Lex Fridman, a Postdoctoral Associate at the MIT AgeLab, had a conversation with Kai-Fu Lee on Chinese soul, Difference between cultures of AI engineering, Role of data in near-term impact of AI, Impact of AI on jobs, Facing mortality and other issues.
Lex Fridman, had a conversation with Kai-Fu Lee on Chinese soul, Difference between cultures of AI engineering, Role of data in near-term impact of AI, Impact of AI on jobs, Facing mortality.
“We’ve been keeping a very low profile, mostly intentionally,” said Doug Lenat, President and CEO of Cycorp. “No outside investments, no debts. We don’t write very many articles or go to conferences, but for the first time, we’re close to having this be applicable enough that we want to talk to you.”
IBM’s Watson and Apple’s Siri stirred up a hunger and awareness throughout the United States for something like a Star Trek computer that really worked — an artificially intelligent system that could receive instructions in plain, spoken language, make the appropriate inferences, and carry out its instructions without needing to have millions and millions of subroutines hard-coded into it.
As we’ve established, that stuff is very hard. But Cycorp’s goal is to codify general human knowledge and common sense so that computers might make use of it.
Robots are making their way into New York City’s restaurants.
A growing number of dining spots throughout town are using machines to prepare all manner of food and drink, in many cases replacing the employees who would normally handle the task. Think gizmos that can do everything from slice a sushi roll into eight uniform pieces to mix the perfect happy-hour cocktail.
I listened to the first hour. it takes time… and the right frame of mind, but it’s worth it.
Jeff Hawkins is the founder of Redwood Center for Theoretical Neuroscience in 2002 and Numenta in 2005. In his 2004 book titled On Intelligence, and in his research before and after, he and his team have worked to reverse-engineer the neocortex and propose artificial intelligence architectures, approaches, and ideas that are inspired by the human brain. These ideas include Hierarchical Temporal Memory (HTM) from 2004 and The Thousand Brains Theory of Intelligence from 2017. This conversation is part of the Artificial Intelligence podcast. Audio podcast version is available on https://lexfridman.com/ai/
INFO:
Podcast website: https://lexfridman.com/ai
Course website: https://deeplearning.mit.edu
YouTube Playlist: http://bit.ly/2EcbaKf
EPISODE LINKS:
Thousand brain theory: http://bit.ly/2Xl83he
On Intelligence: https://amzn.to/322Qly4
Numenta: https://numenta.com/
OUTLINE:
0:00 — Introduction
1:28 — Understanding how the human brain works.
5:44 — Parts of the brain
11:05 — How much do we understand?
14:20 — Nature of time in the brain
20:22 — Building a theory of intelligence.
34:29 — Thousand brains theory of intelligence.
40:06 — Ensembles and sensor fusion
44:00 — Concepts and language
45:38 — Memory palace and method of loci.
50:20 — Reference frames
57:33 — Open problems
59:00 — Context
1:01:50 — Introspective thinking about the brain.
1:04:19 — Deep learning
1:23:09 — Benchmarks
1:27:07 — Brain learning process
1:34:33 — How far are we from solving intelligence.
1:38:37 — Possibility of AI winter
1:39:58 — Consciousness and intelligence.
1:49:16 — Mortality
1:53:49 — Will understanding intelligence make us happy?
1:55:19 — Existential threats of AI
2:01:45 — Super-human intelligence and our future.
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Kenneth Cukier reviews “Possible Minds: Twenty-Five Ways of Looking at AI,” a collection of essays edited by John Brockman.
China is the world leader in facial recognition technology. But is the state using it to violate the human rights of its citizens?
Squirrels mislabeled as sea lions and dragonflies confused with manhole covers are challenging algorithms to be more resilient to attacks.
The rules about what makes a good magnet may not be as rigid as scientists thought. Using a mixture containing magnetic nanoparticles, researchers have now created liquid droplets that behave like tiny bar magnets.
Magnets that generate persistent magnetic fields typically are composed of solids like iron, where the magnetic poles of densely packed atoms are all locked in the same direction (SN: 2/17/18, p. 18). While some liquids containing magnetic particles can become magnetized when placed in a magnetic field, the magnetic orientations of those free-floating particles tend to get jumbled when the field goes away — causing the liquid to lose its magnetism.
Now, adding certain polymers to their recipe has allowed researchers to concoct permanently magnetized liquid droplets. These tiny, moldable magnets, described in the July 19 Science, could be used to build soft robots or capsules that can be magnetically steered through the body to deliver drugs to specific cells.
