Mind Matters News and Analysis on Natural and Artificial Intelligence

CategoryMachine Learning

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Missile explosion

Why we can’t just ban killer robots

Should we develop them for military use? The answer isn’t pretty. It is yes.

Autonomous AI weapons are potentially within the reach of terrorists, madmen, and hostile regimes like Iran and North Korea. As with nuclear warheads, we need autonomous AI to counteract possible enemy deployment while avoiding its use ourselves.

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Stripes on two lane highway

Can We Program Morality into a Self-Driving Car?

A software engineering professor tells us why that’s not a realistic goal

Any discussion of the morality of the self-driving car should touch on the fact that the industry as a whole thrives on hype that skirts honesty.

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Cryptic characters in neon, a password or curse word

Bitcoin: Is Lack of Trust the Biggest Security Threat?

It’s almost a parable: Everyone can see, no one can access, the millions trapped in the ether by a password known only to a dead man
Is this the future of currency? Seems like the Dark Ages to me. Bitcoin is a clever idea, but it is perhaps too clever for its own good. Read More ›
sad robot
Toy Robot looking at itself in mirror

That Robot Is Not Self-Aware

The way the media cover AI, you'd almost think they had invented being hopelessly naïve
If this is how The Telegraph reports on a robotic arm, can you imagine what it will sound like when we get humanoid robots who seem to carry on conversations? We had best inoculate ourselves now against AI hype from science reporters while most of us still have enough self-awareness to realize what’s going on. Read More ›
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Classified section of a newspaper

Part 2: Navigating the Machine Learning Landscape — Supervised Classifiers

Supervised classifiers can sort items like posts to a discussion group or medical images, using one of many algorithms developed for the purpose
In Part 1 of our series, we looked at machine learning, including supervised learning, unsupervised learning, and reinforcement learning. Now we’re going to dive a little deeper into how supervised learning works. Read More ›
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Scrabble pieces with numbers and letters

The Numbers Don’t Speak for Themselves

The patterns uncovered by machine learning may reflect a larger reality or just a bias in gathering data
Because Machine Learning is opaque—even experts cannot clearly explain how a system arrived at a conclusion—we treat it as magic. Therefore, we should mistrust the systems until proven innocent (and correct). Read More ›
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Mortar Board on top of keyboard

Artificial Intelligence Is Actually Superficial Intelligence

The confusing ways the word “intelligence” is used belie the differences between human intelligence and machine sophistication

Words often have more meaning than we hear at first. Consider colors. We associate green with verdant, healthy life and red with prohibition and danger. But these inferences are not embedded in the basic meaning of “red” or “green.” They are cultural accretions we attach to words that enable the richness of language. That, by the way, is one reason why legal documents and technical papers are so difficult to read. The terms used are stripped clean of such baggage, requiring additional words to fill the gaps. The word “intelligent” is like that. Saying that a computer, or a program, is intelligent can lead us down a rabbit hole of extra meaning. An honest researcher merely means the computer has Read More ›

Composite image of image of data
Composite image of image of data

Part 1: Navigating the Machine Learning Landscape

To choose the right type of machine learning model for your project, you need to answer a few specific questions
Most machine learning systems fall into three main categories—supervised learning, unsupervised learning, and reinforcement learning. The choice of system depends first on which category of machine learning best addresses your situation. Read More ›
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Does AI Art Spell the End of the Artist’s Way of Life?

An AI-produced painting sold at auction for $432,500. But is it a trend or just a novelty?
Rather than announce that human artists are now doomed, software engineer Ben Dixon interviewed a number of them and came away with a rather different picture, that “AI-generated art will improve, but artistic creativity will remain a human discipline.” Read More ›
Amoebae move and feed by using pseudopods, which are bulges of cytoplasm formed by the coordinated action of actin microfilaments pushing out the plasma membrane that surrounds the cell.
Amoebae move and feed by using pseudopods, which are bulges of cytoplasm formed by the coordinated action of actin microfilaments pushing out the plasma membrane that surrounds the cell.

Is an Amoeba Smarter Than Your Computer?

Hype aside, the microbe’s math skills ace the Traveling Salesman problem and may help with cybersecurity
When we hear hype about machines that will soon out-think people, we might put it in perspective by recalling that we still struggle to build a machine that can out-think amoebas looking for crumbs. Read More ›
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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Scene clapperboard in front of two actors

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 ›

toothpicks
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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Fake bugs on yellow background

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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Timer attached to steel device

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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Data graph on monitor showing correlation

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 ›