Mind Matters Natural and Artificial Intelligence News and Analysis

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Big data analytics through machine learning, Artificial Intelligence concept background, Using deep learning algorithms for neural network data analysis, Abstract AI 3d illustration

Researchers: Is the Cost of Improving Deep Learning Sustainable?

At IEEE: System designers may have to go back to relying on experts again to tell them what matters, rather than on massive databases

Deep Learning is an approach to computer programming that attempts to mimic the human brain (artificial neural networks) so as to enable systems to cluster data and make accurate predictions (IBM). It’s the dominant AI system today, used to predict how proteins fold and analyse medical scans as well as to beat humans at Go. And yet, four Deep Learning researchers recently wrote in IEEE Spectrum that “The cost of improvement is becoming unsustainable.” As part of their special report, “The Great AI Reckoning,”they explain: While deep learning’s rise may have been meteoric, its future may be bumpy. Like Rosenblatt before them, today’s deep-learning researchers are nearing the frontier of what their tools can achieve. To understand why this will…

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Close-up image of coder typing on computer

The Search for the Universal Algorithm Continues

Why does machine learning always seem to be rounding a corner, only to eventually hit a wall?

DeepMind, a part of Alphabet (i.e., Google), has made many headlines in the past. The biggest was its development of AlphaGo, which used reinforcement learning to beat the number one Go player at the time (2017). DeepMind generalized this into AlphaZero, which is supposedly able to solve any two-player game of perfect information. DeepMind has come back into headlines recently with the attempt to build an AI which can generate any algorithm. While they are starting with map data, the goal is to generalize this and generate any desired algorithm. The search for such a “universal algorithm” has been essentially equivalent to the search for a perpetual motion machine in physics. The allure of both is obvious. In physics, if you…

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Robot eyes closeup

Sure, AI Could Run the World — Except for Its Fundamental Limits

But many of the basic errors, problems, and limitations have no easy solution

We are told that not only will AI take our jobs but it will take our bosses’ jobs and their bosses’ jobs and pretty soon., AI will be running the world… We can see those films on Netflix any night. Science writer and science fiction author Charles Q. Choi offers, in a longish piece at the Institute of Electrical and Electronic Engineers’ online magazine, Spectrum, talking about the real world where “Neural networks can be disastrously brittle, forgetful, and surprisingly bad at math.” AI frequently flubs and it is not clear how to make it flub less. Here are brief notes on three examples of the seven he offers: ➤“Brittle” 97% of AIs could not identify a school bus flipped…

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Robotic man cyborg face representing artificial intelligence 3D rendering

How To Flummox an AI Neural Network

Kids can figure out the same-different distinction. So can ducklings and bees. But top AI can't.

Science writer John Pavlus identifies a key limitation of artificial intelligence: The first episode of Sesame Street in 1969 included a segment called “One of These Things Is Not Like the Other.” Viewers were asked to consider a poster that displayed three 2s and one W, and to decide — while singing along to the game’s eponymous jingle — which symbol didn’t belong. Dozens of episodes of Sesame Street repeated the game, comparing everything from abstract patterns to plates of vegetables. Kids never had to relearn the rules. Understanding the distinction between “same” and “different” was enough. Machines have a much harder time. One of the most powerful classes of artificial intelligence systems, known as convolutional neural networks or CNNs,…

Shot of Corridor in Working Data Center Full of Rack Servers and Supercomputers with Pink Neon Visualization Projection of Data Transmission Through High Speed Internet.
Shot of Corridor in Working Data Center Full of Rack Servers and Supercomputers with Pink Neon Visualization Projection of Data Transmission Through High Speed Internet.

AI Researcher: Stop Calling Everything “Artificial Intelligence”

It’s not really intelligence, says Berkeley’s Michael Jordan, and we risk misunderstanding what these machines can really do for us

Computer scientist Michael I. Jordan, a leading AI researcher, says today’s artificial intelligence systems aren’t actually intelligent and people should stop talking about them as if they were: They are showing human-level competence in low-level pattern recognition skills, but at the cognitive level they are merely imitating human intelligence, not engaging deeply and creatively, says Michael I. Jordan, a leading researcher in AI and machine learning. Jordan is a professor in the department of electrical engineering and computer science, and the department of statistics, at the University of California, Berkeley. Katy Pretz, “Stop Calling Everything AI, Machine-Learning Pioneer Says” at IEEE Spectrum (March 31, 2031) Their principal role, he says, is to “augment human intelligence, via painstaking analysis of large…

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technician standing in front of giant circuitboard, slight zoom effect

For Computers, Smart Is Not the Same Thing as Fast

In response to a reader’s good question …

In a recent article, I argued that computers are not, and never can become smarter. An insightful reader wrote to ask, “What if smartness is defined by speed?” This is a good point. The debate revolves around the definition of “smart.” and if we define “smart” as “fast”, then since computers are certainly getting faster they will necessarily become smarter. Such a definition has intuitive appeal. Think of the world’s best chess player versus a beginner. One of the big distinctions is the chess expert will choose a good move more quickly than a beginner, and in general will play faster than a beginner. As such, play speed demonstrates a certain level of intelligence on the part of the player.…

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Shot of Corridor in Working Data Center Full of Rack Servers and Supercomputers with Pink Neon Visualization Projection of Data Transmission Through High Speed Internet.

