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Today we introduce human neural loop #assembloids created from 4 parts derived from stem cells to study the cortico-striato-midbrain-thalamo-cortical pathway and to model neurodevelopmental disease Work led by the remarkable Ji-Il Kim and Yuki Miura in the lab. Also in collaboration with the Marius Pachitariu lab at HHMI |...

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Sergiu P. Pasca

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27,416 görüntüleme • 1 yıl önce •via X (Twitter)

Sağlık & İyilikBilim & Teknoloji#assembloids
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Sergiu P. Pasca profil fotoğrafı
Sergiu P. Pasca1 yıl önce

Preprint here:

Prof Peter Hotez MD PhD profil fotoğrafı
Prof Peter Hotez MD PhD1 yıl önce

Extraordinary work, really impressive!

Sergiu P. Pasca profil fotoğrafı
Sergiu P. Pasca1 yıl önce

Thank you, Peter!

Maria Robles profil fotoğrafı
Maria Robles1 yıl önce

This is incredible. Congratulations ...the implications here are mindblowing !

Maria Robles profil fotoğrafı
Maria Robles1 yıl önce

We at Robles BioCeutics are big fans of your work !

Carolyn Bertozzi profil fotoğrafı
Carolyn Bertozzi1 yıl önce

Amazing ! 🤯

Sergiu P. Pasca profil fotoğrafı
Sergiu P. Pasca1 yıl önce

Thank you 🙏

Ella Marushchenko profil fotoğrafı
Ella Marushchenko1 yıl önce

Impressive work! Congratulations, Prof. Pasca!

Sergiu P. Pasca profil fotoğrafı
Sergiu P. Pasca1 yıl önce

Thank you

Julio Aguado profil fotoğrafı
Julio Aguado1 yıl önce

wow, exciting work indeed! 🤯

Benzer Videolar

There are now hundreds of genes associated with autism & neurodevelopmental disorders but what key processes in brain development they each disrupt remains unknown. In an article in nature today, we start tackling this question by combining forebrain #assembloids with CRISPR screens to map >400 disease genes onto stages of human cortical interneuron development. Using engineered lines, regionalized neural #organoids and over 1,000 #assembloids, we discovered a group of disease genes that interfere with GABAergic neuron generation or migration, including some surprising disease mechanisms. Check out the video below for details. This work was led by the fearless Xiangling Meng in the lab!! In collaboration with Bassik lab & Georgia Panagiotakos lab! Article here: Supported by the Stanford Brain Organogenesis Center Wu Tsai Neurosciences Institute Stanford Bio-X New York Stem Cell Foundation Research Institute Biohub
1:38

There are now hundreds of genes associated with autism & neurodevelopmental disorders but what key processes in brain development they each disrupt remains unknown. In an article in nature today, we start tackling this question by combining forebrain #assembloids with CRISPR screens to map >400 disease genes onto stages of human cortical interneuron development. Using engineered lines, regionalized neural #organoids and over 1,000 #assembloids, we discovered a group of disease genes that interfere with GABAergic neuron generation or migration, including some surprising disease mechanisms. Check out the video below for details. This work was led by the fearless Xiangling Meng in the lab!! In collaboration with Bassik lab & Georgia Panagiotakos lab! Article here: Supported by the Stanford Brain Organogenesis Center Wu Tsai Neurosciences Institute Stanford Bio-X New York Stem Cell Foundation Research Institute Biohub

Sergiu P. Pasca

165,656 görüntüleme • 2 yıl önce

Our latest work is out today in Science Magazine: a self-organizing system that models organizer-driven patterning and commissural axon guidance in human neural development. This was achieved with human midline #assembloids by combining floor plate and spinal cord #organoids from pluripotent stem cells. A key advance is the three-part configuration (a floor plate squeezed in between two spinal cords), which enables human axons to cross the midline (and the subsequent synchronization of activity between the two parts seen in the video below). This platform opens the door to many applications; here, we used it to screen and identify human-enriched midline crossing regulators. Work led by Massimo Onesto with Neal Amin
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Our latest work is out today in Science Magazine: a self-organizing system that models organizer-driven patterning and commissural axon guidance in human neural development. This was achieved with human midline #assembloids by combining floor plate and spinal cord #organoids from pluripotent stem cells. A key advance is the three-part configuration (a floor plate squeezed in between two spinal cords), which enables human axons to cross the midline (and the subsequent synchronization of activity between the two parts seen in the video below). This platform opens the door to many applications; here, we used it to screen and identify human-enriched midline crossing regulators. Work led by Massimo Onesto with Neal Amin

