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This is a terrible attitude which unfortunately is all too common in the industry right now: evaluating AI/ML systems not based on what they can do, but what th
by lambda 1y ago
This is a terrible attitude which unfortunately is all too common in the industry right now: evaluating AI/ML systems not based on what they can do, but what they hypothetically might be able to do.
The thing is, with enough magical thinking, of course they could do anything. So that let's unscrupulous salesmen sell you something that is not actually possible. They let you do the extrapolation, or they do it for you, promising something that doesn't exist, and may never exist.
How many years has Musk been promising "full self driving", and how many times recently have we seen his cars driving off the road and crashing into a tree because it saw a shadow, or driving into a Wile E Coyote style fake painted tunnel?
While there is some value in evaluating what might come in the future when evaluating, for example, whether to invest in an AI company, you need to temper a lot of the hype around AI by doing most of your evaluation based on what the tools are currently capable of, not some hypothetical future that is quite far from where they are.
One of the things that's tricky is that we have had a significant increase in the capability of these tools in the past few years; modern LLMs are capable of something far better than two or three years ago. It's easy to think "well, what if that exponential curve continues? Anything could be possible."
But in most real life systems, you don't have an unlimited exponential growth, you have something closer to a logistic curve. Exponential at first, but it eventually slows down and approaches a maximum asymptotically.
Exactly where we are on that logistic curve is hard to say. If we still have several more years of exponential growth in capability, then sure, maybe anything is possible. But more likely, we've already hit that inflection point, and continued growth will go slower and slower as we approach the limits of this LLM based approach to AI.
- purple_basilisk 1y agoThis. The most important unknown about AI is when will it plateau.
- HPMOR 1y agoWhy will it plateau?
- sumeno 1y agoBecause every technology does eventually
- red75prime 1y agoWhat is the defining factor that makes all technologies plateau unlike evolution that seems to be open-ended? Technologies don't change themselves, we do. And what is the endgame for AI?
- chipsrafferty 1y agoWhat? Evolution is specifically known for getting caught in local maximums. Species have little evolutionary pressure to get better when they are doing great, like a species with no predators on an island. The only thingsdriving evolution for that creature is natural selection towards living longer and getting less diseases, dying in less accidents, stuff like that. And those aren't specific enough and don't pressure on a time basis so there isn't much pressure to improve beyond the natural lifespan. Plus, for some cases, living longer is not really the goal, it's reproducing more. It's entirely possible, likely even, that maximizing for longevity eventually starts to give a negative effect towards reproduction, and vice versa, so an equilibrium is reached. Also technologies don't develop like evolution really so not sure why you drew that comparison. Technologies plateau for a combination of reasons - too expensive to make it better, no interest in making it better, can't figure out any more science (key people involved leave / die / lose interest, or it's just too difficult with our current knowledge), theoretical limits (like we are reaching in silicon chips). I don't see a lot of similarity with evolution there.
- BobaFloutist 1y agoBecause everything does, eventually.
- SketchySeaBeast 1y agoGiven the shift in focus from back and forth interaction with the AI to giving it a command then waiting as it reads a series self-generated inputs and outputs, I feel like we're at that inflection point - the prompts might appear to be getting smarter because it can do more, but we're just hiding that the "more" it's doing is having a long, hidden conversation that takes a bunch more time and a bunch more compute. This whole "agentic" thing is just enabling the CPU to spin longer.
- hansmayer 1y ago100% this. Actually a lot of (younger) folks don't know that the current LLM "revolution" is the tail end of the last ~20 years of ML developments. So yeah, how many more years? In a way, looking at the costs and complexity to run them, it looks a bit like building huge computers and tvs with electronic tubes in the late 1940s. Maybe there is going to be a transistor moment here and someone recognises we already have a deterministic algorithms we could combine for deterministic tasks, in place of the Slop-Machines...? I dont mind them generating bullshit videos and pictures, as much as the potential they have to completely screw up the quality of software in completely new ways.
- kaycey2022 1y agoThe attitude is typical of crypto grifters or any other grifters. Or if not malign it tends to come from someone who has literally zero experience in the space.