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1:42 Are we on the wrong train to AGI?
4:20 Marvin Minsky and AI generalization problem.
11:57 Defining intelligence in AI
17:17 Is AI masquerading as a trendy statistical analysis tool?
23:35 AI systems lack our most basic intuitions.
27:38 The public not wanting to face Reality.
29:36 Equipping AI with Kant’s categories of the mind (Time, Space, Causality)
33:40 Neural nets VS traditional tools.
34:50 Causality in AI
37:14 Lack of interdisciplinary learning.
45:54 How can we achieve human level of understanding in AI?
49:21 More limitations.
59:35 Motivation in inanimate systems.
1:01:31 Lack of body and transcendent consciousness.
1:05:55 What interdisciplinary learning would you encourage?
1:06:49 Book recommendations.

Gary Marcus is CEO and Founder of Robust AI, well-known machine learning scientist and entrepreneur, author, and Professor Emeritus at New York State University.

Dr. Marcus attended Hampshire College, where he designed his own major, cognitive science, working on human reasoning. He continued on to graduate school at Massachusetts Institute of Technology, where his advisor was the experimental psychologist Steven Pinker. He received his Ph.D. in 1993.

His books include The Algebraic Mind: Integrating Connectionism and Cognitive Science, The Birth of the Mind: How a Tiny Number of Genes Creates the Complexities of Human Thought, Kluge: The Haphazard Construction of the Human Mind, a New York Times Editors’ Choice, and Guitar Zero, which appeared on the New York Times Bestseller list. He edited The Norton Psychology Reader, and was co-editor with Jeremy Freeman of The Future of the Brain: Essays by the World’s Leading Neuroscientist, which included Nobel Laureates May-Britt Moser and Edvard Moser. Together with Ernie Davis, he authored Rebooting AI and is well known to deconstruct myths of the AI community.

A Long March 2F rocket launched the Shenzhou 13 spacecraft carrying astronauts Zhai Zhigang (commander), Wang Yaping and Ye Guangfu to the Tianhe core module of China’s new space station on Oct. 15 2021 at 12:23pm ET (00:23 Oct. 16 Beijing time). Full Story: https://www.space.com/china-launches-shenzhou-13-astronauts-to-space-station.

Broadcast feed from the Jiuquan Satellite Launch Center in the Gobi Desert courtesy China Central Television (CCTV)

BEIJING, Oct 18 (Reuters) — China tested a space vehicle in July, not a nuclear-capable hypersonic missile as reported by the Financial Times, the Chinese foreign ministry said on Monday.

Quoting five people familiar with the matter, the Financial Times reported on Saturday that China had tested a nuclear-capable hypersonic missile that flew through space, circling the globe before cruising down toward its target, which it missed by about two dozen miles. read more. The paper said the feat had “caught U.S. intelligence by surprise”.

“It was not a missile, it was a space vehicle,” ministry spokesman Zhao Lijian told a regular press briefing in Beijing when asked about the report, adding it had been a “routine test” for the purpose of testing technology to reuse the vehicle.

Neural Implant Podcast w/ Ladan Jiracek: https://open.spotify.com/show/7qzl8f0yllPaYlBmW9CX3u?si=aXiWglMkR8Wkw8YGLD81nQ

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Neura Pod is a series covering topics related to Neuralink, Inc. Topics such as brain-machine interfaces, brain injuries, and artificial intelligence will be explored. Host Ryan Tanaka synthesizes informationopinions, and conducts interviews to easily learn about Neuralink and its future.

Most people aren’t aware of what the company does, or how it does it. If you know other people who are curious about what Neuralink is doing, this is a nice summary episode to share. Tesla, SpaceX, and the Boring Company are going to have to get used to their newest sibling. Neuralink is going to change how humans think, act, learn, and share information.

Convolutional neural networks running on quantum computers have generated significant buzz for their potential to analyze quantum data better than classical computers can. While a fundamental solvability problem known as “barren plateaus” has limited the application of these neural networks for large data sets, new research overcomes that Achilles heel with a rigorous proof that guarantees scalability.

“The way you construct a quantum neural can lead to a barren plateau—or not,” said Marco Cerezo, co-author of the paper titled “Absence of Barren Plateaus in Quantum Convolutional Neural Networks,” published today by a Los Alamos National Laboratory team in Physical Review X. Cerezo is a physicist specializing in , , and at Los Alamos. “We proved the absence of barren plateaus for a special type of quantum neural network. Our work provides trainability guarantees for this architecture, meaning that one can generically train its parameters.”

As an (AI) methodology, quantum are inspired by the visual cortex. As such, they involve a series of convolutional layers, or filters, interleaved with pooling layers that reduce the dimension of the data while keeping important features of a data set.

Massive asteroids — including one the size of the Empire State Building — are predicted to make “close” encounters with Earth in the coming weeks, with one set to whiz by as early as Wednesday night.

The space rock “2004 UE,” which at 1,246 feet is only a few feet shorter than the Midtown skyscraper, will be 2.6 million miles away on Nov. 13.

Of the asteroids headed our way, “1996 VB3” — which has a diameter of about 750 feet — is expected to come closest to Earth, at a distance of only 2.1 million miles, according to NASA’s Center for Near-Earth Objects.