Alan Turing first proposed a test for machine intelligence in 1950, but now researchers at Google and their partners have created a suite of 204 tests to replace it, covering subjects such as mathematics, linguistics and chess.
It’s the largest, richest, most in-depth, most accurate map of the Milky Way that’s ever been constructed. This sparks joy.
German industrial manufacturer Covestro aims to develop software with QC Ware that would use quantum computing to create more efficient chemical reactions and better materials.
The fastest-growing black hole of the last 9 billion years has been discovered by an international team led by astronomers at The Australian National University (ANU).
The black hole consumes the equivalent of one Earth every second and shines 7,000 times brighter than all the light from our own galaxy, making it visible to well-equipped backyard astronomers.
Lead researcher Dr. Christopher Onken and his co-authors describe it as a “very large, unexpected needle in the haystack.”
The legendary Skunk Works had a hand in developing Tom Cruise’s fastest plane yet.
In Top Gun: Maverick, Captain Pete “Maverick” Mitchell takes his need for speed to a new realm: the hypersonic realm, that is. Thirty-six years after the first film debuted, Mitchell is a test pilot flying the SR-72 “Darkstar” airplane. Although fictional, the SR-72 has a real-world pedigree, with design help for the aircraft and models coming from the same group that is designing the real SR-72: the world-famous Skunk Works, Lockheed Martin’s Advanced Development Programs.
According to Lockheed Martin, the production team behind Top Gun: Maverick contacted the company’s Skunk Works division to assist with the SR-72 concept. The Skunk Works, a name drawn from the cartoon Li’l Abner, is the division of Lockheed Martin that works on classified aircraft programs.
How Does the Brain Learn?
Posted in neuroscience
Summary: A new, open-source model of synaptic plasticity in the neocortex could propel understanding of how learning occurs in the brain.
Source: University of Montreal.
Everyone knows the human brain is extremely complex—but how does it learn, exactly? Well, the answer may be a lot simpler than commonly believed.
LaMDA and the Sentient AI Trap
Posted in robotics/AI, space
“Quite a large gap exists between the current narrative of AI and what it can actually do,” says Giada Pistilli, an ethicist at Hugging Face, a startup focused on language models. “This narrative provokes fear, amazement, and excitement simultaneously, but it is mainly based on lies to sell products and take advantage of the hype.”
The consequence of speculation about sentient AI, she says, is an increased willingness to make claims based on subjective impression instead of scientific rigor and proof. It distracts from “countless ethical and social justice questions” that AI systems pose. While every researcher has the freedom to research what they want, she says, “I just fear that focusing on this subject makes us forget what is happening while looking at the moon.”
What Lemoire experienced is an example of what author and futurist David Brin has called the “robot empathy crisis.” At an AI conference in San Francisco in 2017, Brin predicted that in three to five years, people would claim AI systems were sentient and insist that they had rights. Back then, he thought those appeals would come from a virtual agent that took the appearance of a woman or child to maximize human empathic response, not “some guy at Google,” he says.
Arguments over whether Google’s large language model has a soul distract from the real-world problems that plague artificial intelligence.
They ve got it swimming.
Ghost Robotics makes the robotic dog, and the “tail” system that enables it to swim is called the Nautical Autonomous Unmanned Tail, or NAUT.
Electrons and their behavior pose fascinating questions for quantum physicists, and recent innovations in sources, instruments and facilities allow researchers to potentially access even more of the information encoded in quantum materials.
However, these research innovations are producing unprecedented—and until now, indecipherable—volumes of data.
“The information content in a piece of material can quickly exceed the total information content in the Library of Congress, which is about 20 terabytes,” said Eun-Ah Kim, professor of physics in the College of Arts and Sciences, who is at the forefront of both quantum materials research and harnessing the power of machine learning to analyze data from quantum material experiments.
Imagine if you could repair damaged tissue in your organs. That is what stem cell research is working towards, because stem cells have tremendous potential to produce the cells of organs such as the liver, pancreas and intestine.
For decades, scientists have attempted to mimic the path that stem cells follow in order to form, for example, organs in embryos. However, despite extensive efforts, getting cells to properly develop in the lab has been very difficult. But they may have overlooked an important step and maybe missing another type of stem cells, suggests a new study from the University of Copenhagen.
“Very simply put, a number of recent studies have attempted make a gut from stem cells in a dish. We have found a new way to do this, a way which follows different aspects of what happens in the embryo. Here, we found a new route that the embryo uses, and we describe the intermediate stage that different types of stem cells could use to make the gut and other organs,” says Ph.D. student at Martin Proks, one of the primary authors of the study from Novo Nordisk Foundation Center for Stem Cell Medicine at the University of Copenhagen (reNEW).