Which of the following sounds more reasonable?
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I shouldn’t have to pay for the content that I use to tune my LLM model and algorithm.
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We shouldn’t have to pay for the content we use to train and teach an AI.
By calling it AI, the corporations are able to advocate for a position that’s blatantly pro corporate and anti writer/artist, and trick people into supporting it under the guise of a technological development.
I think it’s the same reason the CEO’s of these corporations are clamoring about their own products being doomsday devices: it gives them massive power over crafting regulatory policy, thus letting them make sure it’s favorable to their business interests.
Even more frustrating when you realize, and feel free to correct me if I’m wrong, these new “AI” programs and LLMs aren’t really novel in terms of theoretical approach: the real revolution is the amount of computing power and data to throw at them.
Even more frustrating when you realize, and feel free to correct me if I’m wrong, these new “AI” programs and LLMs aren’t really novel in terms of theoretical approach: the real revolution is the amount of computing power and data to throw at them.
This is 100% true. LLMs, neural networks, markov chains, gradient descent, etc. etc. on down the line is nothing particularly new. They’ve collectively been studied academically for 30+ years. It’s only recently that we’ve been able to throw huge amounts of data, computing capacity, and time to tweak said models to achieve results unthinkable 10-ish years ago.
There have been efficiencies, breakthroughs, tweaks, and changes over this time too, but that’s just to be expected. But largely its just sheer raw size/scale that’s just been achievable recently.
Okay, I’m glad I’m not too far off the mark then (I’m not an AI expert/it’s not my field of study).
I think this also points to/is a great example of another worrying trend: the consolidation of computing power in the hands of a few large companies. Without even factoring in the development of true AI/whether that can or will happen anytime soon, the LLMs really show off the massive scale of both computational power consolidation AMD data harvesting by only a very few entities. I’m guessing I’m not alone here in finding that increasingly concerning, particularly since a lot of development is driving towards surveillance applications.
LLMs aren’t really novel in terms of theoretical approach: the real revolution is the amount of computing power and data to throw at them.
This is 100% true. LLMs, neural networks, markov chains, gradient descent, etc. etc. on down the line is nothing particularly new. They’ve collectively been studied academically for 30+ years.
Well LLMs and particularly GPT and its competitors rely on Transformers, which is a relatively recent theoretical development in the machine learning field. Of course it’s based in prior research, and maybe there even is prior art buried in some obscure paper or 404 link, but if that’s your measure then there is no “novel theoretical approach” for anything, ever.
I mean I’ll grant that the available input data and compute for machine learning has increased exponentially, and that’s certainly an obvious factor in the improved output quality. But that’s not all there is to the current “AI” summer, general scientific progress played a non-minor part as well.
In summary, I disagree on data/compute scale being the deciding factor here, it’s deep learning architecture IMHO. The former didn’t change that much over the last half decade, the latter did.
Now as I stated in my first comment in these threads, I don’t know terribly much about the technical details behind current LLM’s and I’m basing my comments on my layman’s reading.
Could you elaborate on what you mean about the development of of deep learning architecture in recent years? I’m curious; I’m not trying to be argumentative.
The funniest thing I’ve seen on this is the ChatGPT CEO, Altman, talking about how he’s a bit afraid of what they’ve created and how it needs limitations – and then when the EU begins to look at regulations, he immediately rejects the concept, to the point of threatening to leave the European market. It’s incredibly transparent what they’re doing.
Unfortunately I don’t know enough about the technology to say if the algorithms and concepts themselves are novel, but without a doubt they couldn’t exist without modern computing power capabilities.
I can tell for a fact that there’s nothing new going on. Only the MASSIVE investment from Microsoft to allow them to train on an insane amount of data. I am no “expert” per se, but I’ve been studying and working with AI for over a decade - so feel free to judge my reply as you please
nothing new going on
I can’t think of anything less accurate to say about LLMs other than that they’re a world-ending threat.
