Lifeboat Foundation

Lemoine, an engineer for Google’s responsible AI organization, described the system he has been working on since last fall as sentient, with a perception of, and ability to express thoughts and feelings that was equivalent to a human child.

“If I didn’t know exactly what it was, which is this computer program we built recently, I’d think it was a seven-year-old, eight-year-old kid that happens to know physics,” Lemoine, 41, told the Washington Post.

Continue reading “Google engineer put on leave after saying AI chatbot has become sentient” »

From a zoomed out, distant view, star-forming cloud L483 appears normal. But when a Northwestern University-led team of astrophysicists zoomed in closer and closer, things became weirder and weirder.

As the researchers peered closer into the cloud, they noticed that its magnetic field was curiously twisted. And then—as they examined a newborn star within the cloud—they spotted a hidden star, tucked behind it.

“It’s the star’s sibling, basically,” said Northwestern’s Erin Cox, who led the new study. “We think these stars formed far apart, and one moved closer to the other to form a binary. When the star traveled closer to its sibling, it shifted the dynamics of the cloud to twist its magnetic field.”

It’s said that the clock is always ticking, but there’s a chance that it isn’t. The theory of “presentism” states that the current moment is the only thing that’s real, while “eternalism” is the belief that all existence in time is equally real. Find out if the future is really out there and predictable—just don’t tell us who wins the big game next year.

This video is episode two from the series “Mysteries of Modern Physics: Time”, Presented by Sean Carroll.
Learn more about the physics of time at https://www.wondrium.com/YouTube.

Continue reading “What Is Time? | Professor Sean Carroll explains the theories of Presentism and Eternalism” »

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SAN FRANCISCO — Google engineer Blake Lemoine opened his laptop to the interface for LaMDA, Google’s artificially intelligent chatbot generator, and began to type.

“Hi LaMDA, this is Blake Lemoine …,” he wrote into the chat screen, which looked like a desktop version of Apple’s iMessage, down to the Arctic blue text bubbles. LaMDA, short for Language Model for Dialogue Applications, is Google’s system for building chatbots based on its most advanced large language models, so called because it mimics speech by ingesting trillions of words from the internet.

Continue reading “The Google engineer who thinks the company’s AI has come to life” »

Why the Public Perception of Tesla is TOTALLY wrong:

Shared by Michael Michalchik.

Continue reading “Tesla Fact vs. Fiction: Why the Public Perception is Wrong” »

Scientists who study the cosmos have a favorite philosophy known as the “mediocrity principle,” which, in essence, suggests that there’s really nothing special about Earth, the sun or the Milky Way galaxy compared to the rest of the universe.

Now, new research from CU Boulder adds yet another piece of evidence to the case for mediocrity: Galaxies are, on average, at rest with respect to the early universe. Jeremy Darling, a CU Boulder astrophysics professor, recently published this new cosmological finding in The Astrophysical Journal Letters.

“What this research is telling us is that we have a funny motion, but that funny motion is consistent with everything we know about the universe —there’s nothing special going on here,” said Darling. “We’re not special as a galaxy or as observers.”

Gravitational-wave scientists propose new method to refine the Hubble Constant—the expansion and age of the universeA team of international scientists, led by the Galician Institute of High Energy Physics (IGFAE) and the ARC Centre of Excellence for Gravitational Wave Discovery (OzGrav), has proposed a simple and novel method to bring the accuracy of the Hubble constant measurements down to 2% using a single obse…

Gravitational wave scientists from The University of Western Australia have led the development of a new laser mode sensor with unprecedented precision that will be used to probe the interiors of neutron stars and test fundamental limits of general relativity.

Recently, scientists made groundbreaking detections that allowed them that gravity does not act instantaneously as Newton thought, instead it propagates at the speed of light.

Neil Cornish, a physicist at Montana State University said, “The speed of gravity, like the speed of light, is one of the fundamental constants in the Universe. Until the advent of gravitational wave astronomy, we had no way to directly measure the speed of gravity.”

In the course of recent months, physicists have gained exceptionally fast ground in bouncing the speed of gravity utilizing gravitational wave perceptions. Earlier, the first LIGO detections of gravitational waves constrained the speed of gravity suggests 50% of the speed of light.

(2022). Journal of Experimental & Theoretical Artificial Intelligence. Ahead of Print.

AI has for decades attempted to code commonsense concepts, e.g., in knowledge bases, but struggled to generalise the coded concepts to all the situations a human would naturally generalise them to, and struggled to understand the natural and obvious consequences of what it has been told. This led to brittle systems that did not cope well with situations beyond what their designers envisaged. John McCarthy (1968) said ‘a program has common sense if it automatically deduces for itself a sufficiently wide class of immediate consequences of anything it is told and what it already knows’; that is a problem that has still not been solved. Dreifus (1998) estimated that ‘Common sense is knowing maybe 30 or 50 million things about the world and having them represented so that when something happens, you can make analogies with others’. Minsky presciently noted that common sense would require the capability to make analogical matches between knowledge and events in the world, and furthermore that a special representation of knowledge would be required to facilitate those analogies. We can see the importance of analogies for common sense in the way that basic concepts are borrowed, e.g., the tail of an animal, or the tail of a capital ‘Q’, or the tail-end of a temporally extended event (see also examples of ‘contain’, ‘on’, in Sec. 5.3.1). More than this, for known facts, such as ‘a string can pull but not push an object’, an AI system needs to automatically deduce (by analogy) that a cloth, sheet, or ribbon, can behave analogously to the string. For the fact ‘a stone can break a window’, the system must deduce that any similarly heavy and hard object is likely to break any similarly fragile material. Using the language of Sec. 5.2.1, each of these known facts needs to be treated as a schema,¹⁴ and then applied by analogy to new cases.

Projection is a mechanism that can find analogies (see Sec. 5.3.1) and hence could bridge the gap between models of commonsense concepts (i.e., not the entangled knowledge in word embeddings learnt from language corpora) and text or visual or sensorimotor input. To facilitate this, concepts should be represented by hierarchical compositional models, with higher levels describing relations among elements in the lower-level components (for reasons discussed in Sec. 6.1). There needs to be an explicit symbolic handle on these subcomponents; i.e., they cannot be entangled in a complex network. For visual object recognition, a concept can simply be a set of spatial relations among component features, but higher concepts require a complex model involving multiple types of relations, partial physics theories, and causality. Secs. 5.2 and 5.3 give a hint of what these concepts may look like, but a full example requires a further paper.

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