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"This is only possible because we control the design, make, and test steps within one connected system rather than handing off between disconnected tools and teams." Once molecules are designed in silico, they must be synthesized and tested in the real world. In Part 7 of our platform series,...

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Recursion

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167,691 görüntüleme • 22 gün önce •via X (Twitter)

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Sergei Narykov | UHBSE22 gün önce

Connecting design, make and test in one loop is a major advantage. The next challenge is preserving that evidence chain when moving from experimental hits to human response: what transfers, what fails, and what still needs independent validation?

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PeaceWarrior22 gün önce

Future of Medicine...!

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Helicool21 gün önce

Big‑model firms like OpenAI are into AI‑drug but lack auto. Auto is the key bottleneck; owners can be the TSMC of AI pharma. Don’t bear new‑drug risks. Raise capital to build automated factories, lease to OpenAI for their payment, like building AIDCs for them.@RecursiveChris

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"Across our programs, we've advanced quality novel candidates after synthesizing only around 300 compounds, roughly 90% fewer than the industry average." Now that we have mapped the biology, we need to design the exact molecule to target it. In Part 5 of our platform series, SVP of Drug Design Donovan Chin, Ph.D., and VP of Pharmacology Martin Redhead, Ph.D., break down how we transition from biological target discovery to navigating complex chemical space. Just like our approach to biology, we solve chemistry problems through a continuous feedback loop between computation and experimentation. Before a single molecule is ever synthesized in the lab, our team uses Centaur, our integrated drug design environment. By combining hundreds of machine learning and physics-based models into a single platform, we can iteratively design novel molecular structures starting directly from target properties. This generative de novo design approach automatically updates our models so they improve with every single cycle. Our AI-native product engine has already produced over 10 development candidates. By holding our chemistry to the same rigorous standards as our biology, we can synthesize a fraction of the traditional compound volume while delivering superior novel molecules. We believe this focus on quality and novelty over sheer volume will define the true impact of AI on drug development. 🚀 Follow along over the coming weeks as we continue this series, covering how Recursion maps biology, optimizes precision drug design, and closes the gap between patient and discovery. #TechBio #DrugDesign #AIDrugDiscovery #DrugDiscovery #Chemistry
1:41

"Across our programs, we've advanced quality novel candidates after synthesizing only around 300 compounds, roughly 90% fewer than the industry average." Now that we have mapped the biology, we need to design the exact molecule to target it. In Part 5 of our platform series, SVP of Drug Design Donovan Chin, Ph.D., and VP of Pharmacology Martin Redhead, Ph.D., break down how we transition from biological target discovery to navigating complex chemical space. Just like our approach to biology, we solve chemistry problems through a continuous feedback loop between computation and experimentation. Before a single molecule is ever synthesized in the lab, our team uses Centaur, our integrated drug design environment. By combining hundreds of machine learning and physics-based models into a single platform, we can iteratively design novel molecular structures starting directly from target properties. This generative de novo design approach automatically updates our models so they improve with every single cycle. Our AI-native product engine has already produced over 10 development candidates. By holding our chemistry to the same rigorous standards as our biology, we can synthesize a fraction of the traditional compound volume while delivering superior novel molecules. We believe this focus on quality and novelty over sheer volume will define the true impact of AI on drug development. 🚀 Follow along over the coming weeks as we continue this series, covering how Recursion maps biology, optimizes precision drug design, and closes the gap between patient and discovery. #TechBio #DrugDesign #AIDrugDiscovery #DrugDiscovery #Chemistry

Recursion

1,018,443 görüntüleme • 1 ay önce

"Our integrated system narrows millions of molecules down to a short list that's synthetically accessible. Not just promising in silico, but actually makeable before a single one is sent to the labs." Traditional drug design often leans on decades of precedent and familiar chemistry. In Part 6 of our platform series, SVP of Drug Design Donovan Chin, Ph.D., explains how Recursion breaks that mold by getting a full computational design cycle up and running in about a day. Our AI-native engine vastly increases the aperture for our chemists. Instead of relying solely on known binding pockets, they can efficiently explore entirely novel and complex chemical space. By leveraging our integrated data, the team can forecast non-obvious design hypotheses and predict how to synthesize molecules even when nothing like them currently exists. This process begins by scoring binding affinity using advanced 3D structural models like Nesso-1. From there, the team runs hundreds of integrated models covering ADME, potency, advanced simulations, and AI retrosynthesis. This unified system rapidly filters millions of potential molecules down to a precise shortlist of high-quality candidates that are physically ready for the lab. 🚀 Follow along over the coming weeks as we continue this series, covering how Recursion maps biology, optimizes precision drug design, and closes the gap between patient and discovery. #TechBio #DrugDesign #ComputationalChemistry #DrugDiscovery #MachineLearning
1:21

