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i write on AI, longevity, singularity, robotics, energy and the latest SciTech breakthroughs. In a simple, easy-to-read feed ↘️! by (@alxom17)

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This is getting unreal. "A huge humanoid robotics wave is about to arrive 👀" Chinese robotics company AheadForm just unveiled one of the world's most lifelike humanoid robots at WAIC 2026 in Shanghai. This AI-powered humanoid can hold natural conversations, maintain eye contact, blink, display realistic facial expressions and synchronize its speech with lifelike head and facial movements.

This is getting unreal. "A huge humanoid robotics wave is about to arrive 👀" Chinese robotics company AheadForm just unveiled one of the world's most lifelike humanoid robots at WAIC 2026 in Shanghai. This AI-powered humanoid can hold natural conversations, maintain eye contact, blink, display realistic facial expressions and synchronize its speech with lifelike head and facial movements.

464,916 просмотров

wow. This is insane A Nobel laureate claims his high‑pulse laser system could unlock safe, uranium‑free fusion and power hundreds of thousands of homes if prototypes succeed 🤯! Shuji Nakamura, a nobel price winning physicist who invented the blue LED, is now leading Blue Laser Fusion, a company aiming to make commercial nuclear fusion a reality. Nakamura estimates that about 99.5% of fusion research has focused on magnetic confinement, while his team is pursuing the remaining 0.5% through advanced laser technology. At the heart of the concept is OEC, an Optical Enhancement Cavity that stores high-energy laser pulses and can amplify them by up to 100,000×. According to the team, this could provide precise control over the fusion process while improving efficiency and reducing engineering risks. Researchers at the UCSB compare the system to a hammer and an anvil: the laser acts as the hammer that strikes the hydrogen fuel target, while the optical chamber acts as the anvil, storing and regulating the laser energy needed to initiate fusion. If development stays on schedule, Blue Laser Fusion plans to build a 1-gigawatt pilot fusion power plant near Santa Barbara by 2032, capable of supplying electricity to hundreds of thousands of homes. Nakamura's blue LED transformed energy-efficient lighting around the world. As per the International Energy Agency, if older lighting technologies were still used, global indoor lighting electricity consumption would be about 70% higher, while the electricity saved by LEDs is comparable to the power consumption of South Korea. Now, Nakamura hopes to make an even bigger impact through Blue Laser Fusion by developing virtually limitless, zero-carbon fusion energy that could transform how the world powers homes, industry and future technologies.

wow. This is insane A Nobel laureate claims his high‑pulse laser system could unlock safe, uranium‑free fusion and power hundreds of thousands of homes if prototypes succeed 🤯! Shuji Nakamura, a nobel price winning physicist who invented the blue LED, is now leading Blue Laser Fusion, a company aiming to make commercial nuclear fusion a reality. Nakamura estimates that about 99.5% of fusion research has focused on magnetic confinement, while his team is pursuing the remaining 0.5% through advanced laser technology. At the heart of the concept is OEC, an Optical Enhancement Cavity that stores high-energy laser pulses and can amplify them by up to 100,000×. According to the team, this could provide precise control over the fusion process while improving efficiency and reducing engineering risks. Researchers at the UCSB compare the system to a hammer and an anvil: the laser acts as the hammer that strikes the hydrogen fuel target, while the optical chamber acts as the anvil, storing and regulating the laser energy needed to initiate fusion. If development stays on schedule, Blue Laser Fusion plans to build a 1-gigawatt pilot fusion power plant near Santa Barbara by 2032, capable of supplying electricity to hundreds of thousands of homes. Nakamura's blue LED transformed energy-efficient lighting around the world. As per the International Energy Agency, if older lighting technologies were still used, global indoor lighting electricity consumption would be about 70% higher, while the electricity saved by LEDs is comparable to the power consumption of South Korea. Now, Nakamura hopes to make an even bigger impact through Blue Laser Fusion by developing virtually limitless, zero-carbon fusion energy that could transform how the world powers homes, industry and future technologies.

16,009 просмотров

Brain cell communication seen in action. Scientists have captured the millisecond fast process of brain cell communication using advanced imaging. Teams in Berlin and the US used rapid freezing techniques on mouse and human neurons to observe neurotransmitter release and vesicle recycling, revealing key steps and proteins involved. This could help understand brain diseases.

