What can past bottlenecks and imagined technologies tell us about the future of AI?
Category: robotics/AI – Page 97
Microsoft expects more Windows security updates from AI-discovered flaws
Microsoft says Windows users should expect to see an increase in security updates as the company increasingly relies on artificial intelligence to discover vulnerabilities in its codebase.
In a blog post published today, Microsoft said advances in AI have significantly accelerated vulnerability discovery, allowing engineers to identify more security issues before they can be exploited in zero-day attacks.
“The pace of vulnerability discovery is changing with advances in AI making it possible to find more issues, faster, across more code, with new mechanisms that can accelerate both discovery and analysis,” Microsoft said.
Plain language AI workflow tool could cut cloud energy use and costs dramatically
Agentic workflows are artificial intelligence-powered software systems that chain together multiple models and external tools to tackle complicated tasks, like analyzing a video and answering questions about it. But the way these highly fragmented systems are designed and deployed often causes inefficiencies that can lead to wasted computation, energy and cost.
To improve efficiency, researchers from MIT and Microsoft developed an intelligent system that streamlines the process of designing agentic workflows and automatically optimizes how those workflows are implemented. With this new method, a developer can describe what they want the agentic workflow to do in plain language, without needing to specify all the details of their application in advance.
The system automatically figures out the best models and tools to use, as well as the ideal hardware configuration and computational resource allocation when the workflow is executed by a cloud provider. It adjusts those configurations on the fly based on each user’s priorities, such as minimizing costs or maximizing speed.
New physics-based machine-learning method speeds search for 2D quantum materials
Researchers at The University of Manchester have developed a new computational approach to help identify two-dimensional materials that may host unusual quantum behavior. The work, published in Science Advances, focuses on materials with “flat bands,” electronic states where electrons have very little kinetic energy. In these materials, interactions between electrons can become much more important, creating conditions linked to phenomena such as magnetism, unconventional superconductivity and topological electronic behavior.
Finding real materials with flat bands from large datasets is difficult. Conventional searches often rely on density functional theory calculations, which can reveal a material’s electronic structure but are time-consuming when applied across thousands of possible candidates.
The Manchester team took a different route. They developed a physics-informed scoring system that captures two signatures of flat-band behavior, low band dispersion and a strong peak in the density of states, then trained a model to estimate that score directly from atomic structure.
The silent hormone: How adrenal tumors quietly raise cardiovascular risk over time
A major new study, published in The Lancet Diabetes & Endocrinology, has shown that cortisol levels in patients with adrenal tumors are far less stable than previously assumed. The study also found that those in whom cortisol remains persistently elevated carry a significantly greater risk of worsening high blood pressure and a heavier overall cardiometabolic burden.
Cortisol, often referred to as the “stress hormone,” is a steroid hormone produced by the adrenal glands that acts as a master regulator of metabolism, blood pressure and immune function. When benign tumors form on the adrenal glands (found incidentally in 3%–7% of adults), they can cause the body to produce cortisol independently of normal regulatory controls, a condition known as mild autonomous cortisol secretion (MACS).
Until now, it was unclear how cortisol levels in these patients change over time, and what that means for their long-term health.
Small aquatic robots that assemble into reconfigurable structures on the water
Most people think of the waterfront as the edge of the city. A team of MIT researchers sees it as a dynamic, Lego-like construction site. Their new system, called “FloatForm,” is a swarm of small square robotic boats that assemble themselves into larger structures on the water, break apart and reassemble into something new, all with minimal human direction.
Each robot, about the size of a dinner plate at 21 centimeters square (8.3 inches square), is a self-contained vessel with its own thrusters, sensors and magnetic latches. Together, they hint at a future in which floating infrastructure could become more adaptive: a temporary platform after an emergency, a market on a canal or a stage that appears for a festival and dissolves when the crowd goes home.
“Our FloatForm project envisions a future where the waterfront becomes a programmable extension of the city, where autonomous boats can self-organize into bridges, platforms, and other useful structures on demand,” says Daniela Rus, the Panasonic Professor of Electrical Engineering and Computer Science at MIT and director of MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL). “This kind of distributed robotics opens new possibilities for mobility, emergency response, public space, and infrastructure on water.”
Useful Local Open Source AI Models
I’ve been playing with local AI models; AI you can run on your own computer for years now. Each year it gets better and better. Similar to the online cloud-based frontier models (you know them). I won’t go into all the advantages of running open source models on your own local hardware, the reasons are somewhat obvious.
Beyond Agentic AI: The Emergence Of Cognitive AI Ecosystems
In the next decade, AI will likely undergo more significant changes than only becoming more independent; it will also grow more cognitive. AI systems will act as interconnected ecosystems that are capable of contextual awareness, cooperative reasoning, ongoing learning, and adaptive decision-making in almost every facet of society, rather than isolated applications.
Large language models of today are remarkable due to their ability to produce and anticipate information. Persistent memory, multimodal perception, long-term planning, causal reasoning, and self-directed learning within strictly regulated bounds will probably be characteristics of the AI of 2036. Similar to biological neural networks, millions of specialized AI agents will work together to create dynamic intelligence fabrics that continuously optimize national defense, manufacturing, transportation, financial markets, healthcare delivery, and energy grids.
The line between workforce and software will become increasingly hazy. Hundreds of thousands of AI agents working continuously alongside human employees may be employed by organizations as digital workforces. A customized constellation of AI advisers, researchers, legal assistants, financial analysts, engineers, and cybersecurity specialists working around the clock could be present for every knowledge worker. This shift signifies the emergence of an entirely new digital labor force in addition to automation.
Scientists Used Post-Mortem Brain Tissue to Control a Robot
Further reading.
Thumbnail image credit: Paper cited in video.
Unsupervised sensory-motor associative learning by human brain explant in-a-dish enables movement imitation by robot.
https://www.researchsquare.com/articl…
The lab.
Not alive. but not dea: disembodied human brains used for drug testing.
https://www.science.org/content/artic…
#science #brain #technology #news #explained