Unlike block chain, there is a solid chunk of new use cases to be conquered with AI. These might be very technical in nature, but for example, text suggestions on smartphones might already be done with AI, depending on your OS.
We already have text prediction that works more efficiently (from a power and computing point of view) by using things like trees.
There’s very few use-cases I’ve seen where AI is more efficient than an algorithm, and it’s mostly in areas where it does a bunch of tests/research/simulation inputs by throwing random shit at the wall that users wouldn’t normally try really fast.
AI is basically useless when you’re doing something that’s easily repeatable, because it’s easier to actually implement tools that use algorithms to do that kind of thing.
Just give it a couple of years for the hype/boom/bust cycle to complete, then it’ll settle down and people will start using the tech appropriately.
Yep, in the exact same was as blockchain: nowhere.
Unlike block chain, there is a solid chunk of new use cases to be conquered with AI. These might be very technical in nature, but for example, text suggestions on smartphones might already be done with AI, depending on your OS.
We already have text prediction that works more efficiently (from a power and computing point of view) by using things like trees.
There’s very few use-cases I’ve seen where AI is more efficient than an algorithm, and it’s mostly in areas where it does a bunch of tests/research/simulation inputs by throwing random shit at the wall that users wouldn’t normally try really fast.
AI is basically useless when you’re doing something that’s easily repeatable, because it’s easier to actually implement tools that use algorithms to do that kind of thing.
My brother in Christ, a LLM is a tree
neural network tools seem really powerful for image filtering and video compression.
That could explain why SwiftKey sucks now
Google and partners have been showing off some pretty cool use cases for Gemini, mostly related to GCP, at Next 24.