At MAI we’re building a new class of safer, more capable AI systems we call Humanist Superintelligence: AI that is always aligned, controllable, and in service of humanity.
Category: robotics/AI – Page 90
Artificial General Intelligence: So Close Yet So Far?
Despite its rapid development and widespread adoption, AI is a nascent technology with vast potential for enormous growth in the coming years.
Decades of science fiction make it easy to imagine a future in which AI evolves beyond task-focused point applications to offer broad, human-like intelligence. Although artificial general intelligence (AGI) is theoretical, the road to real AGI is fraught with serious technological and societal challenges. AGI developers face the daunting hurdles of making AGI work effectively, accurately, reliably — and, most of all, safely.
Chip-scale ‘acoustic atom’ controls sound waves to imitate atomic energy levels and advance computing
For every action, there is an equal and opposite reaction. What goes up must come down. Physical laws like these govern all of the natural world—except for the tiny internal components of today’s microprocessors, which operate according to the unique and complicated rules of quantum physics.
As the microprocessors that power computers, medical equipment, sensors, and more continue to shrink in size, engineers face challenges controlling quantum-scale systems. But in a step forward for the technology, researchers at Virginia Tech have developed an “acoustic atom”—a chip-scale device that traps and controls sound waves in ways that mimic the behavior of real atoms. Long term, these advances could influence technologies connected to quantum artificial intelligence (AI), telecommunication, medical imaging, GPS, and more.
The research is published in Physical Review Letters by Linbo Shao, assistant professor in Virginia Tech’s Bradley Department of Electrical and Computer Engineering, along with colleagues at the university’s Center for Power Electronic Systems, Department of Physics, and Center for Quantum Information Science and Engineering and the Oak Ridge National Laboratory.
Microsoft 365 Android Apps Let Any App Steal Account Tokens via Leftover Debug Flag
Debug flag disabled Microsoft 365 Android token checks, letting untrusted apps access accounts; patches issued May 12 to reduce risk
New ‘HTTP/2 Bomb’ DoS attack crashes web servers in under a minute
A new denial-of-service (DoS) attack dubbed HTTP/2 Bomb can be launched from a single machine to take down web servers within seconds.
The technique works on default HTTP/2 configurations of major web servers, including NGINX, Apache HTTP Server, Microsoft IIS, Envoy, and Cloudflare Pingora.
Discovered by OpenAI’s Codex software agent under the guidance of researchers at offensive security firm Calif, HTTP/2 Bomb combines two previously known HTTP/2 DoS methods: the HPACK compression amplification and Slowloris-style resource retention via HTTP/2 flow-control stalling.
Google adds Android protection against AI deepfake scam calls
Google is introducing a new Android security feature that will detect and flag phone calls in which scammers use artificial intelligence to impersonate a user’s personal contacts.
Called “fake call detection,” the feature is rolling out globally this month to Android 12 and later devices, starting with Pixel devices, and will be enabled by default.
Once activated, it works automatically when both a caller and recipient are using Phone by Google: when a contact places a call, their device sends a silent, encrypted confirmation signal to the recipient’s device in real time.
Scientists identify a cell type in the brain that was previously ignored and it may explain why human memory has no known upper limit
The human brain contains roughly 86 billion neurons. That number appears in almost every popular account of memory and intelligence, and it tends to carry an implicit argument: that the scale of human cognition follows from the scale of this cell count. What is less often mentioned is that the brain contains a roughly comparable number of a different cell type entirely, one that researchers have treated, for most of the history of neuroscience, as little more than biological scaffolding.
A paper published on 23 May in the Proceedings of the National Academy of Sciences puts forward a new hypothesis about what those cells, called astrocytes, might actually be doing. The work comes from a team at MIT: lead author Leo Kozachkov, Jean-Jacques Slotine, a professor of mechanical engineering and brain and cognitive sciences, and Dmitry Krotov of the MIT-IBM Watson AI Lab, who is the paper’s senior author. Their claim is not that astrocytes have been misunderstood in any dramatic sense; it is the more careful suggestion that they may be doing computational work that neurons, on their own, cannot account for.
This is a hypothesis supported by a mathematical model. The experimental work needed to test it has not yet been done.
The REAL Reason It’s Already Too Late For Most People
A former Google executive says the West is sleepwalking into irrelevance. Mo Gawdat, the former Chief Business Officer at Google X, explains why every nation that fails to build its own AI infrastructure will become a technology colony of the United States and China, dependent on imported intelligence the way developing nations once depended on imported manufacturing.
Mo draws a direct comparison to how China built its tech independence. When Google operated in China, Russian search engine Yandex was protected by the government through regulation that made it difficult for American companies to dominate. The result was that domestic competitors were forced to exist, and they became competitive. He argues the UK and Europe are doing the opposite: importing every piece of software, every AI model, and every platform from Silicon Valley, sending trillions in licensing fees overseas while building nothing domestically.
Discover:
• Why every nation not building its own AI will become \.
AI misses cancer drug target, revealing why lab validation still matters
Researchers at the Icahn School of Medicine at Mount Sinai have identified a previously hidden druggable site in a cancer-related protein that could open the door toward the development of a new generation of more precise cancer drugs. The finding also reveals important limitations in today’s artificial intelligence tools for drug discovery.
The study, published in the June 2 online issue of the Journal of the American Chemical Society, focused on PKMYT1, a type of protein known as a kinase that helps control how cells grow and divide. Because this process can go wrong in cancer, PKMYT1 has emerged as a promising target for new cancer drugs.
Most experimental drugs designed to block kinases work by targeting a region called the ATP-binding site—the part of the protein that uses the cell’s energy supply to function. But many kinases share nearly identical ATP-binding sites, making it difficult for drugs to distinguish between the desired target and other kinases, which can lead to unwanted side effects.