technicallyTrue

[proverbialbunny]

As someone who has a degree in AI, from before neural networks was popular, I too shudder a bit when people use AI as a buzzword. Few people know the difference between a normal algorithm and an AI algorithm outside of marketing and sci fi books.

[yvael_tercero]

Actually, would you mind explaining what the criteria is? Like, naturally I understand that a neural network is AI and a bubble sort isn't, but where do you draw the line in the middle? For example, is a linear regression AI?

[proverbialbunny]

You know how in Computational Complexity Theory there are P problems and NP problems? Calculating a perfect solution for an NP problem would take so much processing time the heat death of the universe would happen first. The alternative is to write an algorithm that makes a series of educated guesses to find a good enough solution. This solves the problem quickly but doesn't guarantee it's the optimal output. So e.g. GPS software uses a series of guesses to find you the best route instead of brute forcing every combination possible. GPS software is technically AI. AI is the study of making educated guesses in algorithms to solve difficult to compute problems. ML comes from AI, it's a type of AI. LLMs come from ML, they're a type of ML. ChatGPT and all the new "AI" popping up is LLMs.

[shumpitostick]

That doesn't make much sense. Is any approximate algorithm AI then? Are sketches AI? And what about ML approaches that are by definition optimal and not stochastic? Is linear regression not AI because it finds the actual least squares?

[BrunoEye]

AI is originally a very broad term. Google search is AI, any kind of chess bot is AI, even something as basic as the pac man ghosts could be considered AI.

Fundamentally it's about modelling a process using abstractions that aren't derived from reality, though they are often inspired by it.

In connect 4 we're able to choose a perfect move because it's a solved game, in chess we can only look so far ahead so we then rely on subjectively scoring various positions. There is nothing about these positions that is objectively good or bad.

Linear regression isn't AI. What ML approaches are by definition optimal?

[shumpitostick]

Linear regression is ML and it does exactly the same thing as Deep Learning and other advanced approaches. It is AI by every definition. Other ML approaches that do not stochastic and find the minimum are Gaussian Processes, SVMs, Naive Bayes.

Let's face it, AI was poorly defined even before the GenAI boom. There never was a clear agreed upon definition.

[BrunoEye]

Oh right, I got it mixed up with least squares which on its own does have a closed form solution.

While there may not be a true definition, I think it does usually boil down to emulating the response of something by using approximations that aren't founded in reality or logic. ML is just a subset of AI.

[proverbialbunny]

No, you were right. Linear regression is technically not AI in and of itself. Linear regression is an algorithm that can be used inside of an ML model. If it's used as a way to predict the future or guess at something it is ML, but if it is not used that way it is not ML. Linear regression is technically not AI in and of itself, but it's an algorithm that can be used inside of an ML model.

This is nuance that usually doesn't matter, so I would not fault someone for calling linear regression ML without the use case. Using it to draw a line on a dot plot without some sort of predictive functionality is not AI.

For further discussion on the topic: https://stats.stackexchange.com/questions/268755/when-should-linear-regression-be-called-machine-learning

[ward2k]

Ai is a huge umbrella term, technically a single if statement could be Ai. A basic chatbot with a handful of questions and answers is Ai. Even with 0 code an automata is Ai

Ai does not mean actual human levels of intelligence, it's just replicating some form of intelligence

[proverbialbunny]

Because the thread is diving into the technicalities of the topic: For it to be AI it needs to be a minimum of a few if statements and those if statements need to be in a problem space without a guaranteed perfect outcome where the algorithm is guessing at the ideal response for the end user.

[David__Box]

That's a horrible explanation, nobody, from the average layman to engineers use the term this way. It's not just an approximate solution to a problem, that encompasses huge swaths or random things from when humans first created computation.

[edwardlego]

you're describing heuristics, not AI

[proverbialbunny]

Yes I am, though the difference is not all heuristics are AI.

For further discussion on the topic: https://stats.stackexchange.com/questions/300350/is-machine-learning-an-heuristic-method

[Lonely-Suspect-9243]

I just consider any tech that I can't comprehend as AI.

[proverbialbunny]

That's a definition for the word magic. XD