Reading this comment section is so strange. Skepticism about generative AI seems to have become some kind of professional sport on the internet.
Consensus in our group is that generative AI is a great tool. Maybe not perfect, but the comparison to the metaverse is absurd: no one asked for the metaverse or needed it for anything, as opposed to several cases where GPT has literally bailed us out of a difficult situation. e.g. some proof of concept needed to be written in a programming language that no one in the group had enough experience with. With no GPT, this could have easily cost someone a week. With GPT assistance – proof of concept ready in less than a day.
Generative AI does suffer from a host of problems. Hallucinations, jailbreaks, injections, reality 101 failures, believe me I’ve encountered all these intimately as I’ve had to utilize GPT for some of my day job tasks, often against its own better judgment and despite its own woefully lacking capacity to deal with the task. What I think is interesting is a candid discussion: why do these issues persist? What have we tried? What techniques can we try next? Are these issues intractable in some profound sense, and constitute a hard ceiling for where generative AI can go? Is there an “impossibility theorem for putting AI on autopilot”? Or are these limitations just artifacts we can engineer away and route around?
It seems like instead of having this discussion, it’s become in vogue to wave around the issues triumphantly and implicitly declare the field successfully dunked on, and the discussion over. That’s, to be blunt, reductive. Smartphones had issues, the early internet had issues. Sure, “they also laughed at Bozo the clown” and all that, but without a serious discussion of the landscape right now, of how far away we are from mitigating these issues and why, a lot of this “ha ha suck it AI” discourse strikes me as deeply performative. Like, suppose a year from now OpenAI solves hallucinations. The issue is just gone. Do all the cool kids who sneered at the invented legal precedents, crafted their image as knowing better than the OpenAI dweebs, elegantly implied how hallucinations are a cornerstone in how the entire field is a stupid useless dead end – do they lose any face? I think they don’t. I think this is why this sneering has become such a lucrative online professional sport.
Some of the skepticism is just a reaction to the excessive hype with which generative AI has been pushed over the past few months. If you’ve seen tech hype cycles before, the hype itself can generate some skepticism. Plus there are many dubious cases where companies are shoving ChatGPT or similar into their products just so they can advertise them as “AI powered”, and these poorly thought out, marketing-driven moves deserve criticism.
It’s amazing how critical Lemmy is of ChatGPT. It has become fashionable to pretend it’s a trash technology. The reality is that it is and will continue changing the world.
Come on now, next you’ll be saying the tech industry consistently overplays its incremental improvements as Earth-shattering paradigm shifts purely for the investment money!
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Yup. As someone who works in tech, I was baffled by the number of people in my field who started freaking out about it. AI isn’t some magic panacea, it’s just another tool that needs to be designed for the task at hand. It’s cool that ChatGPT can get 80% of the way there in so many fields, but that last 20% is where all the hard work is (see the pareto principle).
In the early 1980s, a teacher refused to let me word-process my homework (my penmanship was shit) on the grounds that I shouldn’t be able to produce a paper at the touch of a button.
Upper management look at AI end results and imagine a similar scenario: they don’t see the human effort behind the dumb-waiter and imagine a clerk can just tell an LLM to make me a sequel to Dumbo without getting very specific and then having a team of reviewers watch hundreds of terrible elephant films to curate the few good ones.
But what is telling is how our corporate bosses responded to the prospect of automated art. Much like the robot pizza company who did not automate the process and pass the savings on to you! (his offerings were typical pizza at typical prices and he kept all the savings for himself) our senior execs imagine ways to replace workers with cheaper automation rather than producing better stuff or cheaper movie tickets for their customers.
So maybe we should growl at them and change the system before they figure out how to actually pay fewer people while keeping more profits.
Companies will always keep all the savings and pass on all the expenses. That’s just how they operate. You’re not going to be able to change that system short of a revolution.
That’s what change the system means
3 months ago: Everyone’s going to lose their jobs!
Today: Generative AI’s dead!
More realistically: Generative AI is a tool that will gradually get better over time. It is not universally applicable, but it does have a lot of potential applications. It is not going to take over the world, nor will it just suddenly go away.
That’s pretty much been my take from the beginning. My main concerns were and still are:
- IP law, specifically copyright infringement
- correctness - ChatGPT makes stuff up
- detection - esp for school
My main fear was that it would be more useful for scammers and fraudsters than legitimate uses because of the above issues. I still have those concerns.
