Podcast: Play in new window | Download (Duration: 6:14 — 3.9MB) | Embed
Diving into deep learning Neural networks have had their ups and downs. However, in the last decade or so, they’ve really taken off. There were a couple of breakthroughs that made all the difference. Today we look at one of them, called “Deep Learning.” Here’s a 4-post long blog series on deep learning concepts and …
Podcast: Play in new window | Download (Duration: 4:46 — 3.0MB) | Embed
Evolving neural networks with polyworld Figuring out exactly what structure of a neural network could capture intelligence is a complicated problem. Why not let evolution do it for you? Today we look at Polyworld, where they did and are continuing to do that very experiment. Here’s a talk on polyworld and some of their results. …
Podcast: Play in new window | Download (Duration: 5:13 — 3.0MB) | Embed
Unsupervised learning When you are teaching an AI to solve a problem or do some task, you usually have to provide the right answer. However, sometimes, the AI can learn by itself, without being told what the right answer is.
Podcast: Play in new window | Download (Duration: 4:49 — 3.0MB) | Embed
Better and better Computers are being used to design computers. The better our computers and their tools get, the better computers and tools they can produce. But it wasn’t always an easy path. Today we look at the VAX9000. It used a system called “SID” to generate part of its design. SID was an expert …
Podcast: Play in new window | Download (Duration: 4:42 — 2.8MB) | Embed
An experiment in fuzzy logic Computers use Boolean logic. Everything is true false, yes no, zero and one. There are plenty of situations when a simple yes or no won’t cover it. To get a computer to handle those situations, one can use fuzzy logic. Today, we have an informal experiment that shows why fuzzy …
Podcast: Play in new window | Download (Duration: 5:33 — 3.2MB) | Embed
Socrates is not a woman Evolutionary approaches, genetic algorithms, and neural networks aren’t the only approaches to creating artificial intelligence. Today, we look at one of the early and rather successful approaches—expert systems.
Podcast: Play in new window | Download (Duration: 4:30 — 2.5MB) | Embed
Take heart, yee robots shivering in the cold In the past, new methods of creating an artificial intelligence have garnered interest and enthusiasm. Then, when the over optimistic forecasts fail, nearly all funding and research grinds to a halt. It’s called an AI winter. Despite such setbacks, the general trend has been toward increasing ability …
Previous post in topic First post in topic Table of contents Adding by subtracting There won’t be posts after this one on this thing for a couple of weeks. I must navigate the dangerous, relative infested waters of the holidays. I need to be able to show that the way we program our machine can …
Podcast: Play in new window | Download (Duration: 7:35 — 4.3MB) | Embed
The perceptron In 1957, Frank Rosenblatt came up with the perceptron. The perceptron is a simple neural network that was able to recognize simple shapes. Unfortunately, Rosenblatt got a little over excited, and made over inflated statements about what his perceptron would be able to do. After the 1969 publication of Marvin Minsky and Seymour …