Fruitless Recursion as a Strategy

Luring an opponent into fruitless recursion can be an effective strategy in other games, too. One of the most colorful, bizarre, and fascinating episodes in the history of man-vs.-machine chess came in a 2008 blitz showdown between American grandmaster Hikaru Nakamura and leading computer chess program Rybka. In a game where each side got just three minutes on the clock to play all of their moves or automatically lose, the advantage surely seemed to be on the side of the computer—capable of...

 AI Can't Tell You Why It Did Something

The problem comes when the database and the engine go from )ach to oracle. It happens quite often that I will ask one of the students about a move from one of their games, and why he made it. If the move comes early on, the answer is almost always, "Because that's the nain line." That is, that's the theoretical move in the database, likely 5layed by many Grandmasters before. Sometimes the move isn't thery, but the student prepared it with the help of an engine, so the anwer is similar: "It's ...

 Chess Concept: Running Out of Book

One of the problems with playing against computers is how quickly and how often they change. Grandmasters are used to preparing very deeply for our opponents, researching all of their latest games and looking for weaknesses. Mostly this preparation focuses on openings, the established sequences of moves that start the game and have exotic names like the Sicilian Dragon and the Queen's Indian Defense. We prepare new ideas in these openings, and look for strong new moves ("novelties") with whic...

 New Kind of Memory for AI

AI researchers have typically tried to get around the issues posed by by Montezuma’s Revenge and Pitfall! by instructing reinforcement-learning algorithms to explore randomly at times, while adding rewards for exploration—what’s known as “intrinsic motivation.” But the Uber researchers believe this fails to capture an important aspect of human curiosity. “We hypothesize that a major weakness of current intrinsic motivation algorithms is detachment,” they write. “Wherein the a...

 "Intelligent" Holds "Paranormal" Connotations

As soon as AI successfully solves a problem, the problem is no longer a part of AI. Pamela McCorduck calls it an "odd paradox," that "practical AI successes, computational programs that actually achieved intelligent behavior, were soon assimilated into whatever application domain they were found to be useful in, and became silent partners alongside other problem-solving approaches, which left AI researchers to deal only with the "failures," the tough nuts that couldn't yet be cracked."[3]

 A Single Neuron Can Recognize Patterns

Neocortical neurons have thousands of excitatory synapses. It is a mystery how neurons integrate the input from so many synapses and what kind of large-scale network behavior this enables. It has been previously proposed that non-linear properties of dendrites enable neurons to recognize multiple patterns. In this paper we extend this idea by showing that a neuron with several thousand synapses arranged along active dendrites can learn to accurately and robustly recognize hundreds of unique p...

 Artificial Intelligence VS Intelligence Augmentation

IA, or Intelligence Augmentation, is all about empowering humans with tools that make them more capable and more intelligent, while traditional AI has been about removing humans fully from the loop. The traditional torch bearer for IA is Douglas Engelbart, who laid the seeds for much of the Personal Computer revolution with his famous Mother of All Demos in 1968, where he demoed the computer mouse, hypertext, windowing, videoconferencing, and more for the first time. Douglas Engelbart was foc...

 Lojban as AI Language

Can machines feel pride? Not sure question means anything. But you've seen dogs with hurt feelings and Mike had several times as complex a neural network as a dog. What had made him unwilling to talk to other humans (except strictly business) was that he had been rebuffed: They had not talked to him. Programs, yes--Mike could be programmed from several locations but programs were typed in, usually, in Loglan. Loglan is fine for syllogism, circuitry, and mathematical calculations, but lacks fl...

 The Tipping Point of Sentience

When Mike was installed in Luna, he was pure thinkum, a flexible logic--"High-Optional, Logical, Multi-Evaluating Supervisor, Mark IV, Mod. L"--a HOLMES FOUR. He computed ballistics for pilotless freighters and controlled their catapult. This kept him busy less than one percent of time and Luna Authority never believed in idle hands. They kept hooking hardware into him--decision-action boxes to let him boss other computers, bank on bank of additional memories, more banks of associational neur...

 AI View of AI, Scaling Wars

The artilects, as they have been conceived so far in this book, have been largely "nanoteched" creatures. But nanotechnology may be unnecessarily restrictive and far too large a scale to be suitable for advanced artilects. It may be possible that a "femtoteched" creature could be built. Such "femto-artilects" or "femtolects" as they will be called from now on, would be vastly superior to "nano-artilects" or "nanolects," thus setting the stage for a new "species dominance war" all over again. ...