The Secret Ingredient for AI: Ergodicity
If you don't know the term, you need toEconomist George Gilder notes that creativity in invention and entrepreneurism is characterized by innovative surprise.
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The National Science Foundation and Advancement in Artificial Intelligence
Early in his career, IEEE fellow and retired National Science Foundation program director Paul Werbos developed the neural network training algorithm known as error backpropagation, which has been foundational to the vast majority of today’s advances in artificial intelligence. Listen in as he discusses his work in this area and other topics, including his tenure with the National Science Foundation, Read More ›
Paul Werbos: The National Science Foundation and AI
In today’s episode, Dr. Robert J. Marks continues his conversation with Dr. Paul Werbos, the inventor of the most commonly used technique to train artificial neural networks. Listen in as they turn to the National Science Foundation, its role in steering research in artificial intelligence, and the major turning points in machine intelligence that Dr. Werbos witnessed as a program Read More ›
A Critical Look at the Myth of “Deep Learning”
“Deep learning” is as misnamed a computational technique as exists.I’ve been reviewing philosopher and programmer Erik Larson’s The Myth of Artificial Intelligence. See my earlier posts, here, here, and here. “Deep learning” is as misnamed a computational technique as exists. The actual technique refers to multi-layered neural networks, and, true enough, those multi-layers can do a lot of significant computational work. But the phrase “deep learning” suggests that the machine is doing something profound and beyond the capacity of humans. That’s far from the case. The Wikipedia article on deep learning is instructive in this regard. Consider the following image used there to illustrate deep learning: Note the rendition of the elephant at the top and compare it with the image of the elephant as we experience it at the bottom. The image at the bottom is rich, Read More ›
AI Smash Hits 2020 Part II
An ultimate test of a successful technology is whether it has been reduced to practice. Has it made a financial impact on the market? Has it been adopted by the very picky US military? Has it changed lives? We’re going to count down the AI Smash Hits: the top ten AI success stories for 2020. Join Dr. Robert J. Marks as he Read More ›
Bingecast: Robert J. Marks on the Limitations of Artificial Intelligence
Robert J. Marks talks with Larry L. Linenschmidt of the Hill Country Institute about nature and limitations of artificial intelligence from a computer science perspective including the misattribution of creativity and understanding to computers. Other Larry L. Linenschmidt podcasts from the Hill Country Institute are available at HillCountryInstitute.org. We appreciate the permission of the Hill Country Institute to rebroadcast this Read More ›
All AI’s Are Psychopaths
We can use them but we can’t trust them with moral decisions. They don’t care whyBuilding an AI entails moving parts of our intelligence into a machine. We can do that with rules, (simplified) virtual worlds, statistical learning… We’ll likely create other means as well. But, as long as “no one is home”—that is, the machines lack minds—gaps will remain and those gaps, without human oversight, can put us at risk.
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Technology Centralizes by Its Very Nature
Here are some other truths about technology, some uncomfortable onesTo see what I mean about centralization, consider a non-digital tool, say, a shovel. The shovel doesn’t keep track of your shoveling, read your biometrics, and store a file on you-as-shoveler somewhere. It’s a thing, an artifact. So you see, the new digital technology is itself the heart of the surveillance problem. No Matrix could be built with artifacts.
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Can We Outsource Hiring Decisions to AI and Go for Coffee Now?
I would have fired any of my hiring managers who demonstrated characteristic AI traits immediately. So why do we tolerate it coming from a machine?With historically low unemployment, employers are tempted to reduce costs and speed up the process using artificial intelligence (AI) systems. These systems might help but, for best results, let’s have a look at the problems they can’t solve and some that they might create.
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Just a light frost—or AI winter?
It’s nice to be right once in a while—check out the evidence for yourselfAbout a year ago, I wrote that mounting AI hype would likely give way to yet another AI winter. Now, according to the panelists at “the world’s leading academic AI conference” the temperature is already falling.
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Gee-Whiz Tech and AI Reality – Part I
Robert J. Marks talks with Larry L. Linenschmidt of the Hill Country Institute about the nature and limitations of artificial intelligence from a computer science perspective. This is Part 1 of 2 parts. Other Larry L. Linenschmidt podcasts from the Hill Country Institute are available at HillCountryInstitute.org. We appreciate the permission of the Hill Country Institute to rebroadcast this podcast Read More ›
Lazy Engineers Treat AI as Magic!
When software engineers mostly use shared code, they save time but risk losing understandingBuilding from scratch is different. Knowing when to use a tool and why and knowing the limitations of each tool separates the craftsperson from the novice.
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We Built the Power Big Social Media Have Over Us
Click by click, and the machines learned the patterns. Now we aren’t sure who is in chargeWe’re stuck, working for free, training the Web giants’ ML systems to reap benefits for them while enduring (assuming we notice) the downsides.
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Gary Smith: The AI Delusion
“When I Nod My Head, Hit It!” And Other Commands that Confuse AI.Pablo Picasso said “Computers Are Useless. They Can Only Give You Answers.” Picasso didn’t go far enough. The answers that computers give must themselves be questioned. This is especially true of AI. Questioning AI is the topic today on Mind Matters. Show Notes 01:27 | Introduction to Gary Smith 02:40 | The AI Delusion 04:50 | Stocks and Data 07:00 Read More ›
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
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 ›
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.”
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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 paperThe 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.”
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Can the Air Force Create Thinking Planes?
Smart drones? They are working on general artificial intelligence (GAI)Eric Holloway: The likely way this will turn out is they’ll realize human-in-the-loop is unavoidable for any useful system, so it’ll spin off into something like the existing field of human computation.
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The “superintelligent AI myth”
The problem that even the skeptical Deep Learning researcher left outI 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.
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