Sergiu P. Pasca

10,345 görüntüleme • 1 yıl önce

The full video from Cortical Labs explaining how they put 200,000 brain cells onto a silicon chip and had it play Doom is wild: “When a demon appears on the left of the screen, specific electrodes stimulate the sensory area of the neural culture on the left side. The neurons react to that stimulation. We then listen to their response, the spikes, and interpret that activity as motor commands. If the neurons fire in a specific pattern, the Doom guy shoots.”
6:15

The full video from Cortical Labs explaining how they put 200,000 brain cells onto a silicon chip and had it play Doom is wild: “When a demon appears on the left of the screen, specific electrodes stimulate the sensory area of the neural culture on the left side. The neurons react to that stimulation. We then listen to their response, the spikes, and interpret that activity as motor commands. If the neurons fire in a specific pattern, the Doom guy shoots.”

Trung Phan

233,552 görüntüleme • 5 ay önce

New Paper: Continuous Thought Machines 🧠 Neurons in brains use timing and synchronization in the way that they compute, but this is largely ignored in modern neural nets. We believe neural timing is key for the flexibility and adaptability of biological intelligence. We propose a new neural architecture, “Continuous Thought Machines” (CTMs), which is built from the ground up to use neural dynamics as a core representation for intelligence. By using neural dynamics as a first-class representational citizen, CTMs naturally perform adaptive computation. Many emergent, interesting behaviors arise as a result: CTMs solve mazes by observing a raw maze image and producing step-by-step instructions directly from its neural dynamics. When tasked with image recognition, the CTM naturally takes multiple steps to examine different parts of the image before making its decision. This step-by-step approach not only makes its behavior more interpretable but also improves accuracy: the longer it “thinks,” the more accurate its answers become. We also found that this allows the CTM to decide to spend less time thinking on simpler images, thus saving energy. When identifying a gorilla, for example, the CTM’s attention moves from eyes to nose to mouth in a pattern remarkably similar to human visual attention. I think this work underscores an important, yet often lost, synergy between neuroscience and AI. While modern AI is ostensibly brain-inspired, the two fields often operate in surprising isolation. By starting with such inspiration and iteratively following the emergent, interesting behaviors, we developed a model with unexpected capabilities, such as its surprisingly strong calibration in classification tasks, a feature that was not explicitly designed for. When we initially asked, “why do this research?”, we hoped the journey of the CTM would provide compelling answers. By embracing light biological inspiration and pursuing the novel behaviors observed, we have arrived at a model with emergent capabilities that exceeded our initial designs. We are committed to continuing this exploration, borrowing further concepts to discover what new and exciting behaviors will emerge, pushing the boundaries of what AI can achieve.
0:40

New Paper: Continuous Thought Machines 🧠 Neurons in brains use timing and synchronization in the way that they compute, but this is largely ignored in modern neural nets. We believe neural timing is key for the flexibility and adaptability of biological intelligence. We propose a new neural architecture, “Continuous Thought Machines” (CTMs), which is built from the ground up to use neural dynamics as a core representation for intelligence. By using neural dynamics as a first-class representational citizen, CTMs naturally perform adaptive computation. Many emergent, interesting behaviors arise as a result: CTMs solve mazes by observing a raw maze image and producing step-by-step instructions directly from its neural dynamics. When tasked with image recognition, the CTM naturally takes multiple steps to examine different parts of the image before making its decision. This step-by-step approach not only makes its behavior more interpretable but also improves accuracy: the longer it “thinks,” the more accurate its answers become. We also found that this allows the CTM to decide to spend less time thinking on simpler images, thus saving energy. When identifying a gorilla, for example, the CTM’s attention moves from eyes to nose to mouth in a pattern remarkably similar to human visual attention. I think this work underscores an important, yet often lost, synergy between neuroscience and AI. While modern AI is ostensibly brain-inspired, the two fields often operate in surprising isolation. By starting with such inspiration and iteratively following the emergent, interesting behaviors, we developed a model with unexpected capabilities, such as its surprisingly strong calibration in classification tasks, a feature that was not explicitly designed for. When we initially asked, “why do this research?”, we hoped the journey of the CTM would provide compelling answers. By embracing light biological inspiration and pursuing the novel behaviors observed, we have arrived at a model with emergent capabilities that exceeded our initial designs. We are committed to continuing this exploration, borrowing further concepts to discover what new and exciting behaviors will emerge, pushing the boundaries of what AI can achieve.