Would Super AI Cure Cancer — or Destroy the Earth?

Max Planck Institute computer scientists say that we not only don’t but can’t know

An international team of computer scientists associated with the Max Planck Institute concluded that, given the nature of computers, there is no way of determining what superintelligent AI would do: An international team of computer scientists used theoretical calculations to show that it would be fundamentally impossible to control a super-intelligent AI “A super-intelligent machine that controls the world sounds like science fiction. But there are already machines that perform certain important tasks independently without programmers fully understanding how they learned it. The question therefore arises whether this could at some point become uncontrollable and dangerous for humanity”, says study co-author Manuel Cebrian, Leader of the Digital Mobilization Group at the Center for Humans and Machines, Max Planck Institute for…

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Top view of attractive young woman sleeping well in bed hugging soft white pillow. Teenage girl resting, good night sleep concept. Lady enjoys fresh soft bedding linen and mattress in bedroom

#5 AI hype: AI Could Go Psychotic Due To Lack of Sleep!

Well, that’s what we can hear from Scientific American, if we believe all we read

Our nerds here at the Walter Bradley Center have been discussing the AI hypes of the year. Our director Robert J. Marks, Eric Holloway and Jonathan Bartlett have been talking about 12 overyhyped AI ideas. From AI Dirty Dozen 2020 Part II, here’s #5 AI: can go psychotic due to lack of sleep! Our story begins at 16:03. Here’s a partial transcript. Show Notes and Additional Resources follow, along with a link to the complete transcript. The story started at Scientific American Some types of artificial intelligence could start to hallucinate if they don’t get enough rest, just as humans do… The change will come when (and if) AI systems that mimic living brains are incorporated into the wide range…

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Female doctor consoling senior woman wearing face mask during home visit

#8 in our AI Hype Countdown: AI Is Better Than Doctors!

Sick of paying for health care insurance? Guess what? AI is better ! Or maybe, wait…

Merry Christmas! Our Walter Bradley Center director Robert J. Marks has been interviewing fellow computer nerds (our Brain Trust) Jonathan Bartlett and Eric Holloway about 12 overhyped AI concepts of the year. From AI Dirty Dozen 2020 Part II. Now here’s #8. Sick of paying for health care insurance? Guess what? AI is better! Or maybe, wait… “Is AI really better than physicians at diagnosis?” starts at 01:25 Here’s a partial transcript. Show Notes and Additional Resources follow, along with a link to the complete transcript. Robert J. Marks: We’re told AI is going to replace lawyers and doctors and accountants and all sorts of people. So, let’s look at a case of the physicians. This was a piece on…

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Hairdressing mannequin located on a wooden table.

Erica, Robot Film Star, is Pretty Typical Modern-Day Puppeteering

It may be a good film, to be sure, Jonathan Bartlett stresses, but there is little new AI in there

Yesterday, we looked at Erica the Robot, our #9 technology hype of 2020. While Erica, described as the star of a film, b, to start production in 2021, may be more sophisticated than some, clever animatronics have actually been around for decades (think Muppets… ). So Robert J. Marks and Eric Holloway talked about the question of how much of the Erica puff signifies something really groundbreaking and how much is the usual AI hype. Jonathan Bartlett (pictured) gets back to us with some further thoughts on that very question: The hype around Erica starts with the simple description of her role in the film. Many articles about the film say that Erica was “cast” in the role. However, being…

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Group of head mannequin or dummy in fashion shop.

#9: Erica the Robot Stars in a Film. But Really, Does She?

