‘Overhyped’ generative AI will get a ‘cold shower’ in 2024, analysts predict::Analyst firm CCS Insight predicts generative AI will get a “cold shower” in 2024 as concerns over growing costs replace the “hype” surrounding the technology.
Honest title: lazy analyst pretends to be smart recycling an overused Gartner graph
We’re getting customers that want to use LLMs to query databases and such. And I fully expect that to work well 95% of the time, but not always, while looking like it always works correctly. And then you can tell customers a hundred times that it’s not 100% reliable, they’ll forget.
So, at some point, that LLM will randomly run a complete non-sense query, returning data that’s so wildly wrong that the customers notice. And precisely that is the moment when they’ll realize, holy crap, this thing isn’t always reliable?! It’s been telling us inaccurate information 5% of the usages?! Why did no one inform us?!?!?!
And then we’ll tell them that we did inform them and no, it cannot be fixed. Then the project will get cancelled and everyone lived happily ever after.
Or something. Can’t wait to see it.
Would you trust a fresh out of college intern to do it? That’s been my metric for relying on LLM’s
It might actually help the intern if they use it:
I’ve been speculating that people raving about these things are just bad at their jobs for a bit, I’ve never been able to get anything useful out of an llm.
Seeing people say they’re saving lots of time with LLMs makes me wonder how much menial busywork other people do relative to myself. I find so few things in my day where using these tools wouldn’t just make me a babysitter for a dumb machine.
It’s great for writing latex.
latexify
sum i=0 to n ( x_i dot (nabla f(x)) x e_r) = 0
\[
\sum_{i=0}^{n} \left( x_i \cdot (\nabla f(x)) \times e_r \right) = 0
\]
Also great at postioning images and fixing weird layout issues.
Yeah… as a Product Manager, dealing with a lot of text based tasks, I really expected to find it more useful than I actually have. I’ve not really been able to use it for writing documentation and sending emails, because it matters to me what is in those and I have something I want to say in them.
The only way I could really consider offloading these tasks to AI is if I just stopped caring what went in them.
Depends on what you do. I personally use LLMs to write preliminary code and do cheap world building for d&d. Saves me a ton of time. My brother uses it at a medium-sized business to write performance evaluations… which is actually funny to see how his queries are set up. It’s basically the employee’s name, job title, and three descriptors. He can do in 20 minutes what used to take him all day.
Well that just sounds kind of bad… I hadn’t even considered generating a performance review for my direct report. It’s part of my job to give them meaningful feedback and help them improve, not just tick a box.
Regardless of what anyone says, I think this is actually a pretty good use case of the technology. The specific verbiage of a review isn’t necessarily important, and ideas can still be communicated clearly if tools are used appropriately.
If you ask a tool like ChatGPT to write “A performance review for a construction worker named Bob who could improve on his finer carpentry work and who is delightful to be around because if his enthusiasm for building. Make it one page.” The output can still be meaningful, and communicate relevant ideas.
I’m just going to take a page from William Edwards Deming here, and state that an employee is largely unable to change the system that they work in, and as such individual performance reviews have limited value. Even if an employee could change the system that they work in, this should be interpreted as the organization having a singular point of failure.
What your brother is doing is a pretty good example of why this stuff needs to be regulated better. People’s performance evaluations are not the kind of thing that these tools are equipped to do properly.
I use AI all the time in my work. With one of my tools I can type in a script and have a fully-acted, fully-voiced virtual instructor added to the training we create. Saves us massively in both time and money and increases engagement.
This is how AI will truly sweep through the market. Small improvements, incrementally developed upon, just like every other technology. White collar workers will be impacted first, with blue collar workers second, as the technology continues to develop.
My friend is an AI researcher as part of his overarching role as an analyst for a massive insurance company, and they’re developing their own internal LLM. The things AI can do will be absolutely market-shattering over time.
Anyone suggesting AI is just a fad/blip is about as naive as someone saying that about the internet in 1994, in my view.
2024 headline: “Analyst replaced by generative AI”
In the mean time, I’m using chat gpt at work every day now and I’m able to work much faster because of it.
To me it’s next generation search engine. For tech queries it’s correct a lot.
Once it stops giving non-existent powershell commands, I’ll give it another go, but for now it has wasted enough of my time.
The worst part is how eager it is to give you a non-existent switch or cli option. Like if it gives you some multi-line solution, all you have to do is say something like “are you sure there’s not an option where I can do this in one line?” And it’ll be like, “oh yeah you’re totally right, you can just use this non-existent thing that totally won’t work! Sorry about the confusion!”
Unfortunately that hasn’t been my experience, but I’m only using it to find answers for things a couple ddg queries won’t solve because traditional search engines are so much faster