hardmaru

257,386 görüntüleme • 1 yıl önce

In the era of 10T-parameter foundation models 😈, can we still build next-generation world representations using 🦥 a single RTX 3090 GPU? We introduce WorldString (a name inspired by string theory), a tiny neural network representation for reconstructing dynamic world instances, ranging from articulated motion and skeletal skinning to soft-body deformation. 🔥 We view object representation as the core primitive of world modeling: the basic executable unit from which perception, interaction, simulation, and generation can be built. With a compact neural basis, WorldString aims to connect dynamic object modeling with neural simulation and foundation models, enabling a scalable path toward richer representations of the physical world.
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In the era of 10T-parameter foundation models 😈, can we still build next-generation world representations using 🦥 a single RTX 3090 GPU? We introduce WorldString (a name inspired by string theory), a tiny neural network representation for reconstructing dynamic world instances, ranging from articulated motion and skeletal skinning to soft-body deformation. 🔥 We view object representation as the core primitive of world modeling: the basic executable unit from which perception, interaction, simulation, and generation can be built. With a compact neural basis, WorldString aims to connect dynamic object modeling with neural simulation and foundation models, enabling a scalable path toward richer representations of the physical world.

Xueyan Zou

38,299 görüntüleme • 1 ay önce

This is what our Osaka University team is developing in our Moonshot Internet of Brains Project. Unlike Synchron’s Stentrode, this technology can access thinner and more fragile cortical veins. By navigating into smaller vessels, it can record neural activity from a wider range of brain regions. So far, successful in pigs, and we aim to bring it to humans in the coming years.
2:50

This is what our Osaka University team is developing in our Moonshot Internet of Brains Project. Unlike Synchron’s Stentrode, this technology can access thinner and more fragile cortical veins. By navigating into smaller vessels, it can record neural activity from a wider range of brain regions. So far, successful in pigs, and we aim to bring it to humans in the coming years.

Ryota Kanai

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Evaluating Neural Networks at the Speed of Light (with Light!). See live optical inference in the video below. Excited to share recent academic work on optical neural networks as a collection of computing elements embedded in the camera lens! These elements perform computation optically even before an image is captured, using the photons in the scene instead of GPU computation after the capture. We were able to achieve ImageNet classification more than two orders of magnitude faster than conventional neural networks on today's GPUs at almost no power consumption! To do this, we developed an array of metalenses that perform this computation on light from the scene. Project: Paper: Amazing collaboration with Kaixuan Wei, Xiao Li, Johannes Froech, Praneeth Chakravarthula, James Whitehead, Ethan Tseng , Arka Majumdar .
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Evaluating Neural Networks at the Speed of Light (with Light!). See live optical inference in the video below. Excited to share recent academic work on optical neural networks as a collection of computing elements embedded in the camera lens! These elements perform computation optically even before an image is captured, using the photons in the scene instead of GPU computation after the capture. We were able to achieve ImageNet classification more than two orders of magnitude faster than conventional neural networks on today's GPUs at almost no power consumption! To do this, we developed an array of metalenses that perform this computation on light from the scene. Project: Paper: Amazing collaboration with Kaixuan Wei, Xiao Li, Johannes Froech, Praneeth Chakravarthula, James Whitehead, Ethan Tseng , Arka Majumdar .

Felix Heide

29,895 görüntüleme • 1 yıl önce

ANOTHER PANDEMIC? Investigators found thousands of vials of blood, tissue, and genetically engineered mice designed to carry COVID, HIV, Hepatitis, and Malaria. The lab was being run by a Chinese national receiving funding from the CCP. He was only hiring other Chinese nationals to work in the lab and steal American intellectual property. We need to stop letting in Chinese nationals!
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ANOTHER PANDEMIC? Investigators found thousands of vials of blood, tissue, and genetically engineered mice designed to carry COVID, HIV, Hepatitis, and Malaria. The lab was being run by a Chinese national receiving funding from the CCP. He was only hiring other Chinese nationals to work in the lab and steal American intellectual property. We need to stop letting in Chinese nationals!