This is just going to be a fancier Muppets movie, Eric Holloway predicts, with a bit more electronics

Our Walter Bradley Center director Robert J. Marks has been interviewing fellow computer nerds (our Brain Trust) Jonathan Bartlett and Eric Holloway about 12 overhyped AI concepts of the year. Lots of stuff happened and it’s the time of year for fun and entertainment! So here’s #9: Erica the Robot, from Japan, is to star in a film (filming begins in 2021): #9 starts at about 16:58 A partial transcript, Show Notes, and Additional Resources follow. A link to the complete transcript follows the Additional Resources. Robert J. Marks: Okay. We are counting down the Dirty Dozen hyped AI stories of 2020, and we’re at #9. In June 2020 in The Hollywood Reporter, we learned of the robot in the…

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Artificial intelligence and future technologies. Mixed media

#10: Big AI Claims Fail To Work Outside Lab

A recent article in Scientific American makes clear that grand claims are often not followed up with great achievements

As the year winds down, our Walter Bradley Center director Robert J. Marks interviews fellow computer nerds (our Brain Trust) Jonathan Bartlett and Eric Holloway about 12 overhyped AI concepts of the past year. Hey, as we like to say, great stuff happened in AI this year. But well, lots of “stuff” happened too and it’s time to have some fun! So here’s #10: Replication problems tarnish the image of rapid AI progress: #10 starts at about 12:44 A partial transcript and Show Notes follow, along with Additional Resources and the entire transcript. Robert J. Marks: # 10, Will artificial intelligence ever live up to its hype? The subtitle to the article with that name in this month’s Scientific American…

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Retro old beige fridge in loft style wooden kitchen

#11: A Lot of AI Is As Transparent As Your Fridge

A great deal of high tech today is owned by corporations

As the year draws to a close, our Walter Bradley Center director Robert J. Marks interviews fellow computer nerds, members of our Brain Trust, Jonathan Bartlett and Eric Holloway on their picks for over hyped AI of the year. Hey, great stuff happened in AI this year. But well, lots of “stuff” happened too. And it’s time to have some fun! So here’s #11! Corporate types insist that they believe in transparency. But a lot of AI is as transparent as your fridge. Our team has the story: #11 starts at about 9:08 A partial transcript and Show Notes follow. A recent article in top science journal Nature pointed out that AI developments that matter today are often not transparent.…

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I caught a huge fish

#12! AI Is Going To Solve All Our Problems Soon!

In our countdown for the Top Twelve AI Hypes of 2020

First, before we get started: The AI industry has been making real progress. But with real progress comes real hype. That figures. We spent all year covering the real progress. Now that we are all kicking up our feet, we are going to send up some of the hype. We used to only have 10 top hypes but now we have 12. If progress continues at this pace, we might end up with 59 by 2050… Anyway, our Walter Bradley Center director Robert J. Marks interviewed fellow computer nerds, members of our Brain Trust, Jonathan Bartlett and Eric Holloway on their picks last Saturday. And here’s #12! The article itself is actually an admission rather than a hype but let’s…

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close-up view of robot playing chess, selective focus

Bingecast: Robert J. Marks on the Limitations of Artificial Intelligence

Robert J. Marks talks with Larry L. Linenschmidt of the Hill Country Institute about nature and limitations of artificial intelligence from a computer science perspective including the misattribution of creativity and understanding to computers. Other Larry L. Linenschmidt podcasts from the Hill Country Institute are available at HillCountryInstitute.org. We appreciate the permission of the Hill Country Institute to rebroadcast this…

Photo by OLEG PLIASUNOV

Did the Economist Really “Interview” an AI?

Perhaps they have a private definition of what an interview "is"…

Faced with a claim that an AI language tool had given an interview, I took the advice I gave readers yesterday, and followed the links. What a revelation. The Economist story was more dishonest than the examples that Siegel discussed in Scientific American.

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Demographic Change

Can The Machine TELL If You Are Psychotic or Gay?

No, and the hype around what machine learning can do is enough to make old-fashioned tabloids sound dull and respectable

Media often co-operate with researchers’ inflated claims about machine learning’s powers of discovery. An ingenious “creative” approach to accuracy enables the misrepresentation, says data analyst Eric Siegel.

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2019 AI Hype Countdown #8: Media Started Doing Their Job!

Yes, this year, there has been a reassuring trend: Media are offering more critical assessment of off-the-wall AI hype

One factor in the growing sobriety may be that, as AI technology transitions from dreams to reality, the future belongs to leaders who are pragmatic about its abilities and limitations.

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Usb charging port in woman's neck, cyborg woman concept.

2019 AI Hype Countdown #10: Sophia the Robot Still Gives “Interviews”

In other news, few popular media ask critical questions

As a humanoid robot, Sophia certainly represents some impressive engineering. It is sad that the engineering fronts ridiculous claims about the state of AI, using partially scripted interactions as if they were real communication.

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Happy African American guy in VR glasses

Gee-Whiz Tech and AI Reality – Part I

Robert J. Marks talks with Larry L. Linenschmidt of the Hill Country Institute about the nature and limitations of artificial intelligence from a computer science perspective. This is Part 1 of 2 parts. Other Larry L. Linenschmidt podcasts from the Hill Country Institute are available at HillCountryInstitute.org. We appreciate the permission of the Hill Country Institute to rebroadcast this podcast…