CategoryMachine Learning
Self-driving Cars Need Virtual Rails
The alternative is more needless fatalitiesA virtual rail is essentially a road that is built expressly for driverless cars.
Read More ›
A Closer Look at Detroit: Become Human, Part III
The second pillar of the AI religion is reductionism, the reduction of humanity to matter and energyIf the qualities that define being human (so that there is an obvious distinction between what is human and what is not) are not material by nature; then the premise of a compelling story about androids that become and surpass human beings as intelligent life falls flat.
Read More ›
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.
Read More ›
Can We Program Morality into a Self-Driving Car?
A software engineering professor tells us why that’s not a realistic goalAny 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.
Read More ›
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 manIs 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 ›
That Robot Is Not Self-Aware
The way the media cover AI, you'd almost think they had invented being hopelessly naïve
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
The Numbers Don’t Speak for Themselves
The patterns uncovered by machine learning may reflect a larger reality or just a bias in gathering dataBecause 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 ›
Artificial Intelligence Is Actually Superficial Intelligence
The confusing ways the word “intelligence” is used belie the differences between human intelligence and machine sophisticationWords 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 ›
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
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 ›
Is an Amoeba Smarter Than Your Computer?
Hype aside, the microbe’s math skills ace the Traveling Salesman problem and may help with cybersecurity
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.
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
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 ›
How Can We Measure Meaningful Information?
Neither randomness nor order alone creates meaning. So how can we identify communications?
6: AI Can Even Exploit Loopholes in the Code!
AI adopts a solution in an allowed set, maybe not the one you expected
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