Wall Street Mav

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🚨Important update from our Robot Learning Lab in London. Following recent news, we’re moving on after a wonderful 2 years… Today, we unveil 4 big pieces of research from our incredible team. Check out the compilation video and thread below to see our final work! 📽️👇
0:33

🚨Important update from our Robot Learning Lab in London. Following recent news, we’re moving on after a wonderful 2 years… Today, we unveil 4 big pieces of research from our incredible team. Check out the compilation video and thread below to see our final work! 📽️👇

Stephen James

31,095 görüntüleme • 2 yıl önce

About 15% of the world’s population — over a billion people — are affected by neurological disorders. BrainStorm, a San Diego-based startup, is accelerating the development of cures for these conditions using AI-powered computational drug discovery paired with lab experiments using organoids: tiny, 3D bundles of brain cells created from patient-derived stem cells. This hybrid, iterative method, where clinical data and AI models inform one another to accelerate drug development. Learn more ➡️ #NVIDIAInception
1:55

About 15% of the world’s population — over a billion people — are affected by neurological disorders. BrainStorm, a San Diego-based startup, is accelerating the development of cures for these conditions using AI-powered computational drug discovery paired with lab experiments using organoids: tiny, 3D bundles of brain cells created from patient-derived stem cells. This hybrid, iterative method, where clinical data and AI models inform one another to accelerate drug development. Learn more ➡️ #NVIDIAInception

NVIDIA AI Developer

26,637 görüntüleme • 1 yıl önce

Introducing Continuous Thought Machines New Blog: Modern AI is powerful, but it’s still distinct from human-like flexible intelligence. We believe neural timing is key. Our Continuous Thought Machine is built from the ground up to use neural dynamics as a powerful representation for intelligence. Thought takes time, and reasoning is a process. Biological brains inspire us with their complex neural activity, where neural timing is critical to intelligence. We’re exploring how to bring that power to AI. The Continuous Thought Machine (CTM) incorporates neuron-level temporal processing and neural synchronization, moving beyond current AI limitations. Our approach has two core innovations: (1) neuron-level temporal processing, where each neuron uses unique parameters to process a history of incoming signals for fine-grained temporal dynamics, and (2) neural synchronization, used as a direct latent representation to modulate data and produce outputs, encoding information directly in the timing of neural activity. Learn more about our approach: Interactive Report: Full Paper: GitHub :
0:57

Introducing Continuous Thought Machines New Blog: Modern AI is powerful, but it’s still distinct from human-like flexible intelligence. We believe neural timing is key. Our Continuous Thought Machine is built from the ground up to use neural dynamics as a powerful representation for intelligence. Thought takes time, and reasoning is a process. Biological brains inspire us with their complex neural activity, where neural timing is critical to intelligence. We’re exploring how to bring that power to AI. The Continuous Thought Machine (CTM) incorporates neuron-level temporal processing and neural synchronization, moving beyond current AI limitations. Our approach has two core innovations: (1) neuron-level temporal processing, where each neuron uses unique parameters to process a history of incoming signals for fine-grained temporal dynamics, and (2) neural synchronization, used as a direct latent representation to modulate data and produce outputs, encoding information directly in the timing of neural activity. Learn more about our approach: Interactive Report: Full Paper: GitHub :

Sakana AI

289,929 görüntüleme • 1 yıl önce

Regardless of whether someone uses talk therapy or pharmacology, or a combination of the two to achieve relief from depression, ultimately, any relief they experience is the consequence of neural plasticity (also called neuroplasticity), which is essentially changes in the function of neural circuits in the brain and/or body. Brain-derived neurotrophic factor (BDNF) was discovered for its role in promoting the growth, survival, and neuroplasticity of neurons, although it has other roles as well. As ketamine has emerged as a treatment for certain forms of depression, it has become clear that it works through several different mechanisms, including changing the amount of inhibition in the brain and rewiring neural circuits. Interestingly, recent findings suggest that ketamine metabolites may actually mimic some of the effects of BDNF by binding to its receptor (called trkB, which, for you aficionados, is a tyrosine kinase). To learn more about ketamine and its role in treating depression, as well as some of the risks associated with ketamine, especially recreational non-MD supervised use, see the new episode of the Huberman Lab podcast out now:
0:40

