If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
I propose to consider the question, 'Can machines think?' This should begin with definitions of the meaning of the terms'machine' and'think'. The definitions might be framed so as to reflect so far as possible the normal use of the words, but this attitude is dangerous. If the meaning of the words'machine' and'think' are to be found by examining how they are commonly used it is difficult to escape the conclusion that the meaning and the answer to the question, 'Can machines think?' is to be sought in a statistical survey such as a Gallup poll. Instead of attempting such a definition I shall replace the question by another, which is closely related to it and is expressed in relatively unambiguous words. The new form of the problem can be described in terms of a game which we call the'imitation game'. It is played with three people, a man (A), a woman (B), and an interrogator (C) who may be of either sex. The interrogator stays in a room apart from the other two. The object of the ...
In the seminal paper on AI, titled Computing Machinery and Intelligence, Alan Turing famously asked: "Can machines think?" -- or, more accurately, can machines successfully imitate thought? Turing clarifies that he's interested in machines that "are intended to carry out any operations which could be done by a human computer." In other words, he's interested in complex digital machines. Since the achievement of a thinking digital machine is a matter of the evolution of machines, it reasons to start at the beginning of machine history. A machine is a device that does work.
This is a Q&A excerpt on the topic of AI from a lecture by Richard Feynman from September 26th, 1985. This is a clip on the Lex Clips channel that I mostly use to post video clips from the Artificial Intelligence podcast, but occasionally I post favorite clips from lectures given by others. Hope you find these interesting, thought-provoking, and inspiring. If you do, please subscribe, click bell icon, and share! Artificial Intelligence podcast website: https://lexfridman.com/ai
Our idea is to evaluate each area step by step. As long as each feature is designed to look like it is part of the same body (same gender, age and so on), then if an eye and mouth can individually pass the test then they should also pass it together. This would allow a robot builder to assess progress as they go to ensure each body part is indistinguishable from a that of human and to prevent ending up with something that falls into the uncanny valley.
Computers have already taken over many things that used to be done by people. But how far can this go and is it a good thing? This talk will deal with a little history of how computing and psychology have developed together as well as with what's happening now. We'll end with a discussion of what might happen in the future and what that may mean for how we live our lives.
The history of AI is often told as the story of machines getting smarter over time. What's lost is the human element in the narrative, how intelligent machines are designed, trained, and powered by human minds and bodies. In this six-part series, we explore that human history of AI--how innovators, thinkers, workers, and sometimes hucksters have created algorithms that can replicate human thought and behavior (or at least appear to). While it can be exciting to be swept up by the idea of super-intelligent computers that have no need for human input, the true history of smart machines shows that our AI is only as good as we are. In 1950, at the dawn of the digital age, Alan Turing published what was to be become his most well-known article, "Computing Machinery and Intelligence," in which he poses the question, "Can machines think?"
Here are the slides from my York Festival of Ideas keynote yesterday, which introduced the festival focus day Artificial Intelligence: Promises and Perils. I start the keynote with Alan Turing's famous question: Can a Machine Think? and explain that thinking is not just the conscious reflection of Rodin's Thinker but also the largely unconscious thinking required to make a pot of tea. I note that at the dawn of AI 60 years ago we believed the former kind of thinking would be really difficult to emulate artificially and the latter easy. In fact it has turned out to be the other way round: we've had computers that can expertly play chess for 20 years, but we can't yet build a robot that could go into your kitchen and make you a cup of tea. In slides 5 and 6 I suggest that we all assume a cat is smarter than a crocodile, which is smarter than a cockroach, on a linear scale of intelligence from not very intelligent to human intelligence.
Artificial intelligence (AI) is seen as both a boon and a threat. It uses our personal data to influence our lives without us realising it. It is used by social media to draw our attention to things we are interested in buying, and by our tablets and computers to predict what we want to type (good). It facilitates targeting of voters to influence elections (bad, particularly if your side loses). Perhaps the truth or otherwise of allegations such as electoral interference should be regarded in the light of the interests of their promoters.