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Category: physics – Page 209

#58 Dr. Ben Goertzel — Artificial General Intelligence

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The field of Artificial Intelligence was founded in the mid 1950s with the aim of constructing “thinking machines” — that is to say, computer systems with human-like general intelligence. Think of humanoid robots that not only look but act and think with intelligence equal to and ultimately greater than that of human beings. But in the intervening years, the field has drifted far from its ambitious old-fashioned roots.

Dr. Ben Goertzel is an artificial intelligence researcher, CEO and founder of SingularityNET. A project combining artificial intelligence and blockchain to democratize access to artificial intelligence. Ben seeks to fulfil the original ambitions of the field. Ben graduated with a PhD in Mathematics from Temple University in 1990. Ben’s approach to AGI over many decades now has been inspired by many disciplines, but in particular from human cognitive psychology and computer science perspective. To date Ben’s work has been mostly theoretically-driven. Ben thinks that most of the deep learning approaches to AGI today try to model the brain. They may have a loose analogy to human neuroscience but they have not tried to derive the details of an AGI architecture from an overall conception of what a mind is. Ben thinks that what matters for creating human-level (or greater) intelligence is having the right information processing architecture, not the underlying mechanics via which the architecture is implemented.

Ben thinks that there is a certain set of key cognitive processes and interactions that AGI systems must implement explicitly such as; working and long-term memory, deliberative and reactive processing, perc biological systems tend to be messy, complex and integrative; searching for a single “algorithm of general intelligence” is an inappropriate attempt to project the aesthetics of physics or theoretical computer science into a qualitatively different domain.

Panel: Dr. Tim Scarfe, Dr. Yannic Kilcher, Dr. Keith Duggar.

Pod version: https://anchor.fm/machinelearningstreettalk/episodes/58-Dr–…e-e15p20i.

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A.I. Wars, The Fermi Paradox and Great Filters with David Brin

Why we need AI to compete against each other. Does a Great Filter Stop all Alien Civilizations at some point? Are we Doomed if We Find Life in Our Solar System?

David Brin is a scientist, speaker, technical consultant and world-known author. His novels have been New York Times Bestsellers, winning multiple Hugo, Nebula and other awards.
A 1998 movie, directed by Kevin Costner, was loosely based on his book The Postman.
His Ph.D in Physics from UCSD — followed a masters in optics and an undergraduate degree in astrophysics from Caltech. He was a postdoctoral fellow at the California Space Institute and the Jet Propulsion Laboratory.
Brin serves on advisory committees dealing with subjects as diverse as national defense and homeland security, astronomy and space exploration, SETI and nanotechnology, future/prediction and philanthropy. He has served since 2010 on the council of external advisers for NASA’s Innovative and Advanced Concepts group (NIAC), which supports the most inventive and potentially ground-breaking new endeavors.

https://www.davidbrin.com/books.html.
https://twitter.com/DavidBrin.
https://www.newsweek.com/soon-humanity-wont-alone-universe-opinion-1717446

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Roboticists discover alternative physics

Energy, mass, velocity. These three variables make up Einstein’s iconic equation E=MC2. But how did Einstein know about these concepts in the first place? A precursor step to understanding physics is identifying relevant variables. Without the concept of energy, mass, and velocity, not even Einstein could discover relativity. But can such variables be discovered automatically? Doing so could greatly accelerate scientific discovery.

This is the question that researchers at Columbia Engineering posed to a new AI program. The program was designed to observe through a , then try to search for the minimal set of fundamental variables that fully describe the observed dynamics. The study was published on July 25 in Nature Computational Science.

The researchers began by feeding the system raw video footage of phenomena for which they already knew the answer. For example, they fed a video of a swinging double pendulum known to have exactly four “state variables”—the angle and of each of the two arms. After a few hours of analysis, the AI produced the answer: 4.7.

Physics, Life Sciences, and Dragon Cargo Transfer Top Tuesday’s Task List for Crew

The Expedition 67 crewmembers aboard the International Space Station spent Tuesday predominantly on research, maintenance, and cargo transfer operations.

Research beneficial to humans on Earth and future crews in space is happening around the clock aboard the orbiting laboratory. NASA Flight Engineer Kjell Lindgren used a majority of his day to service samples for the Immunosenescence investigation inside the Life Science Glovebox. Results from this study may one day inform treatments for accelerated aging processes commonly observed in microgravity and contribute to countermeasures for normal aging progression.

Kinetic energy: Newton vs. Einstein | Who’s right?

Using Newtonian physics, physicists have found an expression for the value of kinetic energy, specifically KE = ½ m v^2. Einstein came up with a very different expression, specifically KE = (gamma – 1) m c^2. In this video, Fermilab’s Dr. Don Lincoln shows how these two equations are the same at low energy and how you get from one to the other.

Relativity playlist:

Fermilab physics 101:
https://www.fnal.gov/pub/science/particle-physics-101/index.html.

Fermilab home page:
https://fnal.gov

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