We show the world’s most powerful AI supercomputers ranked by H100 chip equivalents, led by xAI’s Colossus with 200,000 GPUs.
Category: robotics/AI – Page 43
Team uses AlphaFold AI to redesign geneediting proteins to make them safer
A couple of decades after the discovery of systems that could selectively target DNA, we’re starting to see the first therapies based on gene editing. One challenge these developments have faced is safety. While we can make them pretty specific to the gene we want edited, the human genome is very large, and even rare DNA sequences can appear a couple of times by chance.
As a result, all the original gene-editing systems had known rates of what are called off-target effects, in which they simply edit the wrong sequence. This may be a low-probability event, but edit enough cells—and therapies generally have to edit many—and errors become inevitable.
A lot of effort has gone into finding ways to minimize or eliminate off-target edits. In a recent issue of Nature, researchers described modifying the AI protein-folding software AlphaFold to help identify key areas of gene-editing proteins responsible for off-target effects. Those areas were then modified to reduce the problems.
Why the Next 10 Years May Add 50 to Your Lifespan | Dr. Derya Unutmaz
The next 10 years may add decades to human lifespan by compressing the time it takes to understand, treat, and prevent disease. In this episode, Dr. Derya Unutmaz explains why accelerating AI could transform drug discovery, shorten clinical trials, and push cancer treatment toward increasingly personalized interventions. He also reframes AI not as an existential threat, but as a medical enabler that doctors may soon be ethically obligated to use.
Get weekly, protocol-driven research breakdowns from Dr. Rhonda Patrick to advance healthspan, longevity, brain health, and resilience: https://www.foundmyfitness.com/newsle… 00:00:00 Introduction 00:02:16 Why the next 10 years may add 50 to your lifespan 00:06:25 How AI is transforming drug discovery 00:11:55 Could digital twins shorten clinical trials? 00:14:31 Can AI predict drug safety and efficacy? 00:18:46 Have we already reached AGI? 00:24:28 Why AI may be medicine’s greatest force multiplier 00:30:41 Can AI replicate a scientist’s biological intuition? 00:37:22 Is it malpractice for doctors not to use AI? 00:43:24 What happens when AI monitors disease in real time? 00:46:58 Which AI models should doctors trust? 00:52:34 Claude vs. GPT—does the model matter for diagnosis? 00:56:04 Generalist vs. specialized AI—which works better in medicine? 00:59:30 Why cancer is so hard to cure 01:03:24 Could cancer be curable within a decade? 01:07:35 Can AI design cancer treatments on demand? 01:09:37 How AI could curb overtreatment and side effects 01:12:33 Predicting cancer years before it forms—is it possible? 01:18:55 Why biology could go exponential with AI 01:24:04 Why aging may be easier to prevent than reverse 01:29:56 Can the body be engineered to resist aging? 01:35:13 Can AI model how gene therapy will behave? 01:39:17 What people who reach 110+ reveal about Human 2.0 01:41:27 From Dolly to Yamanaka factors—the case for cellular age reversal 01:46:02 Why full-body rejuvenation is an engineering problem 01:53:49 What happens when AI reasons longer about biology? 01:56:31 The biosecurity dilemma of powerful AI 02:01:17 What should we actually measure to track aging? 02:07:40 How old immune cells distort aging clocks 02:10:28 Why reversing brain aging is uniquely difficult 02:16:55 The ultimate prompt for extending lifespan 02:18:56 What data does a true digital twin need? 02:23:38 How to build a mini digital twin today 02:28:32 How to give AI a long-term memory of your data 02:31:39 Why personal baselines matter for AI advice Derya Unutmaz, M.D. X: https://twitter.com/DeryaTR_ EPISODE LINKS Show notes & transcript: https://www.foundmyfitness.com/episod… PODCAST INFO Apple Podcasts: https://podcasts.apple.com/us/podcast… Spotify: https://open.spotify.com/episode/4BPh… SUPPORT MY MISSION Access more than 130 episodes of my premium podcast (The Aliquot) when you become a FoundMyFitness Premium Member: https://www.foundmyfitness.com/crowds… #ai.
CHAPTERS:
00:00:00 Introduction.
00:02:16 Why the next 10 years may add 50 to your lifespan.
00:06:25 How AI is transforming drug discovery.
00:11:55 Could digital twins shorten clinical trials?
00:14:31 Can AI predict drug safety and efficacy?
00:18:46 Have we already reached AGI?
00:24:28 Why AI may be medicine’s greatest force multiplier.
00:30:41 Can AI replicate a scientist’s biological intuition?
00:37:22 Is it malpractice for doctors not to use AI?
00:43:24 What happens when AI monitors disease in real time?
00:46:58 Which AI models should doctors trust?
00:52:34 Claude vs. GPT—does the model matter for diagnosis?
00:56:04 Generalist vs. specialized AI—which works better in medicine?
00:59:30 Why cancer is so hard to cure.
01:03:24 Could cancer be curable within a decade?