Brain cell communication seen in action. Scientists have captured the millisecond fast process of brain cell communication using advanced imaging. Teams in Berlin and the US used rapid freezing techniques on mouse and human neurons to observe neurotransmitter release and vesicle recycling, revealing key steps and proteins involved. This could help understand brain diseases.

15,667 просмотров

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sam altman: - someday everyone should have a personal robot. - we will definitely build humanoid robots, while also exploring other form factors. - the form factor is less important than figuring out the AI brain that makes the robot work. - he also agreed on building a kind of “super-app” that combines ChatGPT and Codex for AI. - he wants one AI interface that can do whatever you need. - it could use your computer and access your context when needed. - you shouldn't have to choose tabs, tools, or modes. AI should figure it out. - AI should be smart enough to understand what you want and act on it.

sam altman: - someday everyone should have a personal robot. - we will definitely build humanoid robots, while also exploring other form factors. - the form factor is less important than figuring out the AI brain that makes the robot work. - he also agreed on building a kind of “super-app” that combines ChatGPT and Codex for AI. - he wants one AI interface that can do whatever you need. - it could use your computer and access your context when needed. - you shouldn't have to choose tabs, tools, or modes. AI should figure it out. - AI should be smart enough to understand what you want and act on it.

23,606 просмотров • 1 день назад

Wow. This is crazy. A developer trained an AI agent in simulation and deployed it onto a real robotic air hockey table using reinforcement learning. This robot can track the puck with millimeter-level accuracy and react in roughly 20 milliseconds, fast enough to challenge even skilled human players. We’re moving from robots that follow programmed rules to machines that learn strategies in simulation and execute them in the physical world.

Wow. This is crazy. A developer trained an AI agent in simulation and deployed it onto a real robotic air hockey table using reinforcement learning. This robot can track the puck with millimeter-level accuracy and react in roughly 20 milliseconds, fast enough to challenge even skilled human players. We’re moving from robots that follow programmed rules to machines that learn strategies in simulation and execute them in the physical world.

1,585,308 просмотров • 3 месяцев назад

Holy shit. AI agent just learned to fix a quantum computer. 🤯 “This is how the era of self-maintaining machines begins.” Anthropic’s Claude AI agent developed software that can automatically recover drifting lasers used in QuEra’s neutral-atom quantum computers. “Researchers connected Claude to real laboratory hardware through Anthropic’s Model Hardware Standard (MHS), allowing it to modify control software, run experiments, analyze measurements, and improve its strategy.” “The laser’s frequency must remain extremely precise to reliably control the atoms used as quantum bits.” “A process that could take human specialists about 5–10 minutes was reduced to just 0.9–5.4 seconds for smaller disturbances and about 10–14 seconds for the hardest mode-hop events.” 🤯 “The AI-developed controller successfully recovered the correct laser lock in 695 of 700 tests, achieving a 99.3% success rate across 7 disturbance classes.” “During testing, the system also encountered 43 naturally occurring laser mode hops and recovered from all 43 without human intervention.” “Claude then optimized 12 interdependent laser-control parameters across approximately 12,500 evaluations, reducing residual frequency noise by about 5×.” “During a roughly 19-hour unattended test, the optimized system experienced zero lock drops, compared with about 1.6 lock drops per hour before optimization.” “Claude also autonomously commissioned a second laser wavelength in a single unattended overnight run, a process that would normally require weeks of hands-on specialist work.” “For decades, humans built machines that needed us to fix them. Now, we’re teaching machines to help fix themselves. 🫡♥️!

