zlacker

https://en.wikipedia.org/wiki/Gartner_hype_cycle

>>rythms+(OP)
I think Machine learning already went through the trough of disillusion around 2016-2018 in computer vision and around 2018-2020 for voice assistants.

I think we're now past that and people can see that tools like ChatGPT are powerful enough to be applied in many pre existing contexts and industries in unpredictable and inventive ways without huge amounts of manual configuration, which makes it more exciting.

>>krona+H1
Machine learning is way too generic of a term. Everything from linear regressions to neural models is technically "machine learning".

Language models are right now at the very top of the peak of inflated expectations. It's still too early to tell what the real impact will be, but it won't be even remotely close to what you read on the headlines.

Far more impressive technology (like Wolfram Alpha) has existed for almost a decade now, and it's directly comparable to language models for many applications.

My guess is they will end up being something like Rust. Very cool to look at, little impact on your day-to-day.

>>rythms+(OP)
If you can jump around without prediction which point is next, the hype cycle is useless. There are terms ppl use for things that are en vogue. There is no hype cycle.

>>krona+H1
ML/AI is a repeat offender (for that matter, so is The Almighty Blockchain; it managed a few hype cycles under slightly different identities; blockchain, ICO, NFTs, and so on). Remember in the late 90s when Microsoft and Apple both appeared fully convinced that voice would be the primary interface with computers imminently? There was also a large brief chat agent bubble a few years back.