AI & Robotics News and Discussions

[Yuli Ban]

[Ozzie guy]

These deep mind updates are happening fast.

"Abstract
A longstanding goal of the field of AI is a strategy for compiling diverse experience into a highly capable, generalist agent. In the subfields of vision and language, this was largely achieved by scaling up transformer-based models and training them on large, diverse datasets. Motivated by this progress, we investigate whether the same strategy can be used to produce generalist reinforcement learning agents. Specifically, we show that a single transformer-based model -- with a single set of weights -- trained purely offline can play a suite of up to 46 Atari games simultaneously at close-to-human performance. When trained and evaluated appropriately, we find that the same trends observed in language and vision hold, including scaling of performance with model size and rapid adaptation to new games via fine-tuning. We compare several approaches in this multi-game setting, such as online and offline RL methods and behavioral cloning, and find that our Multi-Game Decision Transformer models offer the best scalability and performance. We release the pre-trained models and code to encourage further research in this direction."


https://sites.google.com/view/multi-game-transformers

[Nanotechandmorefuture]

Man definitely gotta look into cloud robotics or anything cool and future tech related to our very near future tech workforce. Its gonna be so drastically different it will be as awesome as it will be daunting at first.

[Ozzie guy]

This Chinese company or organization is working on AGI and seemingly made a breakthrough.





Should AGI related news be posted here or in the singularity thread?

[raklian]

[Yuli Ban]

Interesting! Would be nice to have another humanoid around after ASIMO was retired.

[weatheriscool]

Artificial skin gives robots sense of touch and beyond
https://techxplore.com/news/2022-06-art ... obots.html
by Emily Velasco, California Institute of Technology

We tend to take our sense of touch for granted in everyday settings, but it is vital for our ability to interact with our surroundings. Imagine reaching into the fridge to grab an egg for breakfast. As your fingers touch its shell, you can tell the egg is cold, that its shell is smooth, and how firmly you need to grip it to avoid crushing it. These are abilities that robots, even those directly controlled by humans, can struggle with.

A new artificial skin developed at Caltech can now give robots the ability to sense temperature, pressure, and even toxic chemicals through a simple touch.

This new skin technology is part of a robotic platform that integrates the artificial skin with a robotic arm and sensors that attach to human skin. A machine-learning system that interfaces the two allows the human user to control the robot with their own movements while receiving feedback through their own skin. The multimodal robotic-sensing platform, dubbed M-Bot, was developed in the lab of Wei Gao, Caltech's assistant professor of medical engineering, investigator with Heritage Medical Research Institute, and Ronald and JoAnne Willens Scholar. It aims to give humans more precise control over robots while also protecting the humans from potential hazards.

"Modern robots are playing a more and more important role in security, farming, and manufacturing," Gao says. "Can we give these robots a sense of touch and a sense of temperature? Can we also make them sense chemicals like explosives and nerve agents or biohazards like infectious bacteria and viruses? We're working on this."

[caltrek]

Note that this (see below) describes research at the University of Glasgow, as distinct from research at Caltech as described in the above post.

Percptron: Robots That Feel Pain and AI That Predicts Soccer Players Movements
by Kyle Wiggers & Devin Coldewey
May 31, 2022

Introduction:

(TechCrunch) Research in the field of machine learning and AI, now a key technology in practically every industry and company, is far too voluminous for anyone to read it all. This column, Perceptron (previously Deep Science), aims to collect some of the most relevant recent discoveries and papers — particularly in, but not limited to, artificial intelligence — and explain why they matter.

This week in AI, a team of engineers at the University of Glasgow developed “artificial skin” that can learn to experience and react to simulated pain. Elsewhere, researchers at DeepMind developed a machine learning system that predicts where soccer players will run on a field, while groups from The Chinese University of Hong Kong (CUHK) and Tsinghua University created algorithms that can generate realistic photos — and even videos — of human models.

According to a press release, the Glasgow team’s artificial skin leveraged a new type of processing system based on “synaptic transistors” designed to mimic the brain’s neural pathways. The transistors, made from zinc-oxide nanowires printed onto the surface of a flexible plastic, connected to a skin sensor that registered changes in electrical resistance.

While artificial skin has been attempted before, the team claims that their design differed in that it used a circuit built into the system to act as an “artificial synapse” — reducing input to a spike in voltage. This sped up processing and allowed the team to “teach” the skin how to respond to simulated pain by setting a threshold of input voltage whose frequency varied according to the level of pressure applied to the skin.

The team sees the skin being used in robotics, where it could, for example, prevent a robotic arm from coming into contact with dangerously high temperatures

Read more here: https://techcrunch.com/2022/06/04/perc ... ovements/

[Yuli Ban]

[Yuli Ban]