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Category: robotics/AI – Page 2,060

Sean Carroll: Quantum Mechanics and the Many-Worlds Interpretation

Sean Carroll is a theoretical physicist at Caltech and Santa Fe Institute specializing in quantum mechanics, arrow of time, cosmology, and gravitation. He is the author of several popular books including his latest on quantum mechanics (Something Deeply Hidden) and is a host of a great podcast called Mindscape. This conversation is part of the Artificial Intelligence podcast.

This is the second time Sean has been on the podcast. You can watch the first time here: https://www.youtube.com/watch?v=l-NJrvyRo0c

INFO:
Podcast website:
https://lexfridman.com/ai
iTunes:
https://apple.co/2lwqZIr
Spotify:
https://spoti.fi/2nEwCF8
RSS:
https://lexfridman.com/category/ai/feed/
Full episodes playlist:

Clips playlist:

EPISODE LINKS:
Something Deeply Hidden: https://amzn.to/2C5h40V
Sean’s twitter: https://twitter.com/seanmcarroll
Sean’s website: https://www.preposterousuniverse.com/
Mindscape podcast: https://www.preposterousuniverse.com/podcast/

OUTLINE:
0:00 — Introduction
1:23 — Capacity of human mind to understand physics.
10:49 — Perception vs reality
12:29 — Conservation of momentum
17:20 — Difference between math and physics.
20:10 — Why is our world so compressable.
22:53 — What would Newton think of quantum mechanics.
25:44 — What is quantum mechanics?
27:54 — What is an atom?
30:34 — What is the wave function?
32:30 — What is quantum entanglement?
35:19 — What is Hilbert space?
37:32 — What is entropy?
39:31 — Infinity
42:43 — Many-worlds interpretation of quantum mechanics.
1:01:13 — Quantum gravity and the emergence of spacetime.
1:08:34 — Our branch of reality in many-worlds interpretation.
1:10:40 — Time travel
1:12:54 — Arrow of time
1:16:18 — What is fundamental in physics.
1:16:58 — Quantum computers
1:17:42 — Experimental validation of many-worlds and emergent spacetime.
1:19:53 — Quantum mechanics and the human mind.
1:21:51 — Mindscape podcast

CONNECT:

Continue reading “Sean Carroll: Quantum Mechanics and the Many-Worlds Interpretation” | >

Michio Kaku: AI Will Help Us Discover Genetic Immortality | AI Podcast Clips

This is a clip from a conversation with Michio Kaku from Oct 2019. New full episodes once or twice a week and 1–2 new clips or a new non-podcast video on all other days. You can watch the full conversation here: https://www.youtube.com/watch?v=kD5yc1LQrpQ
(more links below)

Podcast full episodes playlist:

Podcasts clips playlist:

Podcast website:
https://lexfridman.com/ai

Podcast on Apple Podcasts (iTunes):
https://apple.co/2lwqZIr

Podcast on Spotify:

Continue reading “Michio Kaku: AI Will Help Us Discover Genetic Immortality | AI Podcast Clips” | >

Neural network reconstructs human thoughts from brain waves in real time

Researchers from Russian corporation Neurobotics and the Moscow Institute of Physics and Technology have found a way to visualize a person’s brain activity as actual images mimicking what they observe in real time. This will enable new post-stroke rehabilitation devices controlled by brain signals. The team published its research as a preprint on bioRxiv and posted a video online showing their “mind-reading” system at work.

To develop devices controlled by the brain and methods for cognitive disorder treatment and post-stroke rehabilitation, neurobiologists need to understand how the brain encodes information. A key aspect of this is studying the brain activity of people perceiving visual information, for example, while watching a video.

The existing solutions for extracting observed images from brain signals either use functional MRI or analyze the signals picked up via implants directly from neurons. Both methods have fairly limited applications in clinical practice and everyday life.

Hard as ceramic, tough as steel: Newly discovered connection could help design of nextgen alloys

A new way to calculate the interaction between a metal and its alloying material could speed the hunt for a new material that combines the hardness of ceramic with the resilience of metal.

The discovery, made by engineers at the University of Michigan, identifies two aspects of this interaction that can accurately predict how a particular alloy will behave—and with fewer demanding, from-scratch quantum mechanical calculations.

“Our findings may enable the use of machine learning algorithms for alloy design, potentially accelerating the search for better alloys that could be used in turbine engines and nuclear reactors,” said Liang Qi, assistant professor of materials science and engineering who led the research.