Extra-condensed knowledge
- This article is golden knowledge about the current state of artificial intelligence and the potential path for radical advancement.
- CONTEXT
- g-f(2)153 The Big Picture of Business Artificial Intelligence (3/3/2021) in a Single “g-f KBP” Chart
- g-f(2)82 THE BIG PICTURE OF THE DIGITAL AGE, MIT TASK FORCE ON THE WORK OF THE FUTURE, AI Today, and the General Intelligence of Work.
- g-f(2)133 THE BIG PICTURE OF THE DIGITAL AGE, Quanta Magazine, Artificial Neural Nets Finally Yield Clues to How Brains Learn.
- Key points
- Neuroscientist and tech entrepreneur Jeff Hawkins claims he’s figured out how intelligence works—and he wants every AI lab in the world to know about it.
- Today’s deep neural networks are loosely inspired by the way interconnected neurons fire in the brain. But loose inspiration is typically as far as it goes.
- Most people in AI don’t care too much about the details, says Jeff Hawkins. He wants to change that.
- Hawkins’s ideas have inspired big names in AI, including Andrew Ng, and drawn accolades from the likes of Richard Dawkins, who wrote an enthusiastic foreword to Hawkins’s new book A Thousand Brains: A New Theory of Intelligence, published March 2.
Genioux knowledge fact condensed as an image
Condensed knowledge
- Jeff Hawkins' ideas could revolutionize AI.
- Why do you think AI is heading in the wrong direction at the moment?
- That’s a complicated question. Hey, I’m not a critic of today’s AI. I think it’s great; it’s useful. I just don’t think it’s intelligent.
- We’re going to need to build machines that work along similar principles. The only examples we have of intelligent systems are biological systems. Why wouldn’t you study that?
- So what is it brains do that’s crucial to intelligence that you think AI needs to do too?
- There are four minimum attributes of intelligence, a kind of baseline.
- How do most AI researchers feel about these ideas?
- The vast majority of AI researchers don’t really embrace the idea that the brain is important.
- Most people aren’t trying to replicate the brain. It’s just whatever works, works. And today’s neural networks are working well enough.
- Most people in AI have very little understanding of neuroscience. It’s not surprising, because it’s really hard.
Category 2: The Big Picture of the Digital Age
[genioux fact produced, deduced or extracted from MIT Technology Review]
Type of essential knowledge of this “genioux fact”: Essential Analyzed Knowledge (EAK).
Type of validity of the "genioux fact".
- Inherited from sources + Supported by the knowledge of one or more experts + Supported by research.
Authors of the genioux fact
References
“We’ll never have true AI without first understanding the brain”, Will Douglas Heaven, March 3, 2021, MIT Technology Review.
ABOUT THE AUTHORS
I am the senior editor for AI at MIT Technology Review, where I cover new research, emerging trends and the people behind them. Previously, I was founding editor at the BBC tech-meets-geopolitics website Future Now and chief technology editor at New Scientist magazine. I have a PhD in computer science from Imperial College London and know what it’s like to work with robots.
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