Regardless of whether someone uses talk therapy or pharmacology, or a combination of the two to achieve relief from depression, ultimately, any relief they experience is the consequence of neural plasticity (also called neuroplasticity), which is essentially changes in the function of neural circuits in the brain and/or body. Brain-derived neurotrophic factor (BDNF) was discovered for its role in promoting the growth, survival, and neuroplasticity of neurons, although it has other roles as well. As ketamine has emerged as a treatment for certain forms of depression, it has become clear that it works through several different mechanisms, including changing the amount of inhibition in the brain and rewiring neural circuits. Interestingly, recent findings suggest that ketamine metabolites may actually mimic some of the effects of BDNF by binding to its receptor (called trkB, which, for you aficionados, is a tyrosine kinase). To learn more about ketamine and its role in treating depression, as well as some of the risks associated with ketamine, especially recreational non-MD supervised use, see the new episode of the Huberman Lab podcast out now:

Andrew D. Huberman, Ph.D.

511,003 görüntüleme • 3 yıl önce

New research from MIT has identified a single amino acid that enhances the gut’s ability to repair itself — the first evidence that one nutrient alone can drive this kind of regenerative response. In this mechanistic study, researchers tested all twenty amino acids and found one that stood out. It activated immune cells in the intestinal lining to release interleukin-22 (IL-22), a signaling molecule that stimulates stem cells responsible for rebuilding the gut after injury. Mice fed a diet enriched with this amino acid showed greater stem-cell activity, more organoid formation, and faster repair of the intestinal lining after radiation damage. This was not a clinical trial, but it offers a detailed look at how diet communicates with the immune system to shape tissue regeneration at the cellular level. Study: Chi et al., Dietary cysteine enhances intestinal stemness via CD8⁺ T cell–derived IL-22 (MIT, 2025)
1:07

New research from MIT has identified a single amino acid that enhances the gut’s ability to repair itself — the first evidence that one nutrient alone can drive this kind of regenerative response. In this mechanistic study, researchers tested all twenty amino acids and found one that stood out. It activated immune cells in the intestinal lining to release interleukin-22 (IL-22), a signaling molecule that stimulates stem cells responsible for rebuilding the gut after injury. Mice fed a diet enriched with this amino acid showed greater stem-cell activity, more organoid formation, and faster repair of the intestinal lining after radiation damage. This was not a clinical trial, but it offers a detailed look at how diet communicates with the immune system to shape tissue regeneration at the cellular level. Study: Chi et al., Dietary cysteine enhances intestinal stemness via CD8⁺ T cell–derived IL-22 (MIT, 2025)

William A. Wallace, Ph.D.

14,324 görüntüleme • 9 ay önce

Luma’s mission is to make 3D creation accessible to all. We believe that neural rendering will be a significant piece of this puzzle. Sparked by NeRF and follow-up papers – including works from the now Luma research team members – neural rendering has become an incredibly productive field of research! To further accelerate the rate of advancement and help the research community grow and build, today we are excited to sponsor nerfstudio along with the Berkeley AI Research Lab (Berkeley AI Research), led by Professor Angjoo Kanazawa (Angjoo Kanazawa). Nerfstudio is a collaboration-friendly project that has greatly benefited NeRF research by providing a well-built codebase to experiment with and try new ideas in, and we are proud to be a part of this effort. 3D creation is about to change, deeply. It’s time for new ideas, weird ideas, cool ideas. Open source and product-driven research are both crucial to realize this huge vision. Join us at Luma or contribute to Nerfstudio to help us build this future!
0:45

Luma’s mission is to make 3D creation accessible to all. We believe that neural rendering will be a significant piece of this puzzle. Sparked by NeRF and follow-up papers – including works from the now Luma research team members – neural rendering has become an incredibly productive field of research! To further accelerate the rate of advancement and help the research community grow and build, today we are excited to sponsor nerfstudio along with the Berkeley AI Research Lab (Berkeley AI Research), led by Professor Angjoo Kanazawa (Angjoo Kanazawa). Nerfstudio is a collaboration-friendly project that has greatly benefited NeRF research by providing a well-built codebase to experiment with and try new ideas in, and we are proud to be a part of this effort. 3D creation is about to change, deeply. It’s time for new ideas, weird ideas, cool ideas. Open source and product-driven research are both crucial to realize this huge vision. Join us at Luma or contribute to Nerfstudio to help us build this future!

