cross-posted from: https://lemmy.world/post/15864003
You know how Google’s new feature called AI Overviews is prone to spitting out wildly incorrect answers to search queries? In one instance, AI Overviews told a user to use glue on pizza to make sure the cheese won’t slide off (pssst…please don’t do this.)
Well, according to an interview at The Vergewith Google CEO Sundar Pichai published earlier this week, just before criticism of the outputs really took off, these “hallucinations” are an “inherent feature” of AI large language models (LLM), which is what drives AI Overviews, and this feature “is still an unsolved problem.”
They’ve (Big Tech) have sunk so much money and public perception into this, I’m not sure if they can back down. Most likely, the backends of these “AI” will be stripped out and replaced with various well-understood techniques for generating accurate answers (most especially the technique of “paying call center workers pennies to do the work”). The LLMs might remain to act as a “prettifier” pass to make the output sound conversational.
That will buy a few more years of lying to people about how close the AI overlords are while they try to find whatever magic will make them appear to work. But the current model just isn’t sustainable. Companies are pouring truly insane amounts of power (and money, and water) into these machines to get worse results than ever. There isn’t infinite money to speculate and hold out on a magical god-level AI making you king of the earth, but apparently every billionaire is locked in a perverse prisoner’s dilemma to be the first to destroy the planet trying.
I keep calling it magic too because it really will have to be. The major problem of AI is that it isn’t well defined. What the shareholders want is a perfect machine that can answer any question, replace any job, and is never wrong. That doesn’t exist. Humans can’t be infallible so how can we make a machine that is? We can make machines that do amazing things, but not literal magic and that’s what “AI” needs to be to recoup these investments.
Yea I think you’re onto something there with the weird and toxic inertia here. Part of that, I suspect, is that the kind of work and profession that was previously doing the sorts of things that AI will be used for now, namely Data Science and similar, was already a nebulous profession already in transition, which could be simply wiped away over 2-5 years of AI hype. That is, there may literally be no “going back” because what was done before, in many cases, will have been institutionally forgotten or pushed out as a career people are willing to invest in. Which would mean, as you say, whatever persists will cling to the whole AI thing in some way however corrupted and disingenuous.