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Category: robotics/AI – Page 468

The great mystery of where all the aliens are in our vast Universe contemplates ancient interstellar civilizations building enormous megastructures that rival worlds or even stars in the immensity… and asks why we can’t see these giant alien artifacts.

David Brin on Event Horizon with John Michael Godier: • A.I. Wars, The Fermi Paradox and Grea…
This Week in Space with Rod Pyle: • Alien Megastructures — Isaac Arthur a…

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Episode’s Narration-only version: / the-fermi-paradox-absent-megastructures-na…

Credits:
The Fermi Paradox: Absent Megastructures.
Science \& Futurism with Isaac Arthur.
Episode 352, July 21, 2022
Written, Produced \& Narrated by Isaac Arthur.

Editors:

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Johns Hopkins electrical and computer engineers are pioneering a new approach to creating neural network chips—neuromorphic accelerators that could power energy-efficient, real-time machine intelligence for next-generation embodied systems like autonomous vehicles and robots.

Electrical and computer engineering graduate student Michael Tomlinson and undergraduate Joe Li—both members of the Andreou Lab—used natural language prompts and ChatGPT4 to produce detailed instructions to build a spiking neural network chip: one that operates much like the human brain.

Through step-by-step prompts to ChatGPT4, starting with mimicking a single biological neuron and then linking more to form a network, they generated a full that could be fabricated.

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Gödel’s Incompleteness theorems are two theorems of mathematical logic that demonstrate the inherent limitations of every formal axiomatic system capable of modelling basic arithmetic.

The first incompleteness theorem: No consistent formal system capable of modelling basic arithmetic can be used to prove all truths about arithmetic.

In other words, no matter how complex a system of mathematics is, there will always be some statements about numbers that cannot be proved or disproved within the system.

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Computing has already accelerated scientific discovery. Now scientists say a combination of advanced AI with next-generation cloud computing is turbocharging the pace of discovery to speeds unimaginable just a few years ago.

Microsoft and the Pacific Northwest National Laboratory (PNNL) in Richland, Washington, are collaborating to demonstrate how this acceleration can benefit chemistry and materials science – two scientific fields pivotal to finding energy solutions that the world needs.

Scientists at PNNL are testing a new battery material that was found in a matter of weeks, not years, as part of the collaboration with Microsoft to use to advanced AI and high-performance computing (HPC), a type of cloud-based computing that combines large numbers of computers to solve complex scientific and mathematical tasks.

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