Mind Matters Natural and Artificial Intelligence News and Analysis

CategoryMachine Learning

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Concept creative idea and innovation. Hand picked wooden cube block with head human symbol and light bulb icon

Computer Prof: We Can’t Give Machines Understanding of the World

Not now, anyway. Melanie Mitchell of the Santa Fe Institute finds that ever larger computers are learning to sound more sophisticated but have no intrinsic knowledge

Last December, computer science prof Melanie Mitchell, author of Artificial Intelligence: A Guide for Thinking Humans (2019), let us in on a little-publicized fact: Despite the greatly increased capacity of the vast new neural networks. they are not closer to actually understanding what they read: The crux of the problem, in my view, is that understanding language requires understanding the world, and a machine exposed only to language cannot gain such an understanding. Consider what it means to understand “The sports car passed the mail truck because it was going slower.” You need to know what sports cars and mail trucks are, that cars can “pass” one another, and, at an even more basic level, that vehicles are objects that…

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Alma Mater statue near the Columbia University library.

Should You Choose a College Based on Well-Known Rankings?

What goes into those rankings? Big Data has enabled newer ranking systems that may tell you more of what you need to know

Yesterday, philosopher of science Bruce Gordon interviewed physicist Jed Macosko and law professor Jeff Stake about how to read college rankings. What, exactly, lies behind those numbers, especially the ones from the iconic U.S. News & World Report? Are they something you can bank on or something you should know more about first? Macosko and Stake think you should know more. As Gordon’s introduction puts it, rankings are big business and can lead to outright fraud: A recent stark example of the financial implications of college and university rankings is the case of Moshe Porat, former dean of Temple University’s Fox Business School. Porat was convicted on November 29, 2021 of engaging in a fraudulent scheme to move the business…

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Big data futuristic visualization abstract illustration

How AI Changed — in a Very Big Way — Around the Year 2000

With the advent of huge amounts of data, AI companies switched from using deductive logic to inductive logic

In “Hyping Artificial Intelligence Hinders Innovation” (podcast episode 163), Andrew McDiarmid interviewed Erik J. Larson, author of The Myth of Artificial Intelligence: Why Computers Can’t Think the Way We Do (2021) (Harvard University Press, 2021) on the way “Machines will RULE!” hype discredits — and distracts attention from — actual progress in AI. Erik Larson has founded two two DARPA-funded artificial intelligence startups. Inthe book he urges us to go back to the drawing board with AI research and development. https://episodes.castos.com/mindmatters/34ce0d74-aa74-4ad9-9599-e9ddf2be56a7-Mind-Matters-News-Episode-163-Erik-Larson-.mp3 This portion begins at 01:59 min. A partial transcript and notes, Show Notes, and Additional Resources follow. Andrew McDiarmid: Can you paint a picture first for us of what the AI landscape looks like today and why it’s not…

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Two female programmers working on new project.They working late at night at the office.

If Not Hal or Skynet, What’s Really Happening in AI Today?

Justin Bui talks with Robert J. Marks about the remarkable AI software resources that are free to download and use

In a recent Mind Matters podcast, “Artificial General Intelligence: the Modern Homunculus,” Walter Bradley Center director Robert J. Marks, a and computer engineering prof, spoke with Justin Bui from his own research group at Baylor University in Texas on what is — and isn’t — really happening in artificial intelligence today. Some of the more far-fetched claims remind Dr. Marks of the homunculus, the “little man” of alchemy. So what are the AI engineers really doing and how do they do it? Call it science non-fiction, if you like… https://episodes.castos.com/mindmatters/d4505b4a-de80-40ae-a56c-2636563f3453-Mind-Matters-Episode-159-Justin-Bui-Episode-1-rev1.mp3 This portion begins at 00:44 sec. A partial transcript and notes, Show Notes, and Additional Resources follow. Robert J. Marks: Isaac Newton was the genius who founded classical physics. He…

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Printed circuit board

“Listen to the technology; find out what it’s telling you…”