This is a bit like saying “The internet is a cute thing for tech nerds but will never go mainstream” in like 1995.
nothing new going on
Uhhhh the available models are improving by leaps and bounds by the month, and there’s quite a bit of tangible advancement happening every week. Even more critically the models that can be run on a single computer are very quickly catching up to those that just a year or two ago required some percentage of a hyperscaler’s datacenter to operate
Unless you mean to say that the current insane pace of advancement is all built off of decades of research and a lot of the specific advancements recently happen to be fairly small innovations into previous research infused with a crapload of cash and hype (far more than most researchers could only dream of)
The concepts themselves are some 30 years old, but storage capacity and processing speed have only recently reached a point where generative AI outperforms competing solutions.
But regarding the regulation thing, I don’t know what was said or proposed, and this is just me playing devil’s advocate: but could it be that the CEO simply doesn’t agree with the specifics of the proposed regulations while still believing that some other, different kind of regulation should exist?
Certainly could be, but probably an optimistic take. Most likely they’re just trying to do what corporations have been doing for ages, which is to weaponize government policy to prevent competition. They don’t want restrictions that will materially impact their product, they want restrictions that will materially impact startups to make it more difficult for them to intrude on the established space.
It also plays into the hype cycle they’re trying to create. Saying you’ve made an AI is more likely to capture the attention of the masses then saying you have a LLM. Ditto that point for the existential doomerism that they ceo’s have. Saying your tech is so powerful that it might lead to humanity’s extinction does wonders in building hype.
Agreed. And all you really need to do is browse any of the headlines from even respectable news outlets to see how well it’s working. It’s just article after article uncritically parroting whatever claims these CEO’s make at face value at least 50% of the time. It’s mind-numbing.
I think you are likely right, but it’s more general than just about training costs. The term “AI” carries a ton of baggage, both good and bad.
To some extent, I think we also keep pushing back the boundary of what we consider “intelligence” as we learn more and better understand what we’re creating. I wonder if every future tech generation will continue this cycle until/unless humanity actually does create a general artificial intelligence–every iteration getting slightly closer but still falling short of “true” AI, then being looked at as a disappointment and not worthy of the term anymore. Rinse and repeat.
I’m not sure what you’re trying to say here; LLMs are absolutely under the umbrella of AI, they are 100% a form of AI. They are not AGI/STRONG AI, but they are absolutely a form of AI. There’s no “reframing” necessary.
No matter how you frame it, though, there’s always going to be a battle between the entities that want to use a large amount of data for profit (corporations) and the people who produce said content.
On the flip side, the same battle is also fought between giant corporations that amass intellectual property and the people who want to actually use that intellectual property instead of letting it sit in some patent troll’s hoard until a lawsuit op presents itself. Seeing as there are quite a few reasonably decent open-source LLMs out there like Koala and Alpaca also training on data freely available on the Internet, I’m actually rooting for the AI companies in this case, in the hopes of establishing a disruptive precedent.
True, and this is the annoying thing about people unqualified to talk about AI giving their opinions online. People not involved in the industry hear “AI” and expect HAL-9000 or Ava from Ex Machina rather than the software that the weather service uses to predict if it will rain tomorrow, or the models your doctor uses to help determine your risk of Heart Disease.
This is compounded further when someone makes a video simplifying what an LLM is and mentioning that the latest models use it, which leads to the chimes of “bUt iT’S jUsT aN Llm BrO iTs nOt AI” and “ItS jUsT a LOaD oF DaTa aND aLGorItHMs, tHaTs NoT AI”. A little bit of knowledge is a dangerous thing.
This is actually exactly what I mean. Most people hear AI and envision something much, much more complex. It’s easier to argue that HAL-9000 is like a human and should therefore be allowed to freely view book content like a human, versus argue that a sophisticated LLM is like a human and should be allowed to freely view books like a human. That’s moreso where I’m coming from. And politicians are stupid enough to pass laws envisioning these as HAL-9000.
Both of those statements are reasonable. You shouldn’t have to pay to utilize anything you scrape from the internet, so long as you don’t violate copyright by redistributing it
Honestly, I see 0 difference. I think you are suggesting that somehow it is more logical to give information to AI for free sounds more reasonable than to LLM (which is absolutely AI). I see no reason at all to believe so. Maybe you can elaborate?
