Ask HN: Can someone please say where AI is real?
I read constantly about AI but where is it in any real world application?
If you have an example, please explain why it is AI and not just a computer program.
Sounds like smoke and mirrors to me.
If you have an example, please explain why it is AI and not just a computer program.
Sounds like smoke and mirrors to me.
13 comments
[ 4.9 ms ] story [ 60.8 ms ] threadAlso AI always means "a level of intelligence we haven't achieved yet." Siri could've been considered AI in the past.
1. It's not for an adtech or financial application.
2. It's not for a company that's primarily adtech or finance.
Though clearly AI has value, it seems in practice much of it is implemented for things of questionable human value.
Some examples:
1. Search (some argue the heavy personalization has made it actually less accurate, but that's subjective).
2. Computer vision (main monetization seems to be computer vision/filters. Self driving cars will be useful if and when that comes to fruition)
3. Handwriting recognition. I think this is a great example of AI being helpful. I'm not sure how much of this is "AI" vs. just statistics and machine learning. Maybe it's all the same, in this context.
Edit:
To expand on this a little more... I think it's important to remember that "AI" isn't a "thing" so much as a "field" or a family of (possibly somewhat related) techniques. That is, AI includes specific algorithms and approaches ranging from automated reasoners and inference engines, to pattern recognition using deep learning, to evolutionary algorithms, planning algorithms, etc., etc. What there isn't yet is one single artificial general intelligence that we can talk about as the be-all end-all of AI.
So yeah, individual organizations are using AI techniques all over the place. But nobody is using "AI" because it doesn't exist yet.
In 2016, investors decided to make AI a new priority (it kinda was there for ever). So all the tech companies use this word today to stay "relevant".
Deep neural networks on visual and audio data are passing my smell test. At my last job I helped design and build neural networks to process music data. The results were shockingly good: the networks could tell us a very wide variety of information about a song at an accuracy that exceeded human experts, including genre and mood. This is in a domain that most people think of as very human ("understanding" and "feeling" music), which is what made the results so impressive.
The goalposts will continue to move, but an inflection point has been hit in the last few years. I believe we'll see at least one or two more inflection points in the next several decades as we move closer and closer to "strong" conscious AIs that are functionally above human intelligence.