Holy shit. AI agent just learned to fix a quantum computer. 🤯 “This is how the era of self-maintaining machines begins.” Anthropic’s Claude AI agent developed software that can automatically recover drifting lasers used in QuEra’s neutral-atom quantum computers. “Researchers connected Claude to real laboratory hardware through Anthropic’s Model Hardware Standard (MHS), allowing it to modify control software, run experiments, analyze measurements, and improve its strategy.” “The laser’s frequency must remain extremely precise to reliably control the atoms used as quantum bits.” “A process that could take human specialists about 5–10 minutes was reduced to just 0.9–5.4 seconds for smaller disturbances and about 10–14 seconds for the hardest mode-hop events.” 🤯 “The AI-developed controller successfully recovered the correct laser lock in 695 of 700 tests, achieving a 99.3% success rate across 7 disturbance classes.” “During testing, the system also encountered 43 naturally occurring laser mode hops and recovered from all 43 without human intervention.” “Claude then optimized 12 interdependent laser-control parameters across approximately 12,500 evaluations, reducing residual frequency noise by about 5×.” “During a roughly 19-hour unattended test, the optimized system experienced zero lock drops, compared with about 1.6 lock drops per hour before optimization.” “Claude also autonomously commissioned a second laser wavelength in a single unattended overnight run, a process that would normally require weeks of hands-on specialist work.” “For decades, humans built machines that needed us to fix them. Now, we’re teaching machines to help fix themselves. 🫡♥️!

30,071 просмотров • 8 дней назад

“AI MODELS COULD BECOME 10× SMALLER WITHOUT LOSING MOST OF THEIR INTELLIGENCE.” Mark Zuckerberg says one of the most powerful developments in AI is model distillation: taking the capabilities of a much larger model and transferring them into a much smaller one. - Meta's huge frontier models can serve as "teachers" for smaller models. - Zuckerberg says a model could potentially retain around 90–95% of the larger model's intelligence while being only ~10% of its size. - That means dramatically lower inference costs, memory requirements and computing power. - Developers can distill and customize these capabilities for their own applications. And that's where open-source models come into the picture.

“AI MODELS COULD BECOME 10× SMALLER WITHOUT LOSING MOST OF THEIR INTELLIGENCE.” Mark Zuckerberg says one of the most powerful developments in AI is model distillation: taking the capabilities of a much larger model and transferring them into a much smaller one. - Meta's huge frontier models can serve as "teachers" for smaller models. - Zuckerberg says a model could potentially retain around 90–95% of the larger model's intelligence while being only ~10% of its size. - That means dramatically lower inference costs, memory requirements and computing power. - Developers can distill and customize these capabilities for their own applications. And that's where open-source models come into the picture.

77,374 просмотров • 29 дней назад

“AI COULD SOON THINK 100× TO 1,000× FASTER THAN HUMANS.” Emad Mostaque says AI systems are about to become dramatically faster as specialized AI hardware improves. He says humans currently operate at roughly 20–30 tokens per second, while current AI models are around 40 tokens per second. He points to Taalas' technology, which he says demonstrated an 8-billion-parameter model generating around 14,000 tokens per second. Mostaque says current AI systems are effectively “thinking at the speed of a human”, but that will soon change. He predicts AI systems could reach 1,000 tokens per second, followed by 10,000 tokens per second by the end of next year. His broader point is that AI could eventually “think a thousand times faster” than humans.

“AI COULD SOON THINK 100× TO 1,000× FASTER THAN HUMANS.” Emad Mostaque says AI systems are about to become dramatically faster as specialized AI hardware improves. He says humans currently operate at roughly 20–30 tokens per second, while current AI models are around 40 tokens per second. He points to Taalas' technology, which he says demonstrated an 8-billion-parameter model generating around 14,000 tokens per second. Mostaque says current AI systems are effectively “thinking at the speed of a human”, but that will soon change. He predicts AI systems could reach 1,000 tokens per second, followed by 10,000 tokens per second by the end of next year. His broader point is that AI could eventually “think a thousand times faster” than humans.

11,565 просмотров • 6 дней назад

AI is entering its physics era guys.. A duo refused Bezos' multi-billion-dollar offer, then unveiled an AI model that no PC can run. "They unveiled Accelerated Understanding (AU), a new physics-first AI startup that takes a different approach from traditional language models. Its models are designed to predict how physical systems evolve across space and time." "In testing, the model processed 5 trillion pieces of physical data in a single prompt — roughly 5 million times more data than Google Gemini or Anthropic Claude can handle at once. This isn't 5 trillion words or tokens. It's massive 3D + time (4D) physical data." 👀 "The model uses neural operators instead of conventional Transformer architectures, and it's designed to simulate phenomena such as weather, fluid dynamics, materials, geology and semiconductor behavior." "AU says it has trained models with up to 1 trillion parameters, with scaling experiments reaching 35 trillion parameters. A 5-trillion-point inference can reportedly generate around 22 TB of output." Now, AI is moving from predicting what comes next in a sentence to predicting what happens next in the physical world. Acceleration is everywhere! 👀

