Bias in AI systems is proving to be a major stumbling block in efforts to more broadly integrate the technology into our society.
A new initiative that will reward researchers for finding any prejudices in AI systems could help solve the problem.
The effort is modeled on the bug bounties that software companies pay to cybersecurity experts who alert them of any potential security flaws in their products.
What is driving the mulitverse theory? Are the multiverse stories only a sticky-plaster solution to the Big Bang theory problem? Leading thinkers Sabine Hossenfelder, Roger Penrose and Michio Kaku debate.
00:00 Introduction.
02:22 Michio Kaku | Multiverse theory has now dominating cosmology; it is unavoidable.
06:03 Sabine Hossenfelder | Believing in the multiverse is the logical equivalent to believing in God.
07:57 Roger Penrose | Universes are sequential and so are not independent worlds.
16:36 Theme 1 | Do scientifc theories need to be testable?
28:45 Theme 2 | Are tales of the multiverse solutions to the Big Bang theory in trouble?
42:49 Theme 3 | Will theories of the universe always be bound by untestable elements?
Multiverses are everywhere. Or at least the theory is. Everyone from physicists Stephen Hawking and Brian Greene to Marvel superheroes have shown their support for the idea. But critics argue that not only is the multiverse improbable, it is also fantasy and fundamentally unscientific as the theory can never be tested — a requirement that has defined science from its outset.
Should we reject the grand claims and leave multiverse theories to the pages of comic books? Are tales of the multiverse really sticking-plaster solutions for Big Bang theory in trouble? Or should we take multiverse theory as seriously as its proponents, and accept that modern science has moved beyond the bounds of experiment and into that of imagination?
Scientists from around the world have reconstructed the laws of gravity, to help get a more precise picture of the universe and its constitution.
The standard model of cosmology is based on General Relativity, which describes gravity as the curving or warping of space and time. While the Einstein equations have been proven to work very well in our solar system, they had not been observationally confirmed to work over the entire universe.
An international team of cosmologists, including scientists from the University of Portsmouth in England, has now been able to test Einstein’s theory of gravity in the outer-reaches of space.
Given a 3D piece of origami, can you flatten it without damaging it? Just by looking at the design, the answer is hard to predict, because each and every fold in the design has to be compatible with flattening.
This is an example of a combinatorial problem. New research led by the UvA Institute of Physics and research institute AMOLF has demonstrated that machine learning algorithms can accurately and efficiently answer these kinds of questions. This is expected to give a boost to the artificial intelligence-assisted design of complex and functional (meta)materials.
In their latest work, published in Physical Review Letters this week, the research team tested how well artificial intelligence (AI) can predict the properties of so-called combinatorial mechanical metamaterials.
Gallery QI — Becoming: An Interactive Music Journey in VR — Opening Night.
November 3rd, 2022 — Atkinson Hall auditorium.
UC San Diego — La Jolla, CA
By Shahrokh Yadegari, John Burnett, Eito Murakami and Louis Pisha.
“Becoming” is the result of a collaborative work that was initiated at the Opera Hack organized by San Diego Opera. It is an operatic VR experience based on a Persian poem by Mowlana Rumi depicting the evolution of human spirit. The audience experiences visual, auditory and tactile impressions which are partly curated and partly generated interactively in response to the player’s actions.
“Becoming” incorporates fluid and reactive graphical material which embodies the process of transformation depicted in the Rumi poem. Worlds seamlessly morph between organic and synthetic environments such as oceans, mountains and cities and are populated by continuously evolving life forms. The music is a union of classical Persian music fused with electronic music where the human voice becomes the beacon of spirit across the different stages of the evolution. The various worlds are constructed by the real-time manipulation of particle systems, flocking algorithms and terrain generation methods—all of which can be touched and influenced by the viewer. Audience members can be connected through the network and haptic feedback technology provides human interaction cues as well as an experiential stimulus.
One small step for a machine… one giant leap for the singularity.
This AI actually improved a key algorithm that makes it run even faster.
In this video I discuss new Deepmind’s AlphaTensor algorithm and why this work is so important for all the fields of Engineering!
“Machine learning provides a way of providing almost human-like intuition to huge data sets. One valuable application is for tasks where it’s difficult to write a specific algorithm to search for something—human faces, for instance, or perhaps ” something strange,” wrote astrophysicist and Director of the Penn State University Extraterrestrial Intelligence Center, Jason Wright in an email to The Daily Galaxy. ” In this case, you can train a machine-learning algorithm to recognize certain things you expect to see in a data set,” Wright explains, ” and ask it for things that don’t fit those expectations, or perhaps that match your expectations of a technosignature.
Crowdsourcing Alien Structures
For instance,’ Wright notes, theoretical physicist Paul Davies has suggested crowdsourcing the task of looking for alien structures or artifacts on the Moon by posting imaging data on a site like Zooniverse and looking for anomalies. Some researchers (led by Daniel Angerhausen) have instead trained machine-learning algorithms to recognize common terrain features, and report back things it doesn’t recognize, essentially automating that task. Sure enough, the algorithm can identify real signs of technology on the Moon—like the Apollo landing sites!
The project, known as DAF-MIT AI Accelerator, selected a pilot out of over 1,400 applicants.
The United States Air Force (DAF) and Massachusetts Institute of Technology (MIT) commissioned their lead AI pilot — a training program that uses artificial intelligence — in October 2022. The project utilizes the expertise at MIT and the Department of Air Force to research the potential of applying AI algorithms to advance the DAF and security.
The military department and the university created an artificial intelligence project called the Department of the Air Force-Massachusetts Institute of Technology Artificial Intelligence Accelerator (DAF-MIT AI Accelerator).
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Why does Facebook constantly change its algorithm? I can never keep up.” “We’re the ones giving them money. Why are they always making it harder on us to get our content to our audience?” You’re not alone if you’ve ever asked either of those questions. For years, marketers and advertisers have been noticing changes to Facebook’s algorithm. Each time, these changes only seemed to hurt their organic reach and ad performance with Facebook marketing. Though the Facebook algorithm isn’t the only thing affecting the reach of your content, it is one of the most important. That’s why all marketers must stay up to date on the changes and updates as Facebook rolls them out.
Find out about changes to the Facebook algorithm, how it works, and take away 19 clever tips you can try today to outsmart the algorithm.
Next, you seem to assume that when I catch a ball, my mind solves equations unconsciously, brining together inertia, gravity, air resistance to calculate my response. You may be right, but I don’t think most neuroscientist agree with you. That’s another computationalist prejudice. Rather than solving equations, my nervous system uses experience and extrapolation through repeated trial and improvement to hone a skill in extrapolating paths; no equations involved. As I say, I could be wrong, it’s an empirical question. But as far as I know, the balance of evidence and theory supports my interpretation.
The meaning of semantics is not just that it means something, but that it can be used to make statements about the world, beyond the formal system used to express that meaning. That, too, is definitional.
Your main argument seems like a really desperate move to sustain the computationalist faith that you assert at the beginning in the face of huge, perhaps insuperable difficulties.