That’s the motto of CalTech’s Carver Mead, who will speak at COSM 2021

A COSM 2021 speaker that tech watchers won’t want to miss is CalTech’s Carver Mead (1934–), best known in computer history for pioneering the automation, methodology and teaching of the integrated circuit design used in microprocessors and memories. According to the Lemelson–MIT Student Prize program, “Carver Mead has made many of the Information Age’s most significant advances in microcircuitry, which are essential to the internet access and global cellular phone use that many people enjoy and take for granted every day.” Mead is also honored as a teacher. Forty years at CalTech, he advised the first female electrical engineering student there, Louise Kirkbride, who went on to become a tech developer and inventor in her own right. He has helped…

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Robot hand pressing computer keyboard enter

English Prof: You’ll Get Used To Machine Writing — and Like It!

Yohei Igarashi argues that seamless machine writing is an outcome of the fact that most of what humans actually write is highly predictable

English professor Yohei Igarashi, author of The Connected Condition: Romanticism and the Dream of Communication (2019), contends that writing can mostly be automated because most of it is predictable: Instances of automated journalism (sports news and financial reports, for example) are on the rise, while explanations of the benefits from insurance companies and marketing copy likewise rely on machine-writing technology. We can imagine a near future where machines play an even larger part in highly conventional kinds of writing, but also a more creative role in imaginative genres (novels, poems, plays), even computer code itself. Yohei Igarashi, “The cliché writes back” at Aeon (September 9, 2021) Currently, humans’ ability to guess whether it is machine writing, he says, is only…

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Software development

Publisher of Popular Electronics To Speak at COSM 2021

Futurist John Schroeter is an author as well as a publisher and developer

John Schroeter has many accomplishments as a futurist but also as an author, publisher, and developer: ➤ He is Executive Director at Abundant World Institute, a think tank for leading technologists, futurists and entrepreneurs seeking to create more abundance in the world: Their foundational book, Moonshots—Creating a World of Abundance, won the 2019 Gold Medal by Axiom Business Book Awards, and was recognized by Kirkus Reviews as a “Best Book of 2018.” After Shock (2020) marks the 50-year anniversary of Alvin Toffler’s Future Shock. ➤ He is also the publisher, at TechnicaCuriosa, of iconic mags such as Popular Electronics and Popular Astronomy. “Our iconic titles have literally changed the world. Take Popular Electronics for example. Just one landmark issue was…

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Real Python code developing screen. Programing workflow abstract algorithm concept. Lines of Python code visible under magnifying lens.

How Do We Know the Machine Is Right If No One Knows How It Works?

We don’t, and that’s a problem, says Oxford philosopher John Zerilli

Oxford philosopher John Zerilli, author of A Citizen’s Guide to Artificial Intelligence (2021), asks us to consider how machine learning, the most widely used type of AI, might be deciding our lives without our knowing it: There are many reasons not to take job rejections personally, but there’s one in particular you might not consider: you might have been screened out by an algorithm that taught itself to filter candidates by gender, surname or ethnicity – in other words, by factors that have nothing to do with your ability to do the job. Even if you’re unfazed by the spectre of runaway robots enslaving humanity, this little tale shows how the ascendancy of machine learning (ML) comes with risks that…

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Artificial intelligence, connections and nucleus in concept of interconnected neurons. Abstract background with binary numbers, neural network and cloud computing.

How Marvin Minsky Inspired Artificial Neural Networks

And what Minsky said when a scientist seeking to further develop the field finally met him

Dr. Paul Werbos calls it “a soap opera you wouldn’t believe”: the story of how a young Werbos was inspired by the pioneering computer scientist to pursue the development of artificial neural networks, and how Minsky later could not support the effort for disbelief that there was a solution to its many problems. In this week’s podcast, Dr. Robert J. Marks interviewed Dr. Paul Werbos, famous for his 1974 dissertation which proposed training artificial neural networks through the use of a backpropagation of errors. The two discuss Werbos’s journey in the development of artificial neural networks and the role Marvin Minsky played throughout. This portion begins at 04:25. A partial transcript, Show Notes, and Additional Resources follow. Robert J. Marks:…

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3D rendering of a conceptual images of office cubicles where workers where replaced by artificial intelligence.