"Our integrated system narrows millions of molecules down to a short list that's synthetically accessible. Not just promising in silico, but actually makeable before a single one is sent to the labs." Traditional drug design often leans on decades of precedent and familiar chemistry. In Part 6 of our platform series, SVP of Drug Design Donovan Chin, Ph.D., explains how Recursion breaks that mold by getting a full computational design cycle up and running in about a day. Our AI-native engine vastly increases the aperture for our chemists. Instead of relying solely on known binding pockets, they can efficiently explore entirely novel and complex chemical space. By leveraging our integrated data, the team can forecast non-obvious design hypotheses and predict how to synthesize molecules even when nothing like them currently exists. This process begins by scoring binding affinity using advanced 3D structural models like Nesso-1. From there, the team runs hundreds of integrated models covering ADME, potency, advanced simulations, and AI retrosynthesis. This unified system rapidly filters millions of potential molecules down to a precise shortlist of high-quality candidates that are physically ready for the lab. 🚀 Follow along over the coming weeks as we continue this series, covering how Recursion maps biology, optimizes precision drug design, and closes the gap between patient and discovery. #TechBio #DrugDesign #ComputationalChemistry #DrugDiscovery #MachineLearning

Recursion

1,091,744 görüntüleme • 29 gün önce

“This is the part that turns this from just a cell factory into a data factory. This high-dimensional data is the raw material our foundation models learn from. And because it’s this rich, the data is reusable, mined again and again across programs rather than generated once and thrown away.” Growing disease-relevant cells at scale is only the beginning. In Part 2 of our series on our end-to-end platform, VP of Neuroscience Chris Winrow breaks down how we run genome-scale perturbations and quantify the resulting changes in cellular state. 🔬Using acoustic liquid handlers, we move 2.5-nanoliter droplets of CRISPR-Cas9 reagents into 1,536-well plates, up to 2 million times a week. Crucially, we intentionally randomize these experiments so our machine learning models learn true biology rather than experimental artifacts. By imaging and sequencing these exact cells, we capture thousands of measurements from a single experiment. This creates a rich, reusable dataset that feeds our AI foundation models today and stays future-proofed for tomorrow. 🚀 Follow along over the coming weeks as we continue this series, covering how Recursion maps biology, optimizes precision drug design, and closes the gap between patient and discovery. #TechBio #AI #drugdiscovery #drugdesign #biology #AIdrugdiscovery
2:16

“This is the part that turns this from just a cell factory into a data factory. This high-dimensional data is the raw material our foundation models learn from. And because it’s this rich, the data is reusable, mined again and again across programs rather than generated once and thrown away.” Growing disease-relevant cells at scale is only the beginning. In Part 2 of our series on our end-to-end platform, VP of Neuroscience Chris Winrow breaks down how we run genome-scale perturbations and quantify the resulting changes in cellular state. 🔬Using acoustic liquid handlers, we move 2.5-nanoliter droplets of CRISPR-Cas9 reagents into 1,536-well plates, up to 2 million times a week. Crucially, we intentionally randomize these experiments so our machine learning models learn true biology rather than experimental artifacts. By imaging and sequencing these exact cells, we capture thousands of measurements from a single experiment. This creates a rich, reusable dataset that feeds our AI foundation models today and stays future-proofed for tomorrow. 🚀 Follow along over the coming weeks as we continue this series, covering how Recursion maps biology, optimizes precision drug design, and closes the gap between patient and discovery. #TechBio #AI #drugdiscovery #drugdesign #biology #AIdrugdiscovery

