Advances in brain-computer interfaces enable paralysed users to feel objects in a realistic way via a robotic limb.
Category: robotics/AI – Page 186
E-quipment highlight: Husqvarna Automower EPOS electric robot lawnmowers
They may look like beefed up Roombas, but the new 535 and AWD 580L EPOS robotic lawn mowers from Husqvarna leverage the brand’s decades of outdoor power products expertise to deliver commercial-grade capability in an innovative package.
Husqvarna dropped the two new commercial robot lawnmowers at the GCSAA Conference and Trade Show in San Diego this weekend with claims that the new 580L EPOS model, specifically, “furthers Husqvarna’s commitment to providing autonomous solutions and revolutionizing turf management for golf courses, sports fields, and facility maintenance.”
If you’re wondering about that “EPOS” acronym, it stands for Exact Positioning Operating System. It’s a Husqvarna-developed, satellite-based positioning system that enables the robot mowers to work within virtual boundaries instead of relying on physical boundary wires like other (significantly less expensive) models.
Q&A: Philosopher David Chalmers on ChatGPT, consciousness, and his days at WashU
On September 20, as part of the TRIADS Speaker Series, philosopher David Chalmers will visit WashU to pose a seemingly straightforward question: “Can ChatGPT Think?”
While Chalmers isn’t in the business of providing a direct “yes” or “no” answer to philosophical quandaries like these, he’s perhaps one of the best-qualified minds to ask the question and unravel its potential implications. Whether in the form of books or TED Talks, Chalmers has grappled with the nature of human consciousness for the better part of three decades. And on a parallel track, he has kept a close eye on the development of artificial intelligence, penning journal articles on the subject and presenting at AI conferences since the early ’90s.
Chalmers, now a New York University Professor of Philosophy and Director of the NYU Center for Mind, Brain, and Consciousness, met via Zoom to discuss the marvels and mysteries of ChatGPT, how he uses philosophical questions to gauge the progress of large language models, and his two years spent at Washington University as a postdoctoral fellow.
An efficient artificial neural network-based optimization techniques for the early prediction of coronary heart disease: comprehensive analysis
Mondal, S., Maity, R. & Nag, A. Sci Rep 15, 4,827 (2025). https://doi.org/10.1038/s41598-025-85765-x.
Academic researchers find a way to train an AI reasoning model for less than $50
A small team of AI researchers from Stanford University and the University of Washington has found a way to train an AI reasoning model for a fraction of the price paid by big corporations that produce widely known products such as ChatGPT. The group has posted a paper on the arXiv preprint server describing their efforts to inexpensively train chatbots and other AI reasoning models.
Corporations such as Google and Microsoft have made clear their intentions to be leaders in the development of chatbots with ever-improving skills. These efforts are notoriously expensive and tend to involve the use of energy-intensive server farms.
More recently, a Chinese company called DeepSeek released an LLM equal in capabilities to those being produced by countries in the West developed at far lower cost. That announcement sent stock prices for many tech companies into a nosedive.
AI model masters new terrain at NASA facility one scoop at a time
Extraterrestrial landers sent to gather samples from the surface of distant moons and planets have limited time and battery power to complete their mission. Aerospace and computer science engineering researchers at The Grainger College of Engineering, University of Illinois Urbana-Champaign trained a model to autonomously assess and scoop quickly, then watched it demonstrate its skill on a robot at a NASA facility.
Aerospace Ph.D. student Pranay Thangeda said they trained their robotic lander arm to collect scooping data on a variety of materials, from sand to rocks, resulting in a database of 6,700 points of knowledge. The two terrains in NASA’s Ocean World Lander Autonomy Testbed at the Jet Propulsion Laboratory were brand new to the model that operated the JPL robotic arm remotely.
The study, “Learning and Autonomy for Extraterrestrial Terrain Sampling: An Experience Report from OWLAT Deployment,” was published in the AIAA Scitech Forum.