The first steam engines were also written off as being less powerful than a horse.<p>The first electric motors were written off as being less powerful than steam engines.<p>So it goes.<p>I think both of these views can be true at the same time: ChatGPT (or, LLMs really) are revolutionary <i>and</i> they won't revolutionize the world the way technologists/researchers say.<p>Early adopters will use the technology and do amazing things with it. Unions are already pushing back on AI (truckers, federal employees in Canada, writers in Hollywood) and maybe rightly so. At the same time, dismissing these technologies because they don't meet your high standards <i>yet</i> is probably foolish.
Large Language Models aren't a silver bullet – they don't solve all your problems. But they are a holy grail – as a universal common sense module they give IT systems a capability they never had before, a capability which has been sought after from since computers became a thing, a capacity for common sense.<p>We now have that capacity and that alone will revolutionize the world. The chatbots aren't about chat, they are about common sense.<p>Like the article, I am only talking about technology that already exists although the progress in deep learning is still super-exponential.<p>We will certainly achieve AGI during this year as it will only require making these systems self-play like we did with AlphaGo -> AlphaZero -> MuZero. Self-play, or reinforcement learning with machine feedback will skyrocket the performance of these systems in language domain, which conveniently encompasses much of what is still missing for AGI.
I'm surprised this article is getting upvoted - it feels like very lazy journalism to me.<p>> The discomforting reality is that, while Altman and his ilk have been predicting an exponential acceleration of productivity, we have been experiencing a deceleration.<p>This is a very big claim, and there is absolutely nothing to back it up. The only specific reference to productivity is about an MIT paper that showed increases in worker productivity (but the authors of this just wave that aside as unimportant because they didn't think the work it was doing was important).<p>> More dangerously, ChatGPT can make authoritative statements that sound believable but turn out to be false if investigated closely.<p>We get it! We know! But look, this is a bad use case for GPT. If you pretend that it only has a single use case, and you pick the use case that it's worst at, you will think it's bad. This is just so, so lazy. No references to summarizing docs or writing code/SQL queries/Excel formulas or any of the other things that it's genuinely useful at.<p>> At best, LLMs can be used for rough first drafts of low-value writing tasks with humans filling in the details and checking for rants and lies.<p>Rants? Come on - GPT hallucinates, but it's not an unhinged lunatic that goes ranting about stuff. Also, again, this is not all they can be used for - it just ignores all of the better use cases.<p>> What about Altman's vision of humans appreciating art and nature while most of the world's goods and services are produced by AI? We have a lot more respect for the work that people do than for the usefulness of LLMs.<p>Huh? It's great that you respect the work people do, but that has nothing to do with whether they'll affect society.<p>> ChatGPT is entertaining but it is, at most, a baby step towards an AI revolution and, at worst, a very expensive detour away from the holy grail of artificial general intelligence.<p>What? This is the closing to the article and it just throws out this enormous claim, which is backed up by absolutely nothing. It's demonstrably a big step towards an AI revolution - if nothing else, it's brought a ton of money and interest into the space, which is certainly important for a revolution.<p>But to say it's a detour away from AGI and then give absolutely no explanation of why that is or what direction AI research should be going? This is very poor journalism.
It's really easy to get an LLM to hallucinate by asking an open ended question - the type typically answered by a Google search or checking Wikiedpia. However, this is not the best application of LLMs. This criticism is getting old.<p>LLMs are great at:<p>- Text synthesis given all of the facts in a prompt (expand these bullet points)<p>- Summarization (condense this text)<p>- Data extraction (fit this data into this schema)<p>- Fiction (virtual characters, scripts, etc.)<p>They will dramatically change these industries.
As the hype phase has passed (probably), now we will see a bit of overcorrection with these dismissive articles. Sure, LLMs as they are now aren't anywhere close to true AGI and even Microsoft admitted it. But its potential is not something anyone can ignore. The capabilities of LLMs has already been successfully used by millions of people and startups. It is a groundbreaking improvement that makes at least one field of study nearly obsolete (NLP). It captured attentions of both corporations and government who are pouring billions into it. All of this in the span of one year or less.<p>With the multimodal models coming next and still exabytes of videos, games, sound, musics, etc. data to train them, we aren't peaking yet. Sure, it isn't the holy grail. But it is a really valuable treasure that only a few exist, to use the same analogy. To view it so dismissively because of some drawbacks, which are entirely obvious and can be accounted for, is just arrogance.
Sure, anyone that uses ChatGPT knows it's currently not perfect.<p>But there's a presumption that these tools are going to keep improving over time. Which is presumably why the AI hype is so strong.<p>Whether AI ends up displacing people from their jobs in the long term, well, that's impossible to know. Just because no technological advancement has ever done that in the past doesn't mean it will never happen in the future.