01:07:35 Can AI design cancer treatments on demand?
01:09:37 How AI could curb overtreatment and side effects.
01:12:33 Predicting cancer years before it forms—is it possible?
01:18:55 Why biology could go exponential with AI
01:24:04 Why aging may be easier to prevent than reverse.
01:29:56 Can the body be engineered to resist aging?
01:35:13 Can AI model how gene therapy will behave?
01:39:17 What people who reach 110+ reveal about Human 2.0
01:41:27 From Dolly to Yamanaka factors—the case for cellular age reversal.
01:46:02 Why full-body rejuvenation is an engineering problem.
01:53:49 What happens when AI reasons longer about biology?
01:56:31 The biosecurity dilemma of powerful AI
02:01:17 What should we actually measure to track aging?
02:07:40 How old immune cells distort aging clocks.
02:10:28 Why reversing brain aging is uniquely difficult.
02:16:55 The ultimate prompt for extending lifespan.
02:18:56 What data does a true digital twin need?
02:23:38 How to build a mini digital twin today.
02:28:32 How to give AI a long-term memory of your data.
02:31:39 Why personal baselines matter for AI advice.
Derya Unutmaz, M.D.
X: https://twitter.com/DeryaTR_
EPISODE LINKS
Show notes & transcript: https://www.foundmyfitness.com/episod…
Drug discovery Is changing. Drug development must change too
💬 Artificial intelligence and big data are flooding discovery pipelines with high-potential drug candidates, but this rapid innovation has created a new challenge. Simply put, our capability to design miracle molecules is vastly outstripping our technology to mass-manufacture them safely for the global public. Moving drug making from the scale of lab flasks to commercial bioreactors introduces non-linear biological and engineering shifts that can undermine tasks like purification.
⚡In this New Scientist CoLab podcast, experts from global life sciences leader Cytiva explain the hidden, high-stakes science of purification that is required to close the gap between drug discovery and the pharmacy shelf.
Charlie Stross: The World is Complicated. Elegant Narratives Explaining Everything Are Wrong!
Fifteen years ago, I interviewed Charlie Stross about a short story called “Lobsters.”
This spring, a thousand people queued outside Tencent’s Shenzhen headquarters to raise one.
June 2011, Singularity 1 on 1. Back then, “singularity” was a word most people filed under astrophysics, not #AI. Charlie’s 2001 story “Lobsters,” which grew into Accelerando, was one of the sharpest early maps of what happens when intelligence stops being exclusively biological. Uploaded minds. Post-scarcity economics. Legal personhood for software. An economy run by optimization processes no human fully follows.
He wrote it six years before the iPhone.
Now look at 2026. OpenClaw, the open source agent built by Austrian developer Peter Steinberger, now at OpenAI, became the fastest-growing project in GitHub history. In China, installing it is called 养龙虾, “raising lobsters,” after the red logo. Shenzhen, Wuxi and Changshu rushed out subsidy packages. Retirees, schoolkids and office workers lined up for help. A grey market of house-call technicians appeared within days.
Any connection to Charlie’s story? None. The logo is a claw pun on Claude.
AI & Quantum Computing Are Redefining Research & Development, Manufacturing & Technological Exploration
Chuck Brooks is the president of Brooks Consulting International and one of Executive Mosaic’s GovCon Experts.
The convergence of AI and quantum tech is creating a new frontier of innovation and risk.
This trend is evident from the White House’s FY27 research and development goals that put Artificial intelligence and quantum technologies at the center of the national agenda.
A new ‘golden age’ of mathematics may be dawning, thanks to AI and human ingenuity
In May 2026, OpenAI released a new math result that sent shock waves throughout the world of mathematical research. A major unsolved problem called the “unit distance conjecture” had just been resolved by generative AI.
Since then, there has been a steady drumbeat of new results that either partially or completely leverage artificial intelligence to solve research-level mathematics problems. However, most new math results published in any given month are still generated by humans.
So where is this going? How good, and how quickly, will AI capabilities grow? Will most mathematical research be predominantly artificial intelligence? Or, as some mathematicians suggest, will AI combine with human ingenuity and other computer tools to create a golden age of mathematics?
Machine learning narrows search for additional particles in the Higgs boson family
What if the Higgs boson found in 2012 is not alone but is the only sibling we have encountered so far? Scientists at CERN discovered the particle that year, and it was a major discovery because it explained how other particles acquire mass. For a long time, scientists thought this was the final piece of the puzzle.
They have a framework called the Standard Model that describes the smallest particles in everything we see. This includes electrons in atoms and light particles called photons. However, this framework does not explain everything. It does not tell us about dark matter or why the universe has so much more matter than antimatter. It is like having a map that shows only half the world.
The discovery of the Higgs boson created new questions. Many physicists started wondering whether the Higgs we found is the only one of its kind. They began to ask whether there is a larger family of these particles hiding in the universe. If we find more members of this family, we might finally understand the parts of nature that the current framework misses.