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Category: robotics/AI – Page 33

To discover new physics, AI may need to ‘unlearn’ the old one

A study in the Journal of Cosmology and Astroparticle Physics explores how a machine-learning strategy known as transfer learning could dramatically reduce the computational cost of searching for new physics beyond the standard cosmological model—while also revealing an unexpected risk: Sometimes AI systems can become too reliant on what they already know.

Artificial intelligence is widely used in cosmology to analyze the universe. But testing theories beyond the standard cosmological model, known as ΛCDM, remains extremely computationally demanding.

Although ΛCDM successfully describes many properties of the universe—from its expansion to the distribution of galaxies—physicists know it is probably incomplete. Recent observations hint that phenomena such as massive neutrinos, modified gravity or evolving dark energy could point toward new physics beyond the current model.

Transcending the Brain? AI, Radical Brain Enhancement and the Nature of Consciousness

Human Rights, Ethics, and Artificial Intelligence: Challenges for the next 70 Years of the Universal Declaration.

Susan schneider, university of connecticut, department of philosophy.

Transcending the Brain? AI, Radical Brain Enhancement and the Nature of Consciousness.
The views expressed in this video are those of the speaker(s) at the time of recording and do not necessarily reflect those of the Carr-Ryan Center for Human Rights or Harvard Kennedy School. These perspectives have been presented to encourage debate on important public policy challenges.

Claude Fable 5 and Claude Mythos 5

While Mythos 5 remains largely unconstrained for restricted government and trusted enterprise partners, Fable 5 is wrapped in a sophisticated safety perimeter. If Fable 5 detects a prompt drifting toward high-risk vectors—like cyberwarfare exploits, advanced biology, or chemical synthesis—it doesn’t just give a generic “I can’t answer that” error. Instead, the query seamlessly falls back to Claude Opus 4.8 (Anthropic’s next-most capable model) to handle the response safely.

Today we’re launching Claude Fable 5: a Mythos-class1 model that we’ve made safe for general use.

Fable 5’s capabilities exceed those of any model we’ve ever made generally available. It is state-of-the-art on nearly all tested benchmarks of AI capability, showing exceptional performance in software engineering, knowledge work, vision, scientific research, and many other areas. The longer and more complex the task, the larger Fable 5’s lead over our other models.

Releasing a model this capable comes with risks. Without safeguards, Fable 5’s capabilities in areas like cybersecurity could be misused to cause serious damage. We’ve therefore launched the model with safeguards that mean queries on some topics will instead receive a response from our next-most-capable model, Claude Opus 4.8. To release the model both safely and quickly, we’ve tuned these safeguards conservatively—they’ll sometimes catch harmless requests, though they trigger, on average, in less than 5% of sessions. With more capable models arriving in the coming months, we’re working to improve our safeguards and reduce false positives as quickly as we can.

Asynchronous AI cuts computing energy by orders of magnitude while learning continuously

As artificial intelligence systems grow larger and more powerful, their energy demands are rising dramatically. But recent research from the University of Massachusetts Amherst published in Nature Communications suggests that advanced AI capabilities may be achievable with dramatically lower energy consumption.

A team led by Hava Siegelmann, Provost Professor in the Manning College of Information and Computer Sciences at UMass Amherst, has developed a novel AI that more closely mirrors key aspects of how the human brain operates. Siegelmann and her lab have focused on two complementary goals: enabling AI systems to learn continuously in real time rather than only during a fixed training phase, and dramatically reducing the energy required for intelligent computation.

“Current AI systems are extraordinarily powerful, but they are also extraordinarily energy-hungry,” said Siegelmann. “Our work shows that it is possible to design AI that remains highly capable while operating much more efficiently.”

Hidden geometry explains why kernel methods separate complex data so well

Are two sets of data genuinely different, or is it because of randomness? This question, known as the two-sample testing problem, becomes notoriously difficult in modern datasets, because they are often high-dimensional, complex, and differences between them can take countless subtle forms.

“Simply put, we don’t know what differences to look for, the possibilities are bewildering,” says Professor Victor Panaretos at EPFL’s Institute of Mathematics.

To solve the problem, mathematicians have developed the so-called “kernel methods,” which have emerged as powerful solutions, widely used in fields such as genomics, finance, and artificial intelligence.

Quantum circuits help AI overcome memory limitations with minimal new parameters

For millions of people, chatbots powered by large language models (LLMs) are now a key feature of everyday life. These AI systems are growing at a rapid pace, but scaling them up is becoming increasingly costly and resource-intensive.

Through a new preprint on the arXiv server, a team led by Borja Aizpurua at Multiverse Computing in San Sebastián, Spain, has found a way to improve the performance of LLMs using quantum computing. Their approach could offer a smarter alternative, rather than simply throwing more hardware at the problem.

NFCShare Android malware spreads via fake banking app updates on GitHub

New variants of the NFCShare Android malware are being distributed as fake updates for legitimate banking apps hosted on GitHub.

The malware has evolved and is now targeting customers of multiple banks and financial institutions across Europe in a phishing campaign aimed at stealing payment card data.

After tricking victims with a fake verification screen to place the cards near the mobile device’s near-field communication (NFC) chip, NFCShare reads the information using Android’s IsoDep interface and EMV commands.

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