With any new technology that people say well change the world overnight, take a step back and think it through. For example:
- self driving cars - we still have taxis, Uber, etc, so it hasn’t taken over despite being here for years
- robotics in manufacturing - it’s incredibly expensive to put together and end to end robotic factory, so there are still plenty of manufacturing jobs
- automated fast food - again, the most I’ve seen is increased number of kiosks, that’s it
And so on. People freak out about new tech, then a couple years later they realize that it’s not “finished” and there will be plenty of time to adapt. Unless we recover an alien spaceship or something, that’s just not how technology progresses. Eventually generative AI will redically change our society, but it’ll take decades, so by the time your job is threatened, you’ll be ready to retire.
Kinda is, sure. The problem is when you become overly reliant on the tech without it being reliable. It’s also kinda bad when it causes you to lose skills that you need to maintain it or further it.
Ultimately, generative AI are tools, not magic. We’re now past the hype phase and are now at the leveling out phase of the S-curve as people realizes that these things are limited.
I think ChatGPT is mostly going to be used as an automated copywriter for emails and resumes and such, whereas diffusion models will find their way into digital artists’ workflow.
Life goes on.
I think they have some areas where they’re very useful, but beyond those areas they’re only OK at best. They don’t come close to living up to the hype, which is mostly based on “the next version will be mind blowing!”.
They are a new type of app, nothing more. New types of apps can be extremely useful, and make a lot of tasks easier, e.g. spreadsheets. I would say at best generative AI is as game changing as spreadsheets were, but maybe less.
The hype machine wants us to believe they are as revolutionary as the PC itself, or the car. In fact 10 times as revolutionary! I just don’t buy it… at least not in the foreseeable future.
There was this point where VR gaming seemed like an inevitable successor to traditional gaming. It was everywhere and improving rapidly. There were core concerns, but most felt that those could be solved with time. The technology had so much potential.
This is how the current AI solutions feel to me right now. There are a small-ish group of people who find them very useful and use them often. There are a large group of people who are currently on the hype bandwagon, talking about all the potential they hold. But currently they have yet to truly hit mainstream use.
With VR, all that hype and potential seems largely dead. The promised advancements haven’t seemed like enough to take over from traditional games, the fundamental issues haven’t been fixed because they’re too hard or too costly to fix.
I’m still unsure if AI will go this same route, or if it will eventually break into more mainstream. I think probably the most likely route is something like how Siri/Alexa worked out. Some people use voice assistants all the time, others basically never do. They never quite fully delivered on the revolution they promised, but they were useful enough to stick around. That’s how I feel about the current AI approach.
I think long term we’ll get some other approach that will once again kick off the AI hype machine, but the current AI approach is only going to find limited success because it’s going to be really, really hard to get it to a place where you can reasonably trust the output.
I can’t believe this tech bubble will burst. All the other ones have fared so well.
Genuine question: How hard is it to fix A.I. Hallucinations?
I’m no expert, so take what I’m about to say with a grain of salt.
Fundamentally, a LLM is just a fancy autocomplete; there’s no source of knowledge it’s tapping into, it’s just guessing words (though it is quite good at it). Correspondingly, even if it did have a pool of knowledge, even that can’t be perfect, because the truth is never quite so black and white in many areas.
In other words, hard.
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“If hallucinations aren’t fixable, generative AI probably isn’t going to make a trillion dollars a year,” he said. “And if it probably isn’t going to make a trillion dollars a year, it probably isn’t going to have the impact people seem to be expecting,” he continued. “And if it isn’t going to have that impact, maybe we should not be building our world around the premise that it is.”
Well he sure proves one does not need an AI to hallucinate…
maybe we should not be building our world around the premise that it is
I feel like this is a really important bit. If LLMs turn out to have unsolvable issues that limit the scope of their application, that’s fine, every technology has that, but we need to be aware of that. A fallible machine learning model is not dangerous; AI-based grading, plagiarism checking, resume-filtering, coding, etc. without skepticism is dangerous.
LLMs probably have very good applications that could not be automated in the past but we should be very careful of what we assume those things to be.
Isn’t ChatGPT’s launch only less than 6 months old or something…
Reminds me of the article saying open ai is doomed because it can only last about thirty years with its current level of expenditure.
OpenAI must evolve into serving something other than generative AI.
The compute bills for OpenAI are crazy. They would need more paying customers to try and at least keep the service somewhat viable.
https://futurism.com/the-byte/chatgpt-costs-openai-every-day
