SwiftKey Co-founder: Computers Can’t Just “Evolve” Intelligence
Can vain hopes for AI spring from a wrong understanding of evolution?Ben Medlock asks us to look at self-organization as a principle of life, lacking in computers.
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Can AI Really Evolve into Superintelligence All by Itself?
We can’t just turn a big computer over to evolution and go away and hope for great thingsAt Science earlier this year it was claimed that Darwinian evolution alone can make computers much smarter. As a result, researchers hoped to “discover something really fundamental that will take a long time for humans to figure out”: Artificial intelligence (AI) is evolving—literally. Researchers have created software that borrows concepts from Darwinian evolution, including “survival of the fittest,” to build AI programs that improve generation after generation without human input. The program replicated decades of AI research in a matter of days, and its designers think that one day, it could discover new approaches to AI. Edd Gent, “Artificial intelligence is evolving all by itself” at Science (April 30, 2020) How does that work? The program discovers algorithms using a Read More ›
Will Ideas or Algorithms Rule Science Tomorrow?
David Krakauer of the Santa Fe Institute offers an unsettling vision of future science as produced by machines that no one really understandsThe basic problem is that accepting on faith what we can’t ever hope to understand is not a traditional stance of science. Thus it’s a good question whether science could survive such a transition and still be recognizable to scientists. But does turning things over to incomprehensible algorithms, as Krakauer proposes, really work anyway? Current results from a variety of areas give pause for thought.
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Why we don’t think like computers
If we thought like computers, we would repeat package directions over and over again unless someone told us to stopRobert J. Marks: We have a number of aspects that we exhibit that are not algorithmic. I would say, qualia, creativity, sentience, consciousness are probably things that you cannot write a computer program to simulate.
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Machine Learning, Part 2: Supervised Learning
Machine learning isn’t hard to understand; it’s just different. Let’s start with the most common typeThe neat thing about machine learning is that the algorithm can extract general principles from the dataset that can then be applied to new problems. It is like the story that Newton observed an apple fall and then derived from it the general law of gravity that applies to the entire universe.
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Can Computer Algorithms Be Free of Bias?
Bias is inevitable but it should be recognized and admittedGregory Coppola’s revelations about Google’s politically biased search engine shone a spotlight on how algorithms are written.
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Robotic Accounting Department
The future of number crunchingTechnology has almost entirely replaced the travel agent as well as many brick and mortar stores. But high tech tools like bots are replacing employment in, of all places, accounting. Show Notes Business Intelligence Podcast with Jeremiah Marks
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).
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Exporting and Securing Technologies of Today and Tomorrow
U.S. Export Control and Research EspionageTechnology is vital in commerce and war. Corporations spend billions in development and don’t want to get ripped off. Technology and AI, more than ever, determine military superiority. What are the laws that protect technology and how are they enforced? Show Notes 01:20 | Introduction; Daniel M. Ogden, J.D. 03:06 | Reasons for protected technology 04:00 | Determining what needs Read More ›
This Year’s Top Ten AI Exaggerations, Hyperbole, and Failures: Part I
To end the year, here is our Top Ten Exaggerations, Hyperbole, and Failures list of hype news in artificial intelligence.
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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 needsGoogle 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 ›
Robert J. Marks Talks Computers with Michael Medved
Computers can magnify what we do, he says, and that's the real threatRecently, Robert J. Marks, director of the Walter Bradley Center for Natural and Artificial Intelligence, sat down with radio host and author Michael Medved to help sort through the confusion about what artificial intelligence can and can’t do, now and in the future.
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Who Needs Wisdom? We’ve Got Algorithms!
On a decision about a TV series, the Algorithm offered a narrow view (ratings) while Hollywood offered a “big picture” view. Who was right?While we are seeing some pushback against the movement to “algorithmicize” everything, few lay out explicitly the limitations as well as the benefits of the algorithms increasingly used to make decisions.
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What Humans Do That A.I. Can’t
AI can do many things faster and better than humans. It can beat humans in chess, outsmart us in Jeopardy, and defeat us at GO. The question remains. Is there anything a human can (and always will) do better than an AI? Show Notes