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Artificial Intelligence is any device that perceives its environment and takes actions that maximize its chance of success at some goal.

I got this definition from Wikipedia that cited "Russell and Norvig (2003), Artificial Intelligence: A Modern Approach".

A transistor is a device that amplifies or switches electronic signals when it received an input signal.

Could one say the transistor is the AI?

It is certainly a basic building block of every AI out there, but is it an AI itself, albeit the most basic one?

I'm looking at it from a technological and economic point of view, leaving philosophy aside. From an economic perspective it seems to be an AI because transistor does useful work that it took an intelligent human to perform less than a century ago. And it does it completely on its own.

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I think it might come down to whether the transistor is making a decision. If the transistor is being used as a switch, that would seem to qualify as a decision, even though it's an extremely rudimentary decision.

Intelligence, in reference to Artificial (or Algorithmic) Intelligence, is not restricted to high intelligence. A brute force Tic-Tac-Toe AI has extremely low, narrow intelligence but still constitute AI. An automatic switch, which makes the most simple decision possible, a binary choice, would seem to be the most basic form of intelligence.

Norvig's definition seems rooted in game theory, which is important in terms of utility of intelligence. But in a condition of intractability one is only assuming one's decision is more optimal than other choices. Outcomes can be evaluated, and a determination made as to whether the algorithm was "smart" or "dumb", but these terms refer to relative positions on a spectrum.

It's worth noting this fundamental definition of AI opens up a can of worms in that pre-transistor, automated mechanical switches such as the Strowger switch would also probably qualify.

And automata do not have to be electrical. The History of Automation wiki suggests the first feedback control system was for a water clock invented by Ctesibius. This device dates to the 3rd Century BCE, and water clocks were said to be the most accurate time pieces until Huygens.

This type of intelligence I tend to think of as autonomic, in the sense of involuntary, and distinct from higher functions, which are more commonly associated with "intelligence".


Note: The characteristics of an autonomic system in a computing context are quite interesting and include self-optimization, self-learning, and self-awareness.

ADDENDUM: After much thought, in reference to @JT's answer, I can't see how decisions can be separated from goals—there needs to be an intent, or the decision is merely random. This might prompt the question "can a simple switch be said to have a goal?"

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Replacing my previous ill conceived answer with this definition of Intelligence from Richard Sutton (a founder and leader Reinforcement Learning) should answer your question.

John McCarthy long ago gave one of the best definitions: "Intelligence is the computational part of the ability to achieve goals in the world”. That is pretty straightforward and does not require a lot of explanation. It also allows for intelligence to be a matter of degree, and for intelligence to be of several varieties, which is as it should be. Thus a person, a thermostat, a chess-playing program, and a corporation all achieve goals to various degrees and in various senses. For those looking for some ultimate ‘true intelligence’, the lack of an absolute, binary definition is disappointing, but that is also as it should be.

The part that might benefit from explanation is what it means to achieve goals. What does it mean to have a goal? How can I tell if a system really has a goal rather than seems to? These questions seem deep and confusing until you realize that a system having a goal or not, despite the language, is not really a property of the system itself. It is in the relationship between the system and an observer. (In Dennett's words, it is a ‘stance’ that the observer take with respect to the system.)

What is it in the relationship between the system and the observer that makes it a goal-seeking system? It is that the system is most usefully understood (predicted, controlled) in terms of its outcomes rather than its mechanisms. Thus, for a home-owner a thermostat is most usefully understood in terms of its keeping the temperature constant, as achieving that outcome, as having that goal. But if i am an engineer designing a thermostat, or a repairman fixing one, then i need to understand it at a mechanistic level—and thus it does not have a goal. The thermostat does or does not have a goal depending of the observer. Another example is the person playing the chess computer. If I am a naive person, and a weaker player, I can best understand the computer as having the goal of beating me, of checkmating my king. But if I wrote the chess program (and it does not look very deep) I have a mechanistic way of understanding it that may be more useful for predicting and controlling it (and beating it).

Putting these two together, we can define intelligence concisely (though without much hope of being genuinely understood without further explanation): Intelligence is the computational part of the ability to achieve goals. A goal achieving system is one that is more usefully understood in terms of outcomes than in terms of mechanisms

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Transistor is very similar in its function to single neuron and because of that one transistor could be considered to be a very tiny neural network - from this perspective it could be considered to be a form of artificial intelligence on their own. But transistor is not the first building block of AI, the first building blocks are the smallest particles that are possible in phisics - those are the building blocks of any machine. Also the definition is somehow hard to accept, as there is no reason why thermostat can be considered AI on their own and transistor not. Since thermostat needs an environment in which it works in a way that fulfills the definition of AI, so the transistor could be put in such environment - there's no difference. We consider that something is AI when it maximizes chnace of some goal, but who is defining this goal? We do. So if you say that the goal of some AI system is to have the output current equal to input current multiplied by factor of x, then you can say that bipolar junction transistor is the AI that does exactly that. Of course you can build a processor and memory from such transistors, then write software for eg. face recognition for a computer builded from them. It is all about connecting algorithms together to perform more sophisticated functions. The first "logical gates" (and builing blocks of AI) are the smallest particles possible, the smallest particles that can interact with each other to produce some output available to be used in next interaction - the whole universe works bacause of that - the matter just follows the algorithms - laws of phisics. On the side note: The only thing that for me is not algorithmical is consciousness, I think it is impossible to be created by just algorithms working together. Algorithms doesn't have any feelings and any number of them will not have feelings either - this will only process information without any consciousness inside. Intelligence is computational, consiciousness somehow reaches beyond phisical/algorithmical world - it is worth consideration - I personally think that we are like players in a game and there is other dimension/world from which our consciousness comes from, good question is: what are the rules of this game?

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It's instructive to know the definition of the transistor.

Transistors are electronic components that are used for amplifiers, as circuit breakers, as connectors, as voltage controllers, for signal modulation and others functions.

(An analogy is that the transistor functions as an electric "faucet" that regulates input and output voltage.)

The definition of AI by Andreas Kaplan and Michael Haenlein defines artificial intelligence as:

"The ability of the system to interpret external data correctly, to learn from that data, and to use that learning to achieve certain goals and tasks through flexible adaptation."

[Citation Needed]

Under this definition, transistors are not part of AI, because transistors do not learn and cannot adapt. Transistors are just electronic devices for regulating current.

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The question is based on two concepts:

  1. First artificial intelligence (AI)
  2. The transistor is an intelligent device.

Let us talk about the first AI, why transistors, the same definition of intelligence can be applied to Vaccum tubes, and they definitely existed before transistors. So no matter what definition you decide for intelligence, transistors are not the first AI.

Now we come to the next part, what is artificial intelligence, like intelligence, the definition of artificial intelligence has undergone changes, in the last 6 decades.

If you use the definition loosely, almost any device can be intelligent even an electric bulb.

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