Luma AI

55,591 görüntüleme • 3 yıl önce

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 🧵
1:00

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 🧵

Jason Kelly

12,691 görüntüleme • 4 ay önce

Welcome to the Lab of the Future! 🧬🤖 Excited to share LUMI-lab, out today in Cell — a self-driving platform that pairs an AI foundation model with a robotic lab to autonomously discover ionizable lipids (LNPs) for mRNA delivery. The core problem: Designing lipid nanoparticles (LNPs) is hard. The chemical space of ionizable lipids is vast, experimental cycles are slow, and — critically — historical LNP datasets are far too small to train a predictive model from scratch. Most AI approaches in this space hit a wall immediately: not enough data to learn from. Our solution: lab-in-the-loop foundation model learning. Instead of training on LNP data alone, LUMI starts as a transformer-based foundation model pretrained across broad chemical space, building rich molecular representations before it ever sees a single LNP experiment. Then it enters a closed loop with a robotic synthesis platform: predict → synthesize → assay → update. Each round of real wet-lab experiments fine-tunes the model, which then proposes smarter candidates for the next round. The lab isn't just validating AI predictions — it's actively teaching the model, continuously. What happened when we let it run: LUMI-lab autonomously synthesized and screened 1,700+ ionizable lipids in human bronchial epithelial cells. The top candidate — LUMI-6 — features a brominated lipid tail, a structural motif that had been largely overlooked in LNP design. LUMI found it without being told where to look. When formulated into LNPs and delivered intratracheally to mice, LUMI-6 achieved 20.3% gene editing efficiency in lung epithelial cells — a compelling result for one of the hardest-to-reach therapeutic targets, directly relevant to diseases like cystic fibrosis and alpha-1 antitrypsin deficiency. Why this matters beyond LNPs: This is a proof of concept for a broader thesis — that foundation model pretraining + active learning + robotic experimentation can overcome the data scarcity bottleneck that plagues AI-driven discovery in biology. You don't need a massive domain-specific dataset to start. You need a model that can generalize, a lab that can generate the right data, and a loop that connects them. Huge congratulations to first authors Yue Xu, Haotian Cui, and Kuan Pang, and to the entire Bowen LI team. Grateful to our collaborators at University Health Network and Leslie Dan Faculty of Pharmacy, and to Princess Margaret Cancer Centre Research Princess Margaret Cancer Centre Research. 📄 Paper:
1:05

Welcome to the Lab of the Future! 🧬🤖 Excited to share LUMI-lab, out today in Cell — a self-driving platform that pairs an AI foundation model with a robotic lab to autonomously discover ionizable lipids (LNPs) for mRNA delivery. The core problem: Designing lipid nanoparticles (LNPs) is hard. The chemical space of ionizable lipids is vast, experimental cycles are slow, and — critically — historical LNP datasets are far too small to train a predictive model from scratch. Most AI approaches in this space hit a wall immediately: not enough data to learn from. Our solution: lab-in-the-loop foundation model learning. Instead of training on LNP data alone, LUMI starts as a transformer-based foundation model pretrained across broad chemical space, building rich molecular representations before it ever sees a single LNP experiment. Then it enters a closed loop with a robotic synthesis platform: predict → synthesize → assay → update. Each round of real wet-lab experiments fine-tunes the model, which then proposes smarter candidates for the next round. The lab isn't just validating AI predictions — it's actively teaching the model, continuously. What happened when we let it run: LUMI-lab autonomously synthesized and screened 1,700+ ionizable lipids in human bronchial epithelial cells. The top candidate — LUMI-6 — features a brominated lipid tail, a structural motif that had been largely overlooked in LNP design. LUMI found it without being told where to look. When formulated into LNPs and delivered intratracheally to mice, LUMI-6 achieved 20.3% gene editing efficiency in lung epithelial cells — a compelling result for one of the hardest-to-reach therapeutic targets, directly relevant to diseases like cystic fibrosis and alpha-1 antitrypsin deficiency. Why this matters beyond LNPs: This is a proof of concept for a broader thesis — that foundation model pretraining + active learning + robotic experimentation can overcome the data scarcity bottleneck that plagues AI-driven discovery in biology. You don't need a massive domain-specific dataset to start. You need a model that can generalize, a lab that can generate the right data, and a loop that connects them. Huge congratulations to first authors Yue Xu, Haotian Cui, and Kuan Pang, and to the entire Bowen LI team. Grateful to our collaborators at University Health Network and Leslie Dan Faculty of Pharmacy, and to Princess Margaret Cancer Centre Research Princess Margaret Cancer Centre Research. 📄 Paper:

Bo Wang

57,471 görüntüleme • 5 ay önce

🚨 STUDY: AGE REVERSAL PILL SHOWS PROMISING RESULTS IN DOGS, HUMAN TRIALS NEXT A groundbreaking study on age reversal, involving a new drug aimed at lengthening telomere caps on stem cells, has shown remarkable results in dogs. Zeus, a 12-year-old German Shepherd with terminal cancer, fully recovered after taking the pill, while another senior dog, Benson, regained mobility. The study, conducted by Telomir Pharmaceuticals and the Cleveland Clinic, suggests that humans could soon benefit from this treatment, potentially extending healthy lifespans significantly. Human trials are planned for 2025. Source: ABC 7
3:30

🚨 STUDY: AGE REVERSAL PILL SHOWS PROMISING RESULTS IN DOGS, HUMAN TRIALS NEXT A groundbreaking study on age reversal, involving a new drug aimed at lengthening telomere caps on stem cells, has shown remarkable results in dogs. Zeus, a 12-year-old German Shepherd with terminal cancer, fully recovered after taking the pill, while another senior dog, Benson, regained mobility. The study, conducted by Telomir Pharmaceuticals and the Cleveland Clinic, suggests that humans could soon benefit from this treatment, potentially extending healthy lifespans significantly. Human trials are planned for 2025. Source: ABC 7

Mario Nawfal

1,688,917 görüntüleme • 1 yıl önce

Wrapping up the year and coinciding with #NeurIPS2024, today at Meta FAIR we’re releasing a collection of nine new open source AI research artifacts across our work in developing agents, robustness & safety and new architectures. More in the video from Joelle Pineau. All of this work is part of FAIR’s continued work towards the goal of achieving advanced machine intelligence A few highlights from what we’re releasing today: • Meta Motivo: A first-of-its-kind behavioral foundation model that controls the movements of a virtual embodied humanoid agent to perform complex tasks. • Meta Video Seal: a state-of-the art comprehensive framework for neural video watermarking. • Meta Explore Theory-of-Mind: A program-guided adversarial data generation for theory of mind reasoning. • Meta Large Concept Models: A fundamentally different training paradigm for language modeling that decouples reasoning from language representation. And much more! We’re excited to share this work with the research community and look forward to seeing how it inspires new innovation across the field. Details and access to everything released by FAIR today ➡️
1:34

Wrapping up the year and coinciding with #NeurIPS2024, today at Meta FAIR we’re releasing a collection of nine new open source AI research artifacts across our work in developing agents, robustness & safety and new architectures. More in the video from Joelle Pineau. All of this work is part of FAIR’s continued work towards the goal of achieving advanced machine intelligence A few highlights from what we’re releasing today: • Meta Motivo: A first-of-its-kind behavioral foundation model that controls the movements of a virtual embodied humanoid agent to perform complex tasks. • Meta Video Seal: a state-of-the art comprehensive framework for neural video watermarking. • Meta Explore Theory-of-Mind: A program-guided adversarial data generation for theory of mind reasoning. • Meta Large Concept Models: A fundamentally different training paradigm for language modeling that decouples reasoning from language representation. And much more! We’re excited to share this work with the research community and look forward to seeing how it inspires new innovation across the field. Details and access to everything released by FAIR today ➡️

AI at Meta

156,123 görüntüleme • 1 yıl önce

Physicist Michio Kaku explains, the future of space travel won't rely on dangerous booster rockets, but on a "connectome"—a complete digital map containing every memory and neural pathway of the human brain. By digitizing our minds and transmitting them via laser beam, we could shoot our consciousness to the Moon in a single second or reach Mars in just 20 minutes; completely bypassing the hazards of weightlessness and radiation to explore the cosmos at the speed of light.
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Physicist Michio Kaku explains, the future of space travel won't rely on dangerous booster rockets, but on a "connectome"—a complete digital map containing every memory and neural pathway of the human brain. By digitizing our minds and transmitting them via laser beam, we could shoot our consciousness to the Moon in a single second or reach Mars in just 20 minutes; completely bypassing the hazards of weightlessness and radiation to explore the cosmos at the speed of light.

Cosmos Archive

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