Recursion

224,658 görüntüleme • 1 ay önce

"A hypothesis from a model isn't a discovery yet. So, it goes back into the lab. The biology the model predicted is the biology we saw at the bench." A computational prediction alone does not cure a disease. In Part 4 of our platform series, Associate Principal Scientist Celia Fernandez explains how Recursion closes the loop to turn AI generated hypotheses into validated biological targets. Once our foundation models point to a potential target, we run the lab in the opposite direction. The hypothesis enters a validation cascade that becomes progressively more demanding and highly specific to the disease. This physical testing allows us to aggressively derisk our computational discoveries directly at the bench. We test these targets against the exact same high bar that our global pharma partners hold their own internal programs to. When the loop finally closes, we can confidently prove that the biology the machine learning model predicted matches the physical reality we see in the lab. 🚀Follow along over the coming weeks as we continue this series, covering how Recursion maps biology, optimizes precision drug design, and closes the gap between patient and discovery. #TechBio #AIdrugdiscovery #AI #drugdiscovery
0:42

"A hypothesis from a model isn't a discovery yet. So, it goes back into the lab. The biology the model predicted is the biology we saw at the bench." A computational prediction alone does not cure a disease. In Part 4 of our platform series, Associate Principal Scientist Celia Fernandez explains how Recursion closes the loop to turn AI generated hypotheses into validated biological targets. Once our foundation models point to a potential target, we run the lab in the opposite direction. The hypothesis enters a validation cascade that becomes progressively more demanding and highly specific to the disease. This physical testing allows us to aggressively derisk our computational discoveries directly at the bench. We test these targets against the exact same high bar that our global pharma partners hold their own internal programs to. When the loop finally closes, we can confidently prove that the biology the machine learning model predicted matches the physical reality we see in the lab. 🚀Follow along over the coming weeks as we continue this series, covering how Recursion maps biology, optimizes precision drug design, and closes the gap between patient and discovery. #TechBio #AIdrugdiscovery #AI #drugdiscovery

Recursion

1,014,580 görüntüleme • 1 ay önce

“The data is used to train our models. The models point to the targets. That’s lab-in-the-loop.” Generating millions of data points is only the first step. You need immense computational power to make sense of it (and maybe a good pair of headphones, because BioHive-2 is loud). In Part 3 of our series on our end-to-end platform, Chief Technology Officer Ben Mabey explains how Recursion turns raw data into a novel view of biology. 🖥️Using BioHive-2, one of the fastest supercomputers in the world, we train state-of-the-art foundation models to process every image and sequence we generate. These models create a unique embedding, or fingerprint, for every cellular perturbation we have ever performed. All of this high-dimensional data is compiled into a single massive dataset to form a comprehensive map of biology. By comparing known disease fingerprints against this map, we can find other genetic manipulations that create similar effects. This allows us to identify targets that drive or rescue a disease state, generating new hypotheses and pointing us towards potential novel discoveries. 🚀Follow along over the coming weeks as we continue this series, covering how Recursion maps biology, optimizes precision drug design, and closes the gap between patient and discovery. #TechBio #AI #drugdiscovery #AIdrugdiscovery #biology
1:28

“The data is used to train our models. The models point to the targets. That’s lab-in-the-loop.” Generating millions of data points is only the first step. You need immense computational power to make sense of it (and maybe a good pair of headphones, because BioHive-2 is loud). In Part 3 of our series on our end-to-end platform, Chief Technology Officer Ben Mabey explains how Recursion turns raw data into a novel view of biology. 🖥️Using BioHive-2, one of the fastest supercomputers in the world, we train state-of-the-art foundation models to process every image and sequence we generate. These models create a unique embedding, or fingerprint, for every cellular perturbation we have ever performed. All of this high-dimensional data is compiled into a single massive dataset to form a comprehensive map of biology. By comparing known disease fingerprints against this map, we can find other genetic manipulations that create similar effects. This allows us to identify targets that drive or rescue a disease state, generating new hypotheses and pointing us towards potential novel discoveries. 🚀Follow along over the coming weeks as we continue this series, covering how Recursion maps biology, optimizes precision drug design, and closes the gap between patient and discovery. #TechBio #AI #drugdiscovery #AIdrugdiscovery #biology