AI is entering its physics era guys.. A duo refused Bezos' multi-billion-dollar offer, then unveiled an AI model that no PC can run. "They unveiled Accelerated Understanding (AU), a new physics-first AI startup that takes a different approach from traditional language models. Its models are designed to predict how physical systems evolve across space and time." "In testing, the model processed 5 trillion pieces of physical data in a single prompt — roughly 5 million times more data than Google Gemini or Anthropic Claude can handle at once. This isn't 5 trillion words or tokens. It's massive 3D + time (4D) physical data." 👀 "The model uses neural operators instead of conventional Transformer architectures, and it's designed to simulate phenomena such as weather, fluid dynamics, materials, geology and semiconductor behavior." "AU says it has trained models with up to 1 trillion parameters, with scaling experiments reaching 35 trillion parameters. A 5-trillion-point inference can reportedly generate around 22 TB of output." Now, AI is moving from predicting what comes next in a sentence to predicting what happens next in the physical world. Acceleration is everywhere! 👀

19,294 просмотров • 12 дней назад

This is getting unreal. Robot dogs are reaching superhuman levels of agility 🤯 Chinese robotics company UNIUBI AI just unveiled Lingmao, the world's first quadruped robot to perform a continuous 720° backflip, at WAIC 2026 in Shanghai. This AI-powered robot completed two full aerial rotations in a single jump, landed stably, carries 1.3× its own body weight, and is powered by NVIDIA Orin.

This is getting unreal. Robot dogs are reaching superhuman levels of agility 🤯 Chinese robotics company UNIUBI AI just unveiled Lingmao, the world's first quadruped robot to perform a continuous 720° backflip, at WAIC 2026 in Shanghai. This AI-powered robot completed two full aerial rotations in a single jump, landed stably, carries 1.3× its own body weight, and is powered by NVIDIA Orin.

56,020 просмотров • 1 месяц назад

Thats awesome! A developer used Al-powered 4D Gaussian Splatting to convert flat video footage into dynamic 3D spatial scenes. The system reconstructs different camera angles and depth information from ordinary footage, making it possible to navigate scenes in three dimensions. We're moving from recording video to digitally recreating reality itself.

Thats awesome! A developer used Al-powered 4D Gaussian Splatting to convert flat video footage into dynamic 3D spatial scenes. The system reconstructs different camera angles and depth information from ordinary footage, making it possible to navigate scenes in three dimensions. We're moving from recording video to digitally recreating reality itself.

73,502 просмотров • 3 месяцев назад

"Modern AI was built on one simple idea: machines can learn." Ilya Sutskever says that in the early 2000s, computers couldn't truly learn, and many weren't even sure artificial learning was possible. "He believed neural networks offered the best long-term path because they could learn from data, improve automatically, and scale with increasingly powerful parallel computers." "Back then, models had only dozens or hundreds of neurons, a million parameters was considered huge, and researchers trained them on CPUs using MATLAB."

"Modern AI was built on one simple idea: machines can learn." Ilya Sutskever says that in the early 2000s, computers couldn't truly learn, and many weren't even sure artificial learning was possible. "He believed neural networks offered the best long-term path because they could learn from data, improve automatically, and scale with increasingly powerful parallel computers." "Back then, models had only dozens or hundreds of neurons, a million parameters was considered huge, and researchers trained them on CPUs using MATLAB."

