this post was submitted on 25 Dec 2023
1923 points (97.9% liked)
People Twitter
5390 readers
2028 users here now
People tweeting stuff. We allow tweets from anyone.
RULES:
- Mark NSFW content.
- No doxxing people.
- Must be a tweet or similar
- No bullying or international politcs
- Be excellent to each other.
- Provide an archived link to the tweet (or similar) being shown if it's a major figure or a politician.
founded 2 years ago
MODERATORS
you are viewing a single comment's thread
view the rest of the comments
view the rest of the comments
While this is true, I think of AI in the sci fi sense of a programmed machine intelligence rivaling human problem solving, communication, and opinion forming. Everything else to me is ML.
But like Turing thought, how can we really tell the difference
Turing's question wasn't a philosophical one. It was a literal one, that he tried to answer.
What the person said is NOT true. Nobody like Turing would EVER call those things AI, because they are very specifically NOT any form of "intelligence". Fooling a layman in to mislabeling something is not the same as developing the actual thing that'd pass a Turing test.
As far as taking scifi terms for real things, at least this one is somewhat close. I'm still pissed about hover boards. And Androids are right out!
What you're referring to in movies is properly known as Artificial General Intelligence (AGI).
AI is correctly applied to systems that process in a "biologically similar" fashion. Basically something a human or "smart" animal could do. Things like object detection, natural language processing, facial recognition, etc, are things you can't program (there's more to facial recognition, but I'm simplifying for this discussion) and they need to be trained via a neural network. And that process is remarkably similar to how biological systems learn and work.
Machine learning, on the other hand, are processes that are intelligent but are not intrinsically "human". A good example is song recommendations. The more often you listen to a genre of music, the more likely you are to enjoy other songs in that genre. So a system can count the number of songs you listen to the most in a specific genre, and then recommend that genre more than others. Fairly straightforward to program and doesn't require any training, yet it gets better the more you use it.