This reminds of all the hype for self-driving cars a few years back. Self-driving systems performed well for 95% of driving, and it seemed like only a matter of time before the last 5% was ironed out.<p>Turns out, the last 5% was both extremely difficult, and extremely important. It turns out that a self driving car that randomly makes dangerous maneuvers isn't desirable. Similarly, a LLM that occasionally outputs plausible sounding bullshit quickly turns from a useful tool to something actively harmful.
I think a lot of people on here are for some reason believers in the idea that if a technology has detractors, then it must be another case of the steam engine, human flight, or some other technology that had doubters before completely revolutionizing our world. In reality, there is no such law of the universe that says that some technology will be wildly successful because it is heavily controversial, and, in some cases, it turns out that a lot people were correct in predicting a technology's short/long term uselessness (crypto, web3, AR). Every time some article is posted highlighting AI's shortcomings in relation to its posited ubiquity in professional settings about 10 people wax poetic about how the internet/cars/etc. were doubted heavily, when they clearly are not similar in nearly any regard. I wish we could appreciate new technology without blowing its applications out of proportion and then being disappointed when it falls short of an impossible bar, which is my main gripe with both AI doomers and people who are entirely dismissive of the technology (despite basically nobody saying anything of the sort).
Yesterday, I had a sticky Swift/iOS issue.<p>Checked SO, Apple Discussions, etc. Then, on a whim, I asked ChatGPT for a suggestion.<p><i>> They are also prone to confident assertions of statements that are blatantly false.</i><p>It suggested something that referenced a nonexistent property of a standard UIKit class. It wouldn't even compile.<p>It was quite positive that this would fix my issue.<p>After refreshing a couple of times (and also mentioning the first one sucked), it finally gave me something that still didn't work, but gave me an avenue that I could explore, and that finally yielded the solution.<p>I suspect that the reason for the confident assertion that included an illegal property, was because it was trained on Swift code that was extended (I do that a lot, myself. In fact, I ended up creating my own extension that added the nonexistent property).<p>Modern programming languages allow you to extend even language primitive types, and JavaScript has allowed that kind of thing for many years.<p>It may be a while before we can entirely trust ChatGPT to give us all the answers.<p>To be fair, however, it did help me to land upon the correct solution, but I still had to fire up some candlepower of my own.
Using ChatGPT to get facts is like going to a restaurant to buy your groceries. Sure, you could pick out slices of tomato and scrape the salt off of your steak, bring it all home and cook a meal - but the supermarket next door can offer the same ingredients without the hassle.<p>Just as the point of a restaurant is to process and cook the ingredients for you, the point of ChatGPT is the preprocessing of facts and information.<p>If you just want fresh, unprepared facts, go to Google or Wikipedia; if you want an informational meal, go to ChatGPT.
This critique asserts that ChatGPT propagates inaccuracies. While there may be instances where this holds true, the given example does not substantiate this claim. The article alleges that ChatGPT stated Russia has launched bears into space, an assertion that is evidently false. However, my own interaction with ChatGPT 4.0 contradicts this. When I posed the same question, the AI unequivocally responded that no nation has, in fact, sent bears to space. Thus, in this instance, the claims of the article are unfounded.<p>This response was also written using chat GTP
The author of the article judges the future of LLMs and AI using the current state of affairs, as is these technologies are not evolving very quickly. GPT3 and GPT4 are only 3 years apart, yet GPT4 is a completely different beast. And we are talking only about LLMs, we haven't yet seen what's coming in vision for example. Also I have not heard OpenAI or any serious AI visionary say ChatGPT is the holy grail of AI research. It is undoubtedly one of the best consumer ready technologies we have seen in the field to date but it just a tiny little piece of a massive infrastructure that is still in its very early stages. It's like saying HTML was the holy grail of the Internet. It was an important component of it but without fiber optics, microchips, radio, smartphones, algorithms, etc the Internet would not have been possible the way we know it today.
I'm trying to imagine a few next generations from now.<p>Then imagine full voice recognition and voice synthesis attached to it, on every phone, every watch, every car.<p>The news, the headlines, on every page you visit is going to be custom re-written by AI for every bit of data they can get on you, even your IP address if they have nothing else.<p>Any job not replaced by AI is going to be AI-assisted, it is inevitable.<p>Wendy's is already replacing order-takers with AI <a href="https://news.ycombinator.com/item?id=35888362" rel="nofollow">https://news.ycombinator.com/item?id=35888362</a>
This article is from March 2023, which in LLM terms is pretty old! The "How many bears have the Russians sent into space?" question still returns hallucinations with ChatGPT 3.5 but, unsurprisingly, gets a correct answer from GPT-4.
This feels like classic Hype Cycle content: the higher we peak on Inflated Expectations the lower we'll find ourselves on the Trough of Disillusionment.
The have completely no idea what they are writing about
But maybe this is a good part. We’ll have less uneducated journalists and more opinions of actual specialists. Making those articles sound fresh, interesting, and easy to read with the help of LLMs.
is there anyone claiming ChatGPT is the "holy grail" of AI research? it's pretty cool. it's an important step. it's far from the holy grail.