this post was submitted on 09 Dec 2024
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A bit of a different take than their post, but since they asked:
I've noticed a lot of people use "AI" when they really mean "LLM and/or diffusion model". I can't count the number of times someone at my job has said AI when solely describing LLMs. at this point I've given up on clarifying or correcting the point.
This isn't entirely because LLM is a mouthful to say, but also because it's convenient for tech companies if people don't look at the algorithm behind the curtain (flawed, as all algorithms are) and instead see it as magic.
It's blindingly obvious to anyone who's looked that LLMs and generative image models cannot reason or exhibit actual creativity (c.f. the post about poetry here). Throw enough training data and compute at one and it may be able to multiply better (holy smokes stop the presses a neural network being able to multiply numbers???), or produce obviously bad output x% less of the time, but by this point we've more or less reached the bounds of what the technology can do. The industry's answer is stuff like RAG or manual blacklists, which just serves to hide it's capabilities behind a curtain.
Everyone wants AI money, but classic chatbots don't make money unless they're booking vacations for customers, writing up doctor's notes, or selling you cars.
But LLMs can't actually do this, so in particular any tool in the space has to be uninterrogated enough both to give customers plausible deniability, and to keep the bubble going before they figure it out.
If you use "statistical language model" instead of "AI" in this sentence then people start asking uncomfortable questions about how appropriate it is to expect a mad-libs algorithm trained on 4chan to not be racist.
This is an interesting quote indeed, as expert systems used to be on the forefront of AI; now it's apparently not considered AI at all.
Eventually LLMs will just be considered LLMs, and image generators will just be considered image generators, and people will stop ascribing ✨magic✨ to them; they will join the rank of expert systems, tree search algorithms, logic programming, and everyone else that we just take for granted as another tool in the toolbox. The bubble people will then have to come up with some shinier newer system to attract money.
It really is the same kind of issue faced by the original luddites around factory automation. There the intelligence being artificially replaced was that of experienced weavers, spinners, and other assorted craftspeople instead of programmers, insurance adjusters, clerical staff, and other assorted white-collar professionals but in a social and political sense AI is just a rebranding of automation for the modern economy, and one that more effectively obscures the actual human labor being supplanted. That's a particular bonus for the current bubble because in being vague about what specific labor can be automated they can avoid the kinds of comparisons that make it incredibly obvious that the AI systems aren't actually up to the task. The shift from cottage industry to factories massively increased the sheer volume of goods that could be created, transported, and utilized. (And set the stage for two world wars and the modern age of consumerism which sounds really bad so let me be clear: I like my shiny toys.) The current shift from humans making things to generative AI is trying to replicate that but because of the nature of goods and services we're now talking about it's pretty clear that there simply isn't a comparison. A bolt of cloth is a bolt of cloth, but a book-length statistical prediction just isn't useful or valuable in the same way that an actual book is.