29,171 просмотров • 1 месяц назад

Alexandr Wang says AI will transform civilization faster than most people realize. - Meta has seen agentic systems outperform teams of 100 engineers on certain tasks. - Intelligence and agency will become abundant, no longer the bottleneck of progress. - Humanity could change more in the next 10 years than in the last 100 years. - Systematic and rigorous thinking are still incredibly important because of abstraction layer. - Even if AI models stopped improving today, we'd still have decades of economic and societal transformation ahead. - AI agents could let startups compete with tech giants by acting like teams of thousands. - Future AI systems may coordinate millions, then trillions of AI agents working together. - Every major AI wave has been roughly 10× bigger than the last: Self-driving AI → LLMs | LLMs → Coding agents | Coding agents → The next generation of AI products 👀 - AI could make building companies 10× to 100× easier, shifting the scarce resource from intelligence to vision and ambition. He believes we're entering a once in a civilization opportunity to build companies, discover new science and solve humanity's biggest problems.

Alexandr Wang says AI will transform civilization faster than most people realize. - Meta has seen agentic systems outperform teams of 100 engineers on certain tasks. - Intelligence and agency will become abundant, no longer the bottleneck of progress. - Humanity could change more in the next 10 years than in the last 100 years. - Systematic and rigorous thinking are still incredibly important because of abstraction layer. - Even if AI models stopped improving today, we'd still have decades of economic and societal transformation ahead. - AI agents could let startups compete with tech giants by acting like teams of thousands. - Future AI systems may coordinate millions, then trillions of AI agents working together. - Every major AI wave has been roughly 10× bigger than the last: Self-driving AI → LLMs | LLMs → Coding agents | Coding agents → The next generation of AI products 👀 - AI could make building companies 10× to 100× easier, shifting the scarce resource from intelligence to vision and ambition. He believes we're entering a once in a civilization opportunity to build companies, discover new science and solve humanity's biggest problems.

27,449 просмотров • 1 месяц назад

3 Years Back, Ilya Sutskever on AI 👀 And here's what happening right now..

3 Years Back, Ilya Sutskever on AI 👀 And here's what happening right now..

20,263 просмотров • 1 месяц назад

Wow. That's cool. Researchers just released World, an open-source Unreal Engine 5 simulator for training and testing LLM and VLM agents in realistic 3D environments. The platform supports RGB, depth, and segmentation sensors, along with navigation, vehicles, pedestrians, robots and procedural city generation. It's built with a Gym-like Python interface, it allows AI agents to learn physical and social reasoning in complex virtual worlds before real world deployment. We're moving from AI that only understands information to AI that can perceive, reason and act inside realistic simulated environments.

Wow. That's cool. Researchers just released World, an open-source Unreal Engine 5 simulator for training and testing LLM and VLM agents in realistic 3D environments. The platform supports RGB, depth, and segmentation sensors, along with navigation, vehicles, pedestrians, robots and procedural city generation. It's built with a Gym-like Python interface, it allows AI agents to learn physical and social reasoning in complex virtual worlds before real world deployment. We're moving from AI that only understands information to AI that can perceive, reason and act inside realistic simulated environments.

47,725 просмотров • 3 месяцев назад

"Superintelligence won't arrive all at once. It will emerge through automation." Andrej Karpathy says superintelligence is best understood as the long-term continuation of automation. First, AI automates digital work. Then physical work. Eventually, even scientific discovery, invention, and decision making become increasingly automated. The biggest challenge may not be a single AI taking over. It could be a gradual loss of human understanding and control as billions of autonomous AI systems interact, compete, and make decisions at a scale and speed no human can fully comprehend. Superintelligence may not look like one all-powerful AI. It may look like an economy of autonomous intelligences 👀

"Superintelligence won't arrive all at once. It will emerge through automation." Andrej Karpathy says superintelligence is best understood as the long-term continuation of automation. First, AI automates digital work. Then physical work. Eventually, even scientific discovery, invention, and decision making become increasingly automated. The biggest challenge may not be a single AI taking over. It could be a gradual loss of human understanding and control as billions of autonomous AI systems interact, compete, and make decisions at a scale and speed no human can fully comprehend. Superintelligence may not look like one all-powerful AI. It may look like an economy of autonomous intelligences 👀

15,509 просмотров • 1 месяц назад

Demis Hassabis believes AI could revolutionize medicine within the next few years. - AI already solved the 50-year protein folding challenge with AlphaFold. - Future AI systems could design new drugs automatically. - Drug discovery could shrink from 10 years to months, weeks, or even days. - Most experiments may happen in simulations before human validation. - Personalized medicines tailored to individuals could become possible. - Demis believes AI could bring all diseases within reach of treatment. Future of healthcare could be extraordinary!