Recursion

59,744 görüntüleme • 1 ay önce

🧠 “To build this genome-wide map, we had to create over 1 trillion neurons, roughly the equivalent of 12 human brains. There was no blueprint for this.” To truly study a disease, you have to work with cells that actually resemble it. In Part 1 of our new series breaking down our end-to-end platform, CEO Najat Khan shares the unprecedented engineering required to map biology at an industrial scale. Starting in 2021, we set out to grow human neurons at scale – executing systematic genome-wide perturbations, and capturing high-dimensional imaging. Using specialized proprietary protocols developed in partnership with Roche and Genentech, we kept these iPSC-derived neurons alive, consistent, and biologically representative. We are already seeing the impact of this work, with Genentech having optioned the first neuroscience target from the collaboration into a joint early discovery program. This is the foundation of high-dimensional target discovery. 🚀 Make sure to follow along over the coming weeks as we continue this series, covering how Recursion maps biology, optimizes precision drug design, and closes the gap between patient and discovery.
1:19

🧠 “To build this genome-wide map, we had to create over 1 trillion neurons, roughly the equivalent of 12 human brains. There was no blueprint for this.” To truly study a disease, you have to work with cells that actually resemble it. In Part 1 of our new series breaking down our end-to-end platform, CEO Najat Khan shares the unprecedented engineering required to map biology at an industrial scale. Starting in 2021, we set out to grow human neurons at scale – executing systematic genome-wide perturbations, and capturing high-dimensional imaging. Using specialized proprietary protocols developed in partnership with Roche and Genentech, we kept these iPSC-derived neurons alive, consistent, and biologically representative. We are already seeing the impact of this work, with Genentech having optioned the first neuroscience target from the collaboration into a joint early discovery program. This is the foundation of high-dimensional target discovery. 🚀 Make sure to follow along over the coming weeks as we continue this series, covering how Recursion maps biology, optimizes precision drug design, and closes the gap between patient and discovery.

Recursion

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Can Claude Code design proteins? We're just about to release our wet lab API + SDK so we made a quick demo to test how agents can interact with protein design models and submit the proteins to our lab for testing. This closes the loop between the computational design and the experiment validation We queued up a bunch of agent-designed proteins for wet lab validation, will release the results in a couple weeks on Proteinbase
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Can Claude Code design proteins? We're just about to release our wet lab API + SDK so we made a quick demo to test how agents can interact with protein design models and submit the proteins to our lab for testing. This closes the loop between the computational design and the experiment validation We queued up a bunch of agent-designed proteins for wet lab validation, will release the results in a couple weeks on Proteinbase

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We recently released a technical report highlighting how Isomorphic Labs’ drug design engine is achieving a step change in how we model complex biological mechanisms, consistently outperforming industry benchmarks. Read our blog to discover how we’re bridging the gap between structure prediction and rational drug design. You can find the link in the comments.
0:23

We recently released a technical report highlighting how Isomorphic Labs’ drug design engine is achieving a step change in how we model complex biological mechanisms, consistently outperforming industry benchmarks. Read our blog to discover how we’re bridging the gap between structure prediction and rational drug design. You can find the link in the comments.

Isomorphic Labs

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We built a website to make it super easy to get started with protein design and participate in the Anthropic x Adaptyv protein design competition ▶️ This week, we're challenging people to design an Ozempic-like drug. You can get started in just a few clicks, using the newly released RFD4 model to design proteins targeting the GLP-1 receptor. We'll synthesize and test 1000+ of these designs in our automated biology lab, including whether they actually activate the cell receptor, and make all the results publicly available
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We built a website to make it super easy to get started with protein design and participate in the Anthropic x Adaptyv protein design competition ▶️ This week, we're challenging people to design an Ozempic-like drug. You can get started in just a few clicks, using the newly released RFD4 model to design proteins targeting the GLP-1 receptor. We'll synthesize and test 1000+ of these designs in our automated biology lab, including whether they actually activate the cell receptor, and make all the results publicly available

