Lifeboat Foundation

I watched United Nations delegates debate AI-based weapons that can fire without human initiation. Humans cannot be taken out of that decision-making.

By Kate Graham-Shaw

Imagine a weapon with no human deciding when to launch or pull its trigger. Imagine a weapon programmed by humans to recognize human targets, but then left to scan its internal data bank to decide whether a set of physical characteristics meant a person was friend or foe. When humans make mistakes, and fire weapons at the wrong targets, the outcry can be deafening, and the punishment can be severe. But how would we react, and who would we hold responsible if a computer programmed to control weapons made that fateful decision to fire, and it was wrong?

The authors identify reusable ‘dynamical motifs’ in artificial neural networks. These motifs enable flexible recombination of previously learned capabilities, promoting modular, compositional computation and rapid transfer learning. This discovery sheds light on the fundamental building blocks of intelligent behavior.

Researchers at the University of Tokyo developed a method to integrate engineered skin tissue with humanoid robots, enhancing mobility, self-healing, sensors, and realism.

Google’s DeepMind has unveiled a groundbreaking AI training method called JEST, which significantly reduces energy consumption and training time. Meanwhile, Chinese tech giants like SenseTime and Alibaba are showcasing their own powerful AI models, claiming to outperform even OpenAI’s GPT-4 in certain areas. The race for AI dominance is heating up, with advancements in efficient training and multimodal learning taking center stage.

#google #ai

AI-powered robots are popping up across Silicon Valley. If some industry experts are right, they could help solve a global labor shortage.

Companies like Tesla, Amazon, Microsoft and Nvidia have plowed billions of dollars into what are known as “humanoid” robots. These machines typically stand on two legs, and are designed to perform tasks meant for people.

An homage riff on AI+mind+evolution in honor of Daniel Dennett.

“Machine-Learning Assisted Directed Evolution of Viral Vectors and Microbial Opsins for Minimally Invasive Neuroscience.” AI-4-Science Workshop, October 25, 2019 at Bechtel Residence Dining Hall, Caltech. Learn more about: — AI-4-science: https://www.ist.caltech.edu/ai4science/ — Events: https://www.ist.caltech.edu/events/ Produced in association with Caltech Academic Media Technologies. ©2019 California Institute of Technology.

Researchers from the Smart and Wireless Applications and Technologies Group (SWAT-UGR) have conducted two scientific studies aimed at answering a common question: understanding how electromagnetic waves propagate in the medium.

The increase in network speed opens the door to new possibilities, such as robotic surgery or virtual reality services.

A team of UGR researchers has examined the propagation of electromagnetic waves with the goal of enhancing the deployment of 5G and 6G networks. Additionally, the study results contribute to the development of Industry 4.0, which seeks to automate processes in factories using wireless technologies.

Researchers have developed a pH-responsive nanorobot system that changes confirmation in the tumor microenvironment to selectively kill cancer cells in mice.

Researchers at the Karolinska Institutet (Stockholm, Sweden) have recently developed a nanorobot system capable of killing cancer cells in mice. This system works by activating at lower pH, such as within the tumor microenvironment. It is hoped that this could serve as a proof-of-concept for similar stimulus-responsive nanorobotic approaches and introduce a new range of effective cancer therapeutics.

Certain membrane proteins capable of inducing apoptosis, a type of cell death, appear on the surface of both healthy and cancer cells. These proteins, often called death receptors, join and activate when in close proximity to each other. This closeness is induced by external factors binding to the cell surface.