Will AI Ever Replace Human Beings? Why Do You Ask?

A better question might be: Why do we want to know the future of artificial intelligence?
The question of whether a machine can ever fully replace a human can only have one, predefined answer. My question is, why bother asking the question? You already know the only answer you will accept! Read More ›
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Circle of people. Teamwork. Business meeting. Negotiations, reaching consensus in disagreements. Joint problem solving. Conflict resolution through dialogue. Compromise. Cooperation and collaboration

Consensus Gives Us Information Only If We Are Free to Doubt

There are so many credentialed people on the internet with sufficiently differing views that it sometimes seems as if we could find an expert somewhere to support almost any harebrained idea. So how does a non-expert figure out the truth? Most of us lack the time, training, and inclination to investigate most subjects sufficiently so we are often urged to adopt the consensus opinion. While an individual expert may have wild and crazy ideas, the consensus will most likely be an average informed view. But it’s not that simple. Most of the time it is impossible for the public to determine the consensus opinion. What is usually labeled as consensus opinion is what media believe it to be. And the…

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Concept of robots replacing humans in offices

Will Humans Ever Be Fully Replaceable by AI? Part 1

We must first determine, what is a person and what is the nature of the universe in which a person can exist?

The title question has been around for quite some time. In this discussion, I would like to take an ontological look at this question. What is the essential nature of being a person? To fully replace humans, what must AI machines become capable of? IF we want to consider the possibility of making humans obsolete, we need to know what is the essence of humanity? What is the ontological nature of a person? What characteristics define being a person? Even before we can address the essential nature of a person, we must identify the essential nature of the universe in which that person exists. What is the universe? How many dimensions does it have? Can the universe, or in it…

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In the Futuristic Laboratory Creative Engineer Works on the Transparent Computer Display. Screen Shows Interactive User Interface with Deep Learning System, Artificial Intelligence Prototype.

A Critical Look at the Myth of “Deep Learning”

“Deep learning” is as misnamed a computational technique as exists.

I’ve been reviewing philosopher and programmer Erik Larson’s The Myth of Artificial Intelligence. See my earlier posts, here, here, and here. “Deep learning” is as misnamed a computational technique as exists. The actual technique refers to multi-layered neural networks, and, true enough, those multi-layers can do a lot of significant computational work. But the phrase “deep learning” suggests that the machine is doing something profound and beyond the capacity of humans. That’s far from the case. The Wikipedia article on deep learning is instructive in this regard. Consider the following image used there to illustrate deep learning: Note the rendition of the elephant at the top and compare it with the image of the elephant as we experience it at the bottom. The image at the bottom is rich,…

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Sisters playing with wagon cart on the road outdoors

Artificial Unintelligence

The failure of computer programs to recognize a rudimentary drawing of a wagon reveals the vast differences between artificial and human intelligence

In 1979, when he was just 34 years old, Douglas Hofstadter won a National Book Award and Pulitzer Prize for his book, Gödel, Escher, Bach: An Eternal Golden Braid, which explored how our brains work and how computers might someday mimic human thought. He has spent his life trying to solve this incredibly difficult puzzle. How do humans learn from experience? How do we understand the world we live in? Where do emotions come from? How do we make decisions? Can we write inflexible computer code that will mimic the mysteriously flexible human mind?  Hofstadter has concluded that analogy is “the fuel and fire of thinking.” When humans see, hear, or read something, we can focus on the most salient features, its “skeletal essence.”…

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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Cancel Culture Symbol

How an AI Giant Beat Cancel Culture (You Can Too!)

