Generative AI Hype Cycle is Hitting the ‘Trough of Disillusionment’ [according to technology research and consulting firm Gartner, which has popularized the concept of the 'new technology hype cycle']

MagicShel , 5 hours ago

Good. I’ve been aware of LLMs for about five years but I’ve been saying since the hype started that it can’t do what people are expecting/afraid it will do. It’s about time for sanity to prevail.

remotelove , 4 hours ago

Same. I support AI completely as a tool to solve specific problems and that is about it. What is really cool is that AI libraries and such got a massive boost of needed development so plebs like me can code simple ANN apps in Python with little skill. Documentation has improved 100x and hardware support is fairly good.

LinkedIn seems to be an interesting indicator of where tech is in its hype cycle. I guess LinkedIn went from 100% AI-awesome-everything about 2 months ago to almost zero posts and ads about it. I suppose most of the vaporware AI products are imploding now…

Of course, algorithmic feeds are a thing, so your experience might be different.

lvxferre , 5 hours ago

It does seem to be the case for me - I’ve seen far less overexcited comments, and far more questioning its present and future abilities to perform.

I think that at the bottom of the trough people will stop caring about it altogether except for functionality that has been proven to be useful for - such as a translation aid, coding aid, or to quickly pull off multiple images if you don’t mind overall quality.

I just generated a fresh example highlighting it. I’ll put it inside spoilers to avoid clutter:

German and English, ChatGPT 3.5* [Input 1] translate the following German sentence into English: “der Hund ist schlecht”. * [Output1] The dog is bad. * [Input 2] Which word is being translated as “bad”? * [Output 2] The word “schlecht” is being translated as “bad” in this context. * [Input 3] What are other meanings or connotations of the word “schlecht”? * [Output 3] In addition to “bad,” the word “schlecht” in German can also mean “poor,” “inferior,” “evil,” or “unwell,” depending on the context in which it is used. * [Input 4] Now, translate the sentence “the bad dog is sleeping” into German. * [Output 4] “Der schlechte Hund schläft.” * [Input 5] Why is it “schlechte” in this sentence, instead of “schlecht” as in the earlier sentence? * [Output 5] In German, adjectives change their form based on the gender, number, and case of the noun they are describing. In this case, “Hund” is a masculine noun in the nominative case, so the adjective “bad” (schlecht) needs to take the masculine nominative form, which is “schlechte.” It’s working rather well as a translation aid as long as you know the language, as it could help you to phrase a sentence. However, once you ask for specific info - as I did in input #5 - it drops the ball; in this case outputting technically correct but misleading and incomplete info: * The form also depends on the article. For example, if I were to use “ein” (a) instead of “der” (the), the correct form would be “schlechter” * The way that the output is phrased, it implies that the “schlecht” in the first sentence is not describing a masculine noun in the nominative. It is - and the actual reason why it takes the form “schlecht” is not mentioned in the output (predicatives take the base form). [und nebenbei: alle Hunde sind gut.]

In the “overexcitement peak”, I think that a lot of people were focusing on the correct output, and assuming that the rest would be solved “with enough elbow grease”, playing whack-a-mole with hallucinations. Now they’re noticing that it isn’t.

theangriestbird OP , 4 hours ago

I think that at the bottom of the trough people will stop caring about it altogether except for functionality that has been proven to be useful for

You’re describing the “plateau of productivity”, which is built into this theory:

From this trough of disillusionment the new technology then starts climbing the “slope of enlightenment” where people realistically reassess how the technology can be applied in useful ways, before it reaches the “plateau of productivity” where the new technology is incorporated into the market and and ideally starts to slowly pay off and grow.

and I agree with you! it’s clear that there are good use cases for AI (see this article i posted in Science), we just need to apply it correctly and not overpromise!

lvxferre , 4 hours ago

You’re describing the “plateau of productivity”, which is built into this theory:

Not quite - the plateau represents all useful ways that the tech can be used; what I’m describing is not even a fraction of that, it’s only the stuff that is too obvious to pass.

Thank you for the link - I’m going to give it a check now!