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“We must accelerate the process of tailoring our education system to meet the needs of the real-world economy. We also need to increase our focus on areas such as AI and automation, the digital economy, and design-driven manufacturing.” — Hon’ble PM Shri Narendra Modi in a post-budget webinar
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“We must accelerate the process of tailoring our education system to meet the needs of the real-world economy. We also need to increase our focus on areas such as AI and automation, the digital economy, and design-driven manufacturing.” — Hon’ble PM Shri Narendra Modi in a post-budget webinar

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We are excited to announce the introduction of our brand new Plugin System! This opens a new door for the community to play a more active role in creating the best design and prototyping platform. Learn more:
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We are excited to announce the introduction of our brand new Plugin System! This opens a new door for the community to play a more active role in creating the best design and prototyping platform. Learn more:

Penpot

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"We build our American cities around fire trucks… …We should design our cities, then make the fire trucks fit." In America, we have the largest fire trucks in the world— and they’re quietly shaping how our cities look, feel, and function. In this clip with Austin Tunnell , we break down how one overlooked policy is leading to worse urban design.
5:48

"We build our American cities around fire trucks… …We should design our cities, then make the fire trucks fit." In America, we have the largest fire trucks in the world— and they’re quietly shaping how our cities look, feel, and function. In this clip with Austin Tunnell , we break down how one overlooked policy is leading to worse urban design.

Chris Powers

172,257 görüntüleme • 6 ay önce

We are developing a new design paradigm that enables seamless integration of 2D and 3D on the same canvas in real time. No need for plugins or cumbersome workflows. It's all connected in a single place. All systems (frames, layouts, booleans, vectors, effects, etc.) work in sync across 2D and 3D, non-destructively. This is the starting point of a fully multi-dimensional design process. At some point in the near future, people won't need to refer to '3d design' as a separate part of the process, because it will be all part of the same system. The following is a demo of this in the works within Hana (a design canvas). We will ship this latest development in about a week.
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We are developing a new design paradigm that enables seamless integration of 2D and 3D on the same canvas in real time. No need for plugins or cumbersome workflows. It's all connected in a single place. All systems (frames, layouts, booleans, vectors, effects, etc.) work in sync across 2D and 3D, non-destructively. This is the starting point of a fully multi-dimensional design process. At some point in the near future, people won't need to refer to '3d design' as a separate part of the process, because it will be all part of the same system. The following is a demo of this in the works within Hana (a design canvas). We will ship this latest development in about a week.

Spline

56,203 görüntüleme • 10 ay önce

In 2025, we logged more than 79,000 nautical miles and over 15,000 hours of total operations with Corsair, our 24-ft ASV. Much of this was done on our own dime, operating 6 days a week at our test sites on the West Coast, East Coast, Gulf Coast, and beyond, allowing us to validate and advance our autonomy across diverse maritime environments, mission profiles, and real-world operating conditions. Not every day is perfect by design. We stress test our systems, push our vessels to their limits, and operate in challenging scenarios because that is how gaps are identified and performance improves. Every mile logged and every hour underway informs the next software update, the next design change, and the next operational improvement. If you aren’t finding issues quickly and fixing them expeditiously, you aren’t improving. This is how we advance maritime autonomy, fast. We build quickly, test and validate continuously, and iterate in real operating conditions so we can deliver capability that is proven, reliable, and ready to deliver to naval and maritime operators around the world.
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In 2025, we logged more than 79,000 nautical miles and over 15,000 hours of total operations with Corsair, our 24-ft ASV. Much of this was done on our own dime, operating 6 days a week at our test sites on the West Coast, East Coast, Gulf Coast, and beyond, allowing us to validate and advance our autonomy across diverse maritime environments, mission profiles, and real-world operating conditions. Not every day is perfect by design. We stress test our systems, push our vessels to their limits, and operate in challenging scenarios because that is how gaps are identified and performance improves. Every mile logged and every hour underway informs the next software update, the next design change, and the next operational improvement. If you aren’t finding issues quickly and fixing them expeditiously, you aren’t improving. This is how we advance maritime autonomy, fast. We build quickly, test and validate continuously, and iterate in real operating conditions so we can deliver capability that is proven, reliable, and ready to deliver to naval and maritime operators around the world.