A Twitter mob led by an AI industry bully made a mistake when it came for University of Washington's Pedro Domingos

These days Cancel culture can descend suddenly on anyone who doesn’t think the way a Twitter mob likes about one or another issue. For example: ➤ Celebrity atheist scientist Richard Dawkins was Canceled from speaking at Trinity College in Ireland because he has said critical things about Islam and about some claims of sexual assault. Note: Dawkins says critical things about all religions but Cancel mobs focus narrowly. ➤ The enforcement is irrational. Antiracist author Ibrahim X. Kendi can make negative statements about transgender culture comparatively safely but J. K. Rowlings, in a similar circumstance, became the target of a vicious “deplatform” campaign, against which she ably defended herself. However, people who cannot write like Rowlings have not nearly been…

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AI(Artificial intelligence) concept.

Exactly What IS Artificial Intelligence Anyway?

How does AI relate to machine learning (ML), neural computing, informatics, and a host of other hot CS buzz words?

Robert J. Marks, director of the Walter Bradley Center for Natural & Artificial Intelligence, likes to explain AI by saying “AI is anything computers do that is kind of amazing.” (“Human Exceptionalism,” Reasons to Believe, August 8, 2020). Using this definition AI is a general term that includes a collection of computer science technologies. AI is fluid. Dr. Elaine Rich (pictured), noted computer scientist and an author of Artificial Intelligence, offers a more specific definition: “AI is the study of how to make computers do things which, at the moment, people do better.” (Accessed February 17, 2021) Relying on this definition John Hsia observes: “By definition, once a computer can do what people used to do better, it’s no longer…

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Desert locust Schistocerca gregaria is a species of locust, a periodically swarming, short-horned grasshopper in the family Acrididae

AI Tool Now Predicts Attacks of Locust Swarms for African Farmers

Under the right circumstances, data from the past can be used to predict data in the future

A new free AI tool now forewarns African farmers about impending locust attacks: “Farmers and pastoralists receive free SMS alerts 2-3 months in advance of when locusts are highly likely to attack farms and livestock forage in their areas, allowing for early intervention.” The Kuzi early warning tool is one of a number of new tools that can predict reasonably expected futures. This sort of forecasting is possible if there is large body of oracle ergodic data to train machine intelligence. “Oracle ergodic” simply means that data from the past can be used to predict data in the future. That’s not self-evident. Flipping a coin, for example, is not oracle ergodic in the sense that a history of past flips…

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Data technology background. Big data visualization. Flow of data. Information code. Background in a matrix style. 4k rendering.

Torturing Data Can Destroy a Career: The Case of Brian Wansink

Wansink wasn’t alone. A surprising number of studies published in highly respected peer-reviewed journals are complete nonsense and could not be replicated with fresh data

Until a few years ago, Brian Wansink (pictured in 2007) was a Professor of Marketing at Cornell and the Director of the Cornell Food and Brand Lab. He authored (or co-authored) more than 200 peer-reviewed papers and wrote two popular books, Mindless Eating and Slim by Design, which have been translated into more than 25 languages. In one of his most famous studies, 54 volunteers were served tomato soup. Half were served from normal bowls and half from “bottomless bowls” which had hidden tubes that imperceptibly refilled the bowls. Those with the bottomless bowls ate, on average, 73 percent more soup but they did not report feeling any fuller than the people who ate from normal bowls. Eating is evidently…

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Online dating app or site in mobile phone. Finding love and romance from internet with smartphone. Man giving like. Many hologram photos of beautiful woman around cellphone. Stalker looking at profile

Can AI Find You the Love of Your Life?

Faced with a steeply declining birth rate, Japan’s government has decided to try AI matchmaking

Well, outsourcing everything to technology is the thing these days and the Japanese government, faced with a steeply declining birthrate, is giving AI matchmaking a try: Around half of the nation’s 47 prefectures offer matchmaking services and some of them have already introduced AI systems, according to the Cabinet Office. The human-run matchmaking services often use standardized forms to list people’s interests and hobbies, and AI systems can perform more advanced analysis of this data. “We are especially planning to offer subsidies to local governments operating or starting up matchmaking projects that use AI,” the official said. AFP-JIJI, “We have a match! Japan taps AI to boost birth rate slump” at Japan Times (December 7, 2020) Declining birthrate? Japan Times…