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Category: robotics/AI – Page 83

3D-printable material can heal the body, build better robots and recover critical minerals

A new type of 3D-printable material developed by researchers at The University of Texas at Austin mimics human tissue’s ability to sort and filter, allowing certain molecules to pass through while keeping others out. This broad functionality means the material can be used in a variety of applications across medicine, water and robotics.

Current methods for building small tissue-like materials don’t scale to sizes that can make applications possible, the researchers say. The team overcame these issues of speed and scalability by jamming billions of tiny water droplets tightly together using simple mixing and centrifuge techniques to form large, tissue-like materials in just a few minutes. Each droplet is separated by a thin membrane, allowing the membranes to link up, similar to cell organization in human tissue.

“Tissues can separate and transport ions and molecules; that’s how our kidneys or intestines work, taking only what they need and leaving the rest behind,” said Manish Kumar, professor in the Cockrell School of Engineering’s Fariborz Maseeh Department of Civil, Architectural and Environmental Engineering and the McKetta Department of Chemical Engineering. This work was recently published in Nature Materials.

AI analyzes surgical technique to improve prostate cancer care

The movements of a surgeon in a procedure—called “surgical gestures”—can be used to predict patient recovery, according to Cedars-Sinai investigators. Their findings, published in npj Digital Medicine, suggest this technology could help surgeons refine their techniques and improve patient outcomes.

The investigators have developed an AI system that analyzes surgeons’ techniques during prostate cancer surgery, helping identify the surgical movements associated with the best patient outcomes while also predicting whether patients are likely to regain sexual function.

The AI system, called Frame-to-Outcome (F2O), analyzes video recorded during the nerve-sparing portion of robot-assisted prostate surgery, when surgeons work to preserve the nerves responsible for sexual function. Rather than relying on experts to manually evaluate each procedure, the system automatically identifies patterns in a surgeon’s movements—called “surgical gestures”—and uses them to predict patient recovery.

Neuromancer: From on X:

The Matrix took its name from a 1984 novel written on a manual typewriter by a man who didn’t own a computer. 42 years later, that novel finally gets its own screen.

William Gibson typed Neuromancer on a 1927 Hermes portable. He coined “cyberspace” before he’d ever logged onto anything. The book swept the Hugo, the Nebula, and the Philip K. Dick award in the same year, the only novel ever to take all three.

Then Hollywood spent four decades strip-mining it while calling it unfilmable. The Wachowskis lifted the matrix, the jacked-in hackers, the AI pulling strings behind a corporate veil. Every razor-girl assassin in sci-fi traces back to Molly. Johnny Mnemonic, an actual Gibson adaptation, flopped so hard in 1995 that studios treated his work as radioactive for a generation.

At least five directors attached and detached over the years. Chris Cunningham in 2000. Vincenzo Natali in 2010. Tim Miller at Fox in 2017. Each attempt died the same death. By the time the technology existed to film Neuromancer, audiences had watched its ideas in a dozen movies that borrowed them first.

The original became unfilmable because it looked like a copy of its own copies.

Now the timing loops back on itself. A story about a rogue AI maneuvering to escape its corporate constraints, written before the web existed, lands in January 2027 as the least speculative thing on television.

Continue reading “Neuromancer: From on X:” | >

How Meta’s AI Models Are Powering the First Wave of Genesis Mission Projects

Lawrence Berkeley National Laboratory — one of the US Department of Energy’s premier research laboratories, known for Nobel Prize-winning work in physics, chemistry, and materials science — operates some of the most advanced scientific facilities on the planet. Among them is the Advanced Light Source (ALS), a football field-sized facility that produces intensely bright beams of X-ray light, allowing researchers to study materials from the atomic and molecular scale all the way to plants. The ALS’s instruments, known as beamlines, generate enormous quantities of data — and as recent facility upgrades have dramatically increased their resolution and speed, the volume of data has exploded beyond what scientists can keep up with.

Terence Tao on AI summary

A curated summary of Terence Tao’s current thinking on AI, with practical guidance and links to source material. Positions are distilled from ~70 Mastodon posts, some sixteen interviews and talks, six long-form essays and lectures, ~55 of his own blog comments, and a direct interview; not everything he has said appears here, by design — omission is editorial. Voice is third person; scope is confined to what is obviously about AI.

Latest: his ICM 2026 public lecture “Mathematics in the age of AI” (July 24, 2026) gathers much of this into one argument — the slides are linked here now, and its content will be folded into this summary once the recording is available.

How this page was made. This summary was compiled and drafted by an AI assistant (Claude) from Terence Tao’s public writing, talks, and interviews, then reviewed and corrected by him; the companion interview was conducted by that assistant, with his answers reproduced verbatim (lightly edited). It is a living document, revised as his views develop. Like the rest of tao-web, it is maintained with AI assistance.

Vernor Vinge: We Can Surpass the Wildest Dreams of Optimism

Fifteen years ago, I spent an hour with the man who gave us the word.

Vernor Vinge coined “technological singularity.” In his 1993 paper for NASA, he put a clock on it: within thirty years we would have the technological means to create superhuman intelligence. Shortly after, he wrote, the human era would end.

That deadline came and went. Vinge died in March 2024, past his own due date, which means he never got to grade his own paper. The rest of us are holding the pencil now.

The title of our conversation was his line, not mine:

We can surpass the wildest dreams of optimism.

From most people, that would be marketing. From a hard #ScienceFiction writer who spent thirty years teaching math and computer science, it was a hypothesis with conditions attached, and he was just as specific about what happens when the conditions are not met.

Continue reading “Vernor Vinge: We Can Surpass the Wildest Dreams of Optimism” | >

The Genesis Mission

The Mission is a national initiative led by the Department of Energy and its 17 national laboratories to build the world’s most powerful scientific platform to accelerate discovery science, strengthen national security, and drive energy innovation. It does so by enabling AI-driven, exascale-powered advances that enhance America’s energy innovation, global competitiveness, and security.

By connecting computing, data, and experimental facilities into a unified system, accelerates discovery and shortens the path from research to real-world impact, strengthening U.S. leadership in energy, security, and advanced technology.

Top environmental fund sees Japan key to AI energy challenge

Asia’s best-performing environmental fund has increased exposure to Japan as it expects the nation’s technology sector to prove increasingly pivotal in solving the artificial intelligence industry’s surging power demands.

The BNP Paribas Green Tigers Fund has returned 34% year-to-date, fueled by bets on Japanese equities that sit at the core of its stock-selection strategy, said Oscar Yang, senior portfolio manager at Impax Asset Management. The $208 million portfolio was the top-performing “dark green” strategy, the EU’s highest sustainability classification, in Asia through June 30, Bloomberg-compiled data show.

“A lot of the Japanese companies are so unique and they’re to some extent almost at a monopoly position,” Yang said. “If you cut Japanese companies’ products out of your supply chain, you just basically can’t operate, especially for leading-edge capacity.”