AI is good at winning games. But how does this (and other) accomplishments translate to applications in the real world? George Gilder and Robert J. Marks discuss artificial intelligence, games, and George Gilder’s new book Gaming AI: Why AI Can’t Think but Can Transform Jobs (which you can get for free here). Show Notes Additional Resources
At 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 ›
The list is a selection from “Bingecast: Robert J. Marks on the Limitations of Artificial Intelligence,” a discussion between Larry L. Linenschmidt of the Hill Country Institute and Walter Bradley Center director Robert J. Marks. The focus on why we mistakenly attribute understanding and creativity to computers. The interview was originally published by the Hill Country Institute and is reproduced with thanks. https://episodes.castos.com/mindmatters/Mind-Matters-097-Robert-Marks.mp3 Here is a partial transcript, listing six limits of AI as we know it: (The Show Notes, Additional Resources, and a link to the full transcript are below.) 1. Computers can do a great deal but, by their nature, they are limited to algorithms. Larry L. Linenschmidt: When I read the term “classical computer,” how does a computer function? Let’s build on Read More ›
The 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.
Read More ›
Robert 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.
Read More ›
The 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.
Read More ›
Gregory Coppola’s revelations about Google’s politically biased search engine shone a spotlight on how algorithms are written.
Read More ›
Technology 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
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 ›
Technology 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 ›
To end the year, here is our Top Ten Exaggerations, Hyperbole, and Failures list of hype news in artificial intelligence.
Read More ›
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 ›
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