Mind Matters News and Analysis on Natural and Artificial Intelligence

CategoryMachine Learning

Minnesota State Fair

It’s 2019: Begin the AI Hype Cycle Again!

Media seemingly can’t help portraying today’s high-tech world as a remake of I, Robot (2004), starring you and me.
I have a problem with the possible outcomes when people who don’t know the difference between technology fact and fiction make important decisions based on information from journalists who write as if every computer is a potential personality like HAL from Space Odyssey 2001. Read More ›
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Researchers: Deep Learning Vision Is Very Different from Human Vision

Mistaking a teapot shape for a golf ball, due to surface features, is one striking example from a recent open-access paper
The networks did “a poor job of identifying such items as a butterfly, an airplane and a banana,” according to the researchers. The explanation they propose is that “Humans see the entire object, while the artificial intelligence networks identify fragments of the object.” Read More ›
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2: AI Can Write Novels and Screenplays Better than the Pros!

AI help, not hype: Software can automatically generate word sequences based on material fed in from existing scripts. But with what result?

“AI rites reel gud!” Seriously, the idea is not new. Back in the 1940s, George Orwell (1903–1950) thought that a machine could write popular novels so long as no creative thinking was involved. Thus, in his 1984 police state world, one of the central characters has a job minding a machine that mass produces them. In the 1960s, some film experiments were done along these lines, using Westerns (cowboy stories). At the time, there were masses of formula-based film material to work with in this popular genre. But what does the product look and sound like? In 2016, Ars Technica was proud to sponsor “the first AI-written sci-fi script:” As explained in The Guardian, a recurrent neural network “was fed the Read More ›

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Colorful toothpicks or pick-up sticks

How Can We Measure Meaningful Information?

Neither randomness nor order alone creates meaning. So how can we identify communications?
Dropping a handful of toothpicks on the table seems to produce a different sort of pattern than spelling out a word with toothpicks. Surprisingly, this intuitive distinction is harder to make in math and the sciences. Algorithmic specified complexity (ASC) enables us to distinguish them. Read More ›
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Hole or tunnel in dark wall

6: AI Can Even Exploit Loopholes in the Code!

AI adopts a solution in an allowed set, maybe not the one you expected
One example the programmers offered of this type of gaming the system was a walking digital robot that moved more quickly by somersaulting than by using a normal walking gait. Read More ›
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7: Computers can develop creative solutions on their own!

AI help, not hype, with Robert J. Marks: Programmers may be surprised by which solution, from a range they built in, comes out on top
Sometimes the results are unexpected and even surprising. But they follow directly from the program doing exactly what the programmer programmed it to do. It’s all program, no creativity. Read More ›
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A host of blue squid

9: Will That Army Robot Squid Ever Be “Self-Aware”?

AI help, not hype: What would it take for a robot to be self-aware?
The thrill of fear invites the reader to accept a metaphorical claim as a literal fact. Read More ›
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Google Search: Its Secret of Success Revealed

The secret is not the Big Data pile. No, Google found a way to harness YOUR wants and needs

Google is one of the most widely misunderstood success stories of our time. Many of us equate Google with “Big Data,” that is, amassing huge quantities of data and then finding useful statistical patterns. But is that how it succeeded? In Life after Google: The Fall of Big Data and the Rise of the Blockchain Economy, George Gilder criticizes Google primarily on two fronts: First, it is a “walled garden,” a great platform, but inherently isolated and closed. That is a point worth exploring, but not the focus here. The second point, the one I want to touch on, is that Big Data’s day has come and gone. Because Google is a Big Data company, its brightest days are behind it. Read More ›

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Be Choosy About What You Automate!