Saronic

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Working for an equanimous chemistry within ourselves- a chemistry of peacefulness, joyfulness, & blissfulness must be brought into every individual’s life, into the cultural life of a society, the nations around the world and the entire Humanity. Our #MentalHealth- our sanity- is a fragile privilege. We must protect & nurture it. For this, there are many levels of practices in the Yogic system; completely internalized processes that people can do as simple practices with which they can bring certain equanimity to their chemistry and certain calmness to their neurological system. The technologies of inner wellbeing are what we call the Yogic Sciences. Let’s make it happen. -Sg PMO India #MannkiBaat #InnerEngineering
2:19

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Working for an equanimous chemistry within ourselves- a chemistry of peacefulness, joyfulness, & blissfulness must be brought into every individual’s life, into the cultural life of a society, the nations around the world and the entire Humanity. Our #MentalHealth- our sanity- is a fragile privilege. We must protect & nurture it. For this, there are many levels of practices in the Yogic system; completely internalized processes that people can do as simple practices with which they can bring certain equanimity to their chemistry and certain calmness to their neurological system. The technologies of inner wellbeing are what we call the Yogic Sciences. Let’s make it happen. -Sg PMO India #MannkiBaat #InnerEngineering

Sadhguru

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SOUND, FREQUENCIES, ENERGY AND VIRBRATION The divine essence within creation. "Alpha waves in the human brain are between 6 and 8 hertz. The wave frequency of the human cavity resonates between 6 and 8 hertz. All biological systems operate in the same frequency range. The human brain's alpha waves function in this range and the electrical resonance of the earth is between 6 and 8 hertz. Thus, our entire biological system - the brain and the earth itself - work on the same frequencies. If we can control that resonate system electronically, we can directly control the entire mental system of humankind." - Nikola Tesla
10:35

SOUND, FREQUENCIES, ENERGY AND VIRBRATION The divine essence within creation. "Alpha waves in the human brain are between 6 and 8 hertz. The wave frequency of the human cavity resonates between 6 and 8 hertz. All biological systems operate in the same frequency range. The human brain's alpha waves function in this range and the electrical resonance of the earth is between 6 and 8 hertz. Thus, our entire biological system - the brain and the earth itself - work on the same frequencies. If we can control that resonate system electronically, we can directly control the entire mental system of humankind." - Nikola Tesla

Redpill Drifter

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ELON MUSK: "We're starting off with an advanced technology fab here in Austin, and I'd like to thank Greg Abbott and the state of Texas for the support. So in the advanced technology fab, we will have all of the equipment necessary to make a chip of any kind logical memory, and we will also have all of the equipment necessary to make the masks. So in a single building, we can create a mask, make the chip, test the chip, make another mask, and have an incredibly fast recursive loop for improving the chip design. To the best of my knowledge, this doesn't exist anywhere in the world. We're really going to push the limit of physics in compute, and we're going to try a bunch of wild and crazy things, which you can do if you've got that fast iteration loop that I can't emphasize enough the importance of being able to make it, to test it and and then make and then change the design, do another one, and have that in a single building."
2:03

ELON MUSK: "We're starting off with an advanced technology fab here in Austin, and I'd like to thank Greg Abbott and the state of Texas for the support. So in the advanced technology fab, we will have all of the equipment necessary to make a chip of any kind logical memory, and we will also have all of the equipment necessary to make the masks. So in a single building, we can create a mask, make the chip, test the chip, make another mask, and have an incredibly fast recursive loop for improving the chip design. To the best of my knowledge, this doesn't exist anywhere in the world. We're really going to push the limit of physics in compute, and we're going to try a bunch of wild and crazy things, which you can do if you've got that fast iteration loop that I can't emphasize enough the importance of being able to make it, to test it and and then make and then change the design, do another one, and have that in a single building."

DogeDesigner

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This Star Spangled Banner changed how we heard the guitar and how we can patchwork what all America is. It is distorted and disconnected because we as a people disconnected from the old world and come here to agree to make the new world in freedom.
4:03

This Star Spangled Banner changed how we heard the guitar and how we can patchwork what all America is. It is distorted and disconnected because we as a people disconnected from the old world and come here to agree to make the new world in freedom.

Brian Roemmele

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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.
0:25

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.

Adaptyv Bio

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