Demis Hassabis believes AI could revolutionize medicine within the next few years. - AI already solved the 50-year protein folding challenge with AlphaFold. - Future AI systems could design new drugs automatically. - Drug discovery could shrink from 10 years to months, weeks, or even days. - Most experiments may happen in simulations before human validation. - Personalized medicines tailored to individuals could become possible. - Demis believes AI could bring all diseases within reach of treatment. Future of healthcare could be extraordinary!

31,146 просмотров • 2 месяцев назад

Demis Hassabis says we're entering the "foothills of the singularity." 👀 - He believes AGI could arrive around 2030 (plus or minus a year), marking the beginning of a completely new era for humanity. - According to Hassabis, this year's advances in AI agents, reasoning, and tool use are the first real signs that AI is becoming genuinely useful in everyday workflows. - He says multiple breakthroughs are now converging at once, making progress much faster than expected and giving him confidence that this transformation is approaching. - Hassabis believes society has only a few years to prepare for the profound impact AGI could have, because the choices we make now will shape the future. - Beyond AGI, he says AI could revolutionize biology and medicine. After AlphaFold predicted the structures of over 200 million proteins, his company Isomorphic Labs aims to reduce drug discovery from years to months and eventually even weeks. The next decade could become one of the most transformative periods in human history.

Demis Hassabis says we're entering the "foothills of the singularity." 👀 - He believes AGI could arrive around 2030 (plus or minus a year), marking the beginning of a completely new era for humanity. - According to Hassabis, this year's advances in AI agents, reasoning, and tool use are the first real signs that AI is becoming genuinely useful in everyday workflows. - He says multiple breakthroughs are now converging at once, making progress much faster than expected and giving him confidence that this transformation is approaching. - Hassabis believes society has only a few years to prepare for the profound impact AGI could have, because the choices we make now will shape the future. - Beyond AGI, he says AI could revolutionize biology and medicine. After AlphaFold predicted the structures of over 200 million proteins, his company Isomorphic Labs aims to reduce drug discovery from years to months and eventually even weeks. The next decade could become one of the most transformative periods in human history.

18,875 просмотров • 1 месяц назад

"we take 92-year old human skin cells back to a biological age of around 25 using OSK." David Sinclair says AI could help make age reversal a reality. 👀 - AI screened up to 1 trillion molecules in just a few months, a task that would have taken hundreds to thousands of years using traditional drug discovery. - AI narrowed 1 trillion molecules to around 200 promising drug candidates for laboratory testing. - Researchers used Google DeepMind's AlphaFold protein predictions to virtually test molecules against human proteins before entering the lab. - AI is also helping determine whether human cells have become biologically younger simply by analyzing images of the cells. - Sinclair says his lab can already reprogram 92-year-old human skin cells to a biological age of around 20-25 using OSK partial cellular reprogramming. - "All my students can do this." - "It's not hard at all to reverse aging in isolated human cells." - "The hard part over the last 10 years has been turning it into a safe and effective drug for people." - Biological age is measured using DNA methylation clocks, which Sinclair says are more informative than relying only on telomeres. - Sinclair believes that one day you may no longer be able to tell how old someone is just by looking at them. - Sinclair says his team has early evidence that lost memories can return after brain rejuvenation, adding that the work has not yet been published. - He believes Alzheimer's patients may still retain their memories but have difficulty accessing them. - He believes making the entire body biologically younger could one day cure diseases that are currently incurable. 🤯 - He also said, making the entire body biologically younger could enable it to heal diseases that are currently incurable. Sinclair's approach is simple: "Make the body young, and it will heal itself."