Having automated many processes, I can assure you that that is the First Rule of Automation
The worst trap that people who are pursuing automation fall into is the desire to automate everything. That’s usually a road to disaster. Automation is supposed to save time and money, but it can wind up costing you both if you don't carefully consider what you automate. Read More ›
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Study Shows Eating Raisins Causes Plantar Warts

Sure. Because, if you torture a Big Data enough, it will confess to anything
Enormous data sets compiled by Big Data methods have a higher probability of meaningless correlations than smaller ones compiled by traditional methods. More than ever, common sense is needed. And common sense only comes from programmers writing their own common sense into the software. Read More ›
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Series of drawn human faces

No, Twitter Is Not the New Awful

It’s the Old Awful back for more. It’s the Town Without Pity we all tried to get away from
We need to decide: Is Twitter the telephone company (a communications platform), the newspaper (a publisher), or interconnected private gossip klatsches where anyone can say whatever they want, whatever ensues? Read More ›
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If Computers Thought Like Fruit Flies, They Could Do More

But even with more sophisticated buzz, there remain "non-computable" things that a computer cannot be programmed to think

Recently, researchers discovered that fruit flies use a filter similar to a computer algorithm to assess the odors that help them find fruit, only the flies’ tools are more sophisticated: When a fly smells an odor, the fly needs to quickly figure out if it has smelled the odor before, to determine if the odor is new and something it should pay attention to,” says Saket Navlakha, an assistant professor in Salk’s Integrative Biology Laboratory. “In computer science, this is an important task called novelty detection. Computers use a Bloom filter for that, Navlakha, an integrative biologist, explains: When a search engine such as Google crawls the Web, it needs to know whether a website it comes across has previously Read More ›

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Can Big Data Help Make Your Book a Best Seller?

It’s more likely to help you picture your odds more clearly and clarify your goals
What does Barabási’s Big Data tell us that we couldn’t just guess? Well, for one thing, that there is a “universal sales curve” which means that a book’s only chance of making the list is shortly after publication. Read More ›
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Potted plants from above

That Plant Is Not a Cyborg

Or a robot. The MIT researcher's underlying idea is a good one but let’s not “plant” mistaken ideas
If plants could move around freely, they would move into the most beneficial lighting arrangement. They compensate for their rootedness by growing in the optimum direction and constantly repositioning their leaves. An MIT researcher has helped out a plant by fitting it with electronic sensors attached to robotic wheels. Read More ›
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Quantity vs Quality: Can AI Help Scientists Produce Better Papers?

What happens when scientists simply can't read all their peers' papers and still find time for original research?
Quantity is definitely a solved problem. STM, the “voice of scholarly publishing” estimated in 2015 that roughly 2.5 million science papers are published each year. Some are, admittedly, in predatory or fake journals. But over 2800 journals are assumed to be genuine. Read More ›
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View of Lake Michigan from the Memorial Museum in Milwaukee, Wi

AI Winter Is Coming

Roughly every decade since the late 1960s has experienced a promising wave of AI that later crashed on real-world problems, leading to collapses in research funding.
Nearly all of AI’s recent gains have been realized due to massive increases in data and computing power that enable old algorithms to suddenly become useful. For example, researchers first conceived neural networks—the core idea powering much machine learning and AI’s notable advances—in the late 1950s. The worries of an impending winter arise because we’re approaching the limits of what massive data combined with hordes of computers can do. Read More ›
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Facial Recognition Aids Persecution of Chinese Christians, Muslims

Western companies still seek business ties with an increasingly authoritarian regime

The crackdown on religion is said to stem from Xi Jinping, who became President in 2012. After he got term limits removed in March 2018, some have begun to privately call him “Emperor Xi.”

Read More ›
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AI, it turns out, can solve any problem

As long as we are not too persnickety about what we consider a solution
The machine that knows what we mean instead of what we say is still in the concept stage. Meanwhile, Deep Mind researcher Victoria Krakovna keeps a running list of ways that generate "a solution that literally satisfies the stated objective but fails to solve the problem according to the human designer’s intent.” Read More ›
TV presenter preparing to live streaming video

If a Robot Read the News, Would You Notice a Difference?

The Chinese government thinks not. Is this the way of the future?
The robotic news readers of China serve a quite different purpose from the independent news outlets and commentators of the West; the robots help disseminate controlled information rather than finding and developing information. Read More ›
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The “superintelligent AI myth”

The problem that even the skeptical Deep Learning researcher left out
I largely agree with what François Chollet said last year as to why there will be no explosion of general artificial intelligence. But when he challenged the fear of an AI-driven “intelligence explosion,” he, perhaps unwittingly, said more than he meant. Read More ›