AI-powered DIMON solves complex equations faster, boosting medical diagnostics and engineering simulations.
Category: robotics/AI – Page 29
This article explores why the convergence of these technologies could represent the next quantum leap in artificial intelligence.
Neural network models that are able to make decisions or store memories have long captured scientists’ imaginations. In these models, a hallmark of the computation being performed by the network is the presence of stereotyped sequences of activity, akin to one-way paths. This idea was pioneered by John Hopfield, who was notably co-awarded the 2024 Nobel Prize in Physics. Whether one-way activity paths are used in the brain, however, has been unknown.
A collaborative team of researchers from Carnegie Mellon University and the University of Pittsburgh designed a clever experiment to perform a causal test of this question using a brain-computer interface (BCI). Their findings provide empirical support of one-way activity paths in the brain and the computational principles long hypothesized by neural network models.
Stereotyped sequences of neural population activity, also known as neural dynamics, is believed to underlie numerous brain functions, including motor control, sensory perception, decision making, timing, and memory, among others. The group focused on the brain’s motor system for their work, recently published in Nature Neuroscience, where neural population activity can be used to control a BCI.
In today’s AI news, OpenAI CEO Sam Altman is trying to calm the online hype surrounding his company. On Monday, the tech boss took to X to quell viral rumors that the company had achieved artificial general intelligence. “Twitter hype is out of control again,” he wrote. “We are not gonna deploy AGI next month, nor have we built it.”
In other advancements, Stuttgart, Germany-based Sereact has secured €25mn to advance its embodied AI software that enables robots to carry out tasks they were never trained to do. “With our technology, robots act situationally rather than following rigidly programmed sequences. They adapt to dynamic tasks in real-time, enabling an unprecedented level of autonomy,” said Ralf Gulde, CEO of Sereact (short for “sense, reason, act”).
Then, seven years and seven months ago, Google changed the world with the Transformer architecture, which lies at the heart of generative AI applications like OpenAI’s ChatGPT. Now Google has unveiled a new architecture called Titans, a direct evolution of the Transformer that takes us a step closer to AI that can think like humans.
And, the World Economic Forum Global Risks Report 2025 reveals a world teetering between technological triumph and profound risk. As a structural force, it “has the potential to blur boundaries between technology and humanity” and rapidly introduce novel, unpredictable challenges.
In videos, The next frontier of AI is physical AI. NVIDIA Cosmos—a platform of state-of-the-art generative world foundation models, advanced tokenizers, guardrails, and an accelerated data processing and curation pipeline—accelerates the development of physical-AI-embodied systems such as robots and autonomous vehicles.
The Full Self-Driving version 13.2.2 successfully navigates challenging snowy Canadian roads with impressive performance and minimal driver intervention ## Advanced Navigation in Challenging Conditions.
🚗13.2.2 successfully navigated snowy, slippery roads in Canada without interventions, handling obscured lane lines, vehicles, and signs even when the roadway was difficult to discern.
🌨️The system demonstrated impressive adaptive driving, moving slowly and smoothly with minimal slipping, and never requesting driver takeover despite challenging road conditions. ## Complex Intersection Management.
🛑13.2.2 effectively managed various challenging intersections, including a five-way intersection at an odd angle and a busy roadway with an obscured angle. ## Safety-First Approach.
OpenAI says it trained a new AI model called GPT-4b micro with Retro Biosciences, a longevity science startup trying to extend the human lifespan by 10 years, according to the MIT Technology Review.
Retro, which is backed by Sam Altman, has been working with OpenAI for roughly a year on this research, according to the report. The GPT-4b micro model tries to re-engineer proteins — a specific set called the Yamanaka factors — that can turn human skin cells into young-seeming stem cells. Retro believes these proteins are a promising step toward building human organs and providing supplies of replacement cells.
The model differs slightly from Google’s Nobel prize-winning AlphaFold, which predicts the shape of proteins, but it appears to be OpenAI’s first model that is custom-built for biological research. OpenAI and Retro tell the MIT Technology Review they plan to release research on the model and its outputs.
Two new neural network designs promise to make AI models more adaptable and efficient, potentially changing how artificial intelligence learns and evolves.
Vector Institute’s Remarkable 2024 | Geoffrey Hinton — Will Digital Intelligence Replace Biological Intelligence?
In this profound keynote, Vector co-founder Geoffrey Hinton explores the philosophical implications of artificial intelligence and its potential to surpass human intelligence. Drawing from decades of expertise, Hinton shares his growing concerns about AI’s existential risks while examining fundamental questions about consciousness, understanding, and the nature of intelligence itself.
Geoffrey Hinton is one of the founding fathers of deep learning and artificial neural networks. He was a Vice President and Engineering Fellow at Google until 2023 and is Professor Emeritus at the University of Toronto. In 2024 Hinton was awarded the Nobel Prize in Physics.
Key Topics Covered:
Catch a glimpse of the near future as AI and Quantum Computing transform how we live. Eric Schmidt, decade-long CEO of Google, joins Brian Greene to explore the horizons of innovation, where digital and quantum frontiers collide to spark a new era of discovery.
This program is part of the Big Ideas series, supported by the John Templeton Foundation.
Participants:
Eric Schmidt.
Moderator:
This is supposedly super close now. The waters are muddied, we are possibly already well into Agi, and work is underway for ASI.
Super-agents could make AI a true replacement for human workers.