"we take 92-year old human skin cells back to a biological age of around 25 using OSK." David Sinclair says AI could help make age reversal a reality. 👀 - AI screened up to 1 trillion molecules in just a few months, a task that would have taken hundreds to thousands of years using traditional drug discovery. - AI narrowed 1 trillion molecules to around 200 promising drug candidates for laboratory testing. - Researchers used Google DeepMind's AlphaFold protein predictions to virtually test molecules against human proteins before entering the lab. - AI is also helping determine whether human cells have become biologically younger simply by analyzing images of the cells. - Sinclair says his lab can already reprogram 92-year-old human skin cells to a biological age of around 20-25 using OSK partial cellular reprogramming. - "All my students can do this." - "It's not hard at all to reverse aging in isolated human cells." - "The hard part over the last 10 years has been turning it into a safe and effective drug for people." - Biological age is measured using DNA methylation clocks, which Sinclair says are more informative than relying only on telomeres. - Sinclair believes that one day you may no longer be able to tell how old someone is just by looking at them. - Sinclair says his team has early evidence that lost memories can return after brain rejuvenation, adding that the work has not yet been published. - He believes Alzheimer's patients may still retain their memories but have difficulty accessing them. - He believes making the entire body biologically younger could one day cure diseases that are currently incurable. 🤯 - He also said, making the entire body biologically younger could enable it to heal diseases that are currently incurable. Sinclair's approach is simple: "Make the body young, and it will heal itself."

10,180 просмотров • 1 месяц назад

Robotics just hit a dexterity milestone 🤯! Sharpa Robotics demonstrated autonomous dual-hand apple peeling using its new MoDE-VLA system. Using human-like dexterous hands with tactile sensing, the robot can feel contact and adjust its grip while rotating and peeling the apple. While the system achieved 30% success, the 73% peel completion rate shows robots are starting to master the fine, contact-rich manipulation needed for real world tasks.

Robotics just hit a dexterity milestone 🤯! Sharpa Robotics demonstrated autonomous dual-hand apple peeling using its new MoDE-VLA system. Using human-like dexterous hands with tactile sensing, the robot can feel contact and adjust its grip while rotating and peeling the apple. While the system achieved 30% success, the 73% peel completion rate shows robots are starting to master the fine, contact-rich manipulation needed for real world tasks.

39,388 просмотров • 5 месяцев назад

Aubrey de Grey says defeating age-related diseases ultimately means treating aging itself. - We need to make aging the new COVID. - Mark Zuckerberg said the CCI is going to cure all diseases. - The real challenge is curing the biological damage that causes aging. - Scientific breakthroughs often arrive much faster than expected once the right technologies emerge. - AI is already accelerating biology, from protein structure prediction to drug discovery. - Aging is fundamentally a resource allocation problem. - COVID proved that when governments remove bureaucracy and invest at scale, medical progress can happen in record time. - Aging research has been chronically underfunded. If it became a global priority, progress could accelerate dramatically. Aubrey's message is clear: Don't plan to die from aging. Do everything possible to stay healthy long enough to benefit from future breakthroughs.

Aubrey de Grey says defeating age-related diseases ultimately means treating aging itself. - We need to make aging the new COVID. - Mark Zuckerberg said the CCI is going to cure all diseases. - The real challenge is curing the biological damage that causes aging. - Scientific breakthroughs often arrive much faster than expected once the right technologies emerge. - AI is already accelerating biology, from protein structure prediction to drug discovery. - Aging is fundamentally a resource allocation problem. - COVID proved that when governments remove bureaucracy and invest at scale, medical progress can happen in record time. - Aging research has been chronically underfunded. If it became a global priority, progress could accelerate dramatically. Aubrey's message is clear: Don't plan to die from aging. Do everything possible to stay healthy long enough to benefit from future breakthroughs.

17,777 просмотров • 2 месяцев назад

Aging is the root disease. Everything else is a symptom.

Aging is the root disease. Everything else is a symptom.

25,207 просмотров • 6 месяцев назад

wow Homemade robotic hand & wrist doing actual stuff 👀 It features a high-fidelity robotic hand or bionic prosthetic designed for advanced dexterous manipulation. And engineered to mimic natural human motion, capable of precise tasks such as holding a pen or manipulating tools. It uses 3D-printed components and electronic actuators to mimic human hand movements.

wow Homemade robotic hand & wrist doing actual stuff 👀 It features a high-fidelity robotic hand or bionic prosthetic designed for advanced dexterous manipulation. And engineered to mimic natural human motion, capable of precise tasks such as holding a pen or manipulating tools. It uses 3D-printed components and electronic actuators to mimic human hand movements.

15,051 просмотров • 4 месяцев назад