robotics, high-throughput experiments, AI, and automated analysis to transform scientific discovery. Read more:
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A new #SciencePerspective highlights the strengths and challenges of “self-driving” laboratories, spaces that combine robotics, high-throughput experiments, AI, and automated analysis to transform scientific discovery. Read more:

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Builders Unscripted with Derya Unutmaz, MD Derya talked to Romain Huet about building tools for biology with Codex and a future where AI helps scientists simulate experiments. 09:17 Cell analysis with Codex 13:26 Simulating immune cells 29:48 The future of AI-powered science
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Builders Unscripted with Derya Unutmaz, MD Derya talked to Romain Huet about building tools for biology with Codex and a future where AI helps scientists simulate experiments. 09:17 Cell analysis with Codex 13:26 Simulating immune cells 29:48 The future of AI-powered science

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We raised a $40M Series A to build the automated lab for agentic biology. Last week, we shared the work we did with Paul Jankura: Claude designed proteins, sent them to our automated wet lab, and got real experimental data back. We believe this is where biology is going: AI agents designing experiments, running them in automated wet labs, learning from the results and iterating. But AI can only move as fast as the experiments behind it. To use the potential of AI to cure all diseases, we need to build high-throughput wet lab infrastructure: a “biological gigafactory”. That’s exactly what we’re doing at Adaptyv. Over the past year we’ve grown our lab throughput by over 5x and onboarded more than 100 customers, ranging from bio AI labs like Chai Discovery and Boltz to pharmas like Roche and Novo Nordisk to dozens and dozens of new startups that use AI to radically speed up drug discovery.
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We raised a $40M Series A to build the automated lab for agentic biology. Last week, we shared the work we did with Paul Jankura: Claude designed proteins, sent them to our automated wet lab, and got real experimental data back. We believe this is where biology is going: AI agents designing experiments, running them in automated wet labs, learning from the results and iterating. But AI can only move as fast as the experiments behind it. To use the potential of AI to cure all diseases, we need to build high-throughput wet lab infrastructure: a “biological gigafactory”. That’s exactly what we’re doing at Adaptyv. Over the past year we’ve grown our lab throughput by over 5x and onboarded more than 100 customers, ranging from bio AI labs like Chai Discovery and Boltz to pharmas like Roche and Novo Nordisk to dozens and dozens of new startups that use AI to radically speed up drug discovery.

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We are building autonomous scientific discovery. And it runs 370x faster than a human scientist. Our AI agents index millions of scientific publications and learn what an entire field has done in the time it takes a researcher to read one paper. Then we bring it to the lab to verify and further fuel learnings. 10 years to discover a material? Not here.
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We are building autonomous scientific discovery. And it runs 370x faster than a human scientist. Our AI agents index millions of scientific publications and learn what an entire field has done in the time it takes a researcher to read one paper. Then we bring it to the lab to verify and further fuel learnings. 10 years to discover a material? Not here.

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Introducing PaperQA2, the first AI agent that conducts entire scientific literature reviews on its own. PaperQA2 is also the first agent to beat PhD and Postdoc-level biology researchers on multiple literature research tasks, as measured both by accuracy on objective benchmarks and assessments by human experts. We are publishing a paper and open-sourcing the code. This is the first example of AI agents exceeding human performance on a major portion of scientific research, and will be a game-changer for the way humans interact with the scientific literature. Paper and code are below, and congratulations in particular to Michael Skarlinski, Sam Cox, Jon Laurent, James Braza, Michaela Hinks, Michael Hammerling, Manvitha Ponnapati, Andrew White 🐦‍⬛, and others who pulled this off. 1/
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Introducing PaperQA2, the first AI agent that conducts entire scientific literature reviews on its own. PaperQA2 is also the first agent to beat PhD and Postdoc-level biology researchers on multiple literature research tasks, as measured both by accuracy on objective benchmarks and assessments by human experts. We are publishing a paper and open-sourcing the code. This is the first example of AI agents exceeding human performance on a major portion of scientific research, and will be a game-changer for the way humans interact with the scientific literature. Paper and code are below, and congratulations in particular to Michael Skarlinski, Sam Cox, Jon Laurent, James Braza, Michaela Hinks, Michael Hammerling, Manvitha Ponnapati, Andrew White 🐦‍⬛, and others who pulled this off. 1/

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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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*sponsored Take a look inside the action with AI from Google Cloud, bringing new data insights to help Team USA athletes these Winter Games and beyond.
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*sponsored Take a look inside the action with AI from Google Cloud, bringing new data insights to help Team USA athletes these Winter Games and beyond.

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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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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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🧬 Take a look inside a 3D tissue bioprinting lab! NIH postdoctoral fellow Dr. Cristina Antich Acedo demonstrates how cutting-edge bioprinting can recreate human tissue structure. By combining different cell types and biomaterials, researchers can mimic real biological environments with precision. 🔬 This technology helps accelerate the path from discovery to treatment: • More predictive preclinical models • Reduced reliance on animal testing • Faster, more accurate drug development

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Sam Altman says he’s excited about a future where signing up for ChatGPT’s highest tier gets you a free humanoid robot. ⦿ The mechanical engineering and AI for humanoids are quite hard but feel within grasp. ⦿ Making a billion humanoid robots will take a while; maybe the first million humanoid robots, built the old-fashioned way, will automate the entire robotics supply chain to enable faster scale. ⦿ The demand for humanoids will be far more than what we can handle with current supply chains. ⦿ Things we've tried to bring manufacturing back to the US have failed. AI & robotics is a potential solution.

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ADL CEO Jonathan Greenblatt warns all Americans they now have AI-powered tools capable of taking open-source intelligence to a terrifying new level. These systems can scan tens of millions of posts messages and digital footprints faster than any human could ever track. These AI tools see everything turning public information into a weaponized map of your digital life.

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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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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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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 regular readouts of progress (sort of like every scientists getting to operate as principle investigator) -- these are real advantages over how we do this work today. Enjoyed chatting about it with Pat Grady and Sonya Huang 🐥 at Sequoia Capital!
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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 regular readouts of progress (sort of like every scientists getting to operate as principle investigator) -- these are real advantages over how we do this work today. Enjoyed chatting about it with Pat Grady and Sonya Huang 🐥 at Sequoia Capital!

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Mark Zuckerberg and Priscilla Chan say virtual cells could change how science takes risk, letting researchers test bold ideas in simulation before entering the wet lab. “The promise of being able to do virtual biology… is you can actually take on riskier ideas.” “If you had a virtual cell model… you could actually then start testing it and tinkering on the computational side… and actually see if there is promise doing the experiments in silico before you make the time and money investment in the wet lab.”
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Mark Zuckerberg and Priscilla Chan say virtual cells could change how science takes risk, letting researchers test bold ideas in simulation before entering the wet lab. “The promise of being able to do virtual biology… is you can actually take on riskier ideas.” “If you had a virtual cell model… you could actually then start testing it and tinkering on the computational side… and actually see if there is promise doing the experiments in silico before you make the time and money investment in the wet lab.”

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For decades, drive-thru ordering has relied on human workers to take customer orders. Now, McDonald's is testing artificial intelligence technology that could automate the process entirely. The popular fast-food chain revealed the new system, called ArchIQ, a Google-powered AI ordering platform, at the company's 2026 worldwide convention.
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For decades, drive-thru ordering has relied on human workers to take customer orders. Now, McDonald's is testing artificial intelligence technology that could automate the process entirely. The popular fast-food chain revealed the new system, called ArchIQ, a Google-powered AI ordering platform, at the company's 2026 worldwide convention.

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