Toggle light / dark theme

Scientists develop wearable robotic system to restore hand function

Researchers at the Medical University of Vienna, in collaboration with ETH Zurich, the Technical University of Munich and Medical Faculty Belgrade, have developed a wearable neurorobotic system that combines electrical neurostimulation with hand exoskeletons. In a clinical trial involving 14 patients with hand impairments caused by neurological injury, the technology supported finger mobility, tactile perception and grip control. The results demonstrate the potential of personalised assistive systems for people living with the consequences of spinal cord or brain injury. The study has recently been published in the journal Science Advances.

Hand movements and the sense of touch are essential for everyday activities such as grasping, eating, dressing or personal hygiene. However, after damage to the central nervous system, motor and sensory impairments of the hand often persist. Conventional rehabilitation can achieve improvements, but does not always lead to sufficient restoration of hand function. There is therefore a great need for assistive technologies suitable for everyday use.

A research team led by study director Stanisa Raspopovic from the Center for Medical Physics and Biomedical Engineering at MedUni Vienna has developed the “SensoExo” system for assisting people with hand sensorimotor impairements. It combines a wearable hand exoskeleton with a custom-fitted neurostimulation sleeve. The sleeve stimulates specific nerves and muscles in the forearm through the skin. Sensors on the fingers detect touch and gripping forces and translate this information into electrical stimulation, providing users with tactile feedback. In addition, functional electrical stimulation can assist users open and close their fingers more easily.

New AI math tool could sharpen image editing, drug discovery and simulations

Clarkson University researchers have developed a new mathematical tool that could make artificial intelligence systems more accurate, controllable and useful across applications ranging from image editing to drug discovery.

Clarkson University postdoctoral researcher Zander Blasingame and Chen Liu, professor of electrical and computer engineering, created a new family of numerical solvers called Rex that improves how generative AI models move between random noise and meaningful data. Their work, “Rex: A Family of Reversible Exponential (Stochastic) Runge-Kutta Solvers,” will be presented this summer at the International Conference on Machine Learning (ICML 2026), and an earlier version of the paper is available on the arXiv preprint server.

Diffusion and flow-matching models are the foundation of many modern generative AI systems, including image generators, molecular design tools and scientific simulators. They work by gradually transforming random noise into useful outputs. While that process is effective for creating new content, many important applications require running it in reverse. Existing methods often introduce errors that make it difficult to accurately recover the original information.

Elon Musk UPDATE Neuralink 4.0 Chip Destroy Entire BCI Industry!

Elon Musk UPDATE Neuralink 4.0 Chip introduces Neuralink’s next-generation O1 brain chip developed with Samsung.
This video explores the latest progress of the Neuralink 4.0 chip, including movement restoration, speech recovery, Blindsight vision technology, and how Neuralink patients are using brain-computer interfaces today.
We also examine Samsung’s 4nm partnership, the new R1 surgical robot, and competition from Synchron, Paradromics, and China’s NEO system to understand how the Neuralink 4.0 chip could shape the future of the BCI industry.
If you’re interested in Elon Musk, AI, neuroscience, and future medical technology, this breakdown explains why many experts view the Neuralink 4.0 chip as one of the most important developments in brain-computer interfaces.

🔔 Join our community and hit Subscribe!
https://bit.ly/3i7gILj.
===
#teslacarworld.
#Neuralink.
#Neuralinkupdate.
#BrainComputerInterface.
#Neuralink40Chip.
#BCITechnology

How to Build a Synthethic Mind: Brain Inspired AI Exists Now

Further Reading.
Thumbnail image credit: Adobe Stock.

Brains and algorithms partially converge in natural language processing.
https://www.nature.com/articles/s4200

Strong Prediction: Language Model Surprisal Explains Multiple N400 Effects.
https://pmc.ncbi.nlm.nih.gov/articles

Foundation model of neural activity predicts response to new stimulus types.
https://www.nature.com/articles/s4158

Dendrites endow artificial neural networks with accurate, robust and parameter-efficient learning.
https://www.nature.com/articles/s4146

A Computational Perspective on NeuroAI and Synthetic Biological Intelligence.

Gary Marcus on AI: How do we bridge the mind with the brain?

Gary Marcus is now one of the loudest skeptics of the AI boom. In 2012, almost nobody was listening.

I have the tape.

That year, I sat down with him for Singularity. FM, right after he published a sharp critique of Ray Kurzweil’s theory of mind in The New Yorker. Marcus was already making the argument that would define his career. Intelligence is not just pattern-matching. The mind is a kluge, a messy evolutionary patch job. And scale alone will not get you to real #AI.

More than a decade later, that argument is everywhere. Labs are chasing the hybrid and neurosymbolic approaches he pointed to back then. The field finally caught up to the conversation.

But here is what makes the interview worth revisiting. He also bet big on neuroscience as the road forward, on projects like Blue Brain and Whole Brain Emulation. The breakthroughs came from somewhere else entirely.

So was he the prophet, or just early on some calls and wrong on others? Watch it and decide for yourself.

Gödel, Escher, Bach author Doug Hofstadter on why today’s AI terrifies him

Wonderful book.


Douglas Hofstadter, the Pulitzer Prize–winning author of Gödel, Escher, Bach, voices his concerns about how the current wave of rapid advancements in AI may endanger humanity.

CHAPTERS
0:00 Introduction.
0:34 When I started out, computers were rigid.
1:29 I thought Artificial Intelligence would take hundreds of years.
1:59 I never imagined computers would rival humans so soon.
2:53 It feels like humans are about to be eclipsed.
4:01 I feel diminished, inferior.
5:01 AI pioneer Geoff Hinton may regret part of his life’s work.
6:07 Conclusion: what do you think?

WATCH THE FULL INTERVIEW
• Gödel, Escher, Bach author Doug Hofstadter…

READ \

New technique cools high-performance chips from the inside out

Researchers at the Korea Advanced Institute of Science and Technology (KAIST) have developed a technique to carve microscopic liquid-cooling channels directly inside silicon semiconductor chips.

Interestingly, the computer architecture slashed the energy required for cooling by pumping ordinary, room-temperature water straight through the chip’s internal structure.

“As the performance of AI semiconductors and advanced electronic packaging becomes increasingly limited by heat, we expect this technology to serve as a foundational cooling solution for future high-performance computing systems,” said Professor Sung Jin Kim.

/* */