Lifeboat Foundation

Reservoir computing is already one of the most advanced and most powerful types of artificial intelligence that scientists have at their disposal – and now a new study outlines how to make it up to a million times faster on certain tasks.

That’s an exciting development when it comes to tackling the most complex computational challenges, from predicting the way the weather is going to turn, to modeling the flow of fluids through a particular space.

Such problems are what this type of resource-intensive computing was developed to take on; now, the latest innovations are going to make it even more useful. The team behind this new study is calling it the next generation of reservoir computing.

Black holes are getting weirder by the day. When scientists first confirmed the behemoths existed back in the 1970s, we thought they were pretty simple, inert corpses. Then, famed physicist Stephen Hawking discovered that black holes aren’t exactly black and they actually emit heat. And now, a pair of physicists has realized that the sort-of-dark objects also exert a pressure on their surroundings.

The finding that such simple, non-rotating “black holes have a pressure as well as a temperature is even more exciting given that it was a total surprise,” co-author Xavier Calmet, a professor of physics at the University of Sussex in England, said in a statement.

I predicted that by 2030 you would be able to tell an AI assistant to build brand new books, movies, TV, video games, etc… on demand. That has now arrived, although in its Very Early stages. Look forward to building whatever media you want, or changing existing media into whatever you want.

“OpenAI Codex: Just Say What You Want!”

Continue reading “OpenAI Codex: Just Say What You Want! 🤖” »

Cumrun Vafa is a theoretical physicist at Harvard. Please support this podcast by checking out our sponsors:
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CORRECTIONS:
- I’m currently hiring folks to help me with editing and image overlays so there may be some errors in overlays (as in this episode) as we build up a team. I ask for your patience.
- At 1 hour 27 minute mark, we overlay an image of Brian Greene. We meant to overlay an image of Michael Green, an early pioneer of string theory: https://bit.ly/michael-green-physicist.
- The image overlay of the heliocentric model is incorrect.

Continue reading “Cumrun Vafa: String Theory | Lex Fridman Podcast #204” »

CERN Courier

Jennifer Ngadiuba and Maurizio Pierini describe how ‘unsupervised’ machine learning could keep watch for signs of new physics at the LHC that have not yet been dreamt up by physicists.

In the 1970s, the robust mathematical framework of the Standard Model ℠ replaced data observation as the dominant starting point for scientific inquiry in particle physics. Decades-long physics programmes were put together based on its predictions. Physicists built complex and highly successful experiments at particle colliders, culminating in the discovery of the Higgs boson at the LHC in 2012.

Continue reading “Hunting anomalies with an AI trigger” »

There are eight known planets in the Solar System (ever since Pluto was booted from the club), but for a while, there has been some evidence that there might be one more.

A hypothetical Planet 9 lurking on the outer edge of our Solar System. So far this world has eluded discovery, but a new study has pinned down where it should be. The evidence for Planet 9 comes from its gravitational pull on other bodies. If the planet exists, its gravity will affect the orbits of other planets.

So if something seems to be tugging on a planet, just do a bit of math to find the source. This is how Neptune was discovered when John Couch Adams and Urbain Le Verrier noticed independently that Uranus seemed to be tugged by an unseen planet.

Integrated Information Theory is one of the leading models of consciousness. It aims to describe both the quality and quantity of the conscious experience of a physical system, such as the brain, in a particular state. In this contribution, we propound the mathematical structure of the theory, separating the essentials from auxiliary formal tools. We provide a definition of a generalized IIT which has IIT 3.0 of Tononi et al., as well as the Quantum IIT introduced by Zanardi et al. as special cases. This provides an axiomatic definition of the theory which may serve as the starting point for future formal investigations and as an introduction suitable for researchers with a formal background.

Integrated Information Theory (IIT), developed by Giulio Tononi and collaborators [5, 45–47], has emerged as one of the leading scientific theories of consciousness. At the heart of the latest version of the theory [19, 25 26, 31 40] is an algorithm which, based on the level of integration of the internal functional relationships of a physical system in a given state, aims to determine both the quality and quantity (‘Φ value’) of its conscious experience.

The Bernese theoretical astrophysicist Kevin Heng has achieved a rare feat: On paper, he has derived novel solutions to an old mathematical problem needed to calculate light reflections from planets and moons. Now, data can be interpreted in a simple way to understand planetary atmospheres, for example. The new formulae will likely be incorporated into future textbooks.

For millennia, humanity has observed the changing phases of the Moon. The rise and fall of sunlight reflected off the Moon, as it presents its different faces to us, is known as a “phase curve.” Measuring phase curves of the Moon and Solar System planets is an ancient branch of astronomy that goes back at least a century. The shapes of these phase curves encode information on the surfaces and atmospheres of these celestial bodies. In modern times, astronomers have measured the phase curves of exoplanets using space telescopes such as Hubble, Spitzer, TESS

Launched on April 18 2018, aboard a SpaceX Falcon 9 rocket, NASA’s Transiting Exoplanet Survey Satellite (TESS) is a mission to search nearby stars for undiscovered worlds with a gold of discovering thousands of exoplanets around nearby bright stars.

Three reasons why it falls short.

Isaac Newton invented physics as we know it. And one of the ways he did so was that he formalized the initial condition problem into calculus — the mathematics of change.