The argument for current LLM AIs leading to AGI has always been that they would spontaneously develop independent reasoning, through an unknown emergent property that would appear as they scale. It hasn’t happened, and there’s no sign that it will.
That’s a dilemma for the big AI companies. They are burning through billions of dollars every month, and will need further hundreds of billions to scale further - but for what in return?
Current LLMs can still do a lot. They’ve provided Level 4 self-driving, and seem to be leading to general-purpose robots capable of much useful work. But the headwinds look ominous for the global economy, - tit-for-tat protectionist trade wars, inflation, and a global oil shock due to war with Iran all loom on the horizon for 2025.
If current AI players are about to get wrecked, I doubt it’s the end for AI development. Perhaps it will switch to the areas that can actually make money - like Level 4 vehicles and robotics.
Self driving uses LLMs? Or a specific type of AI? If it’s LLM I wouldn’t trust it on a side street, since that’s not what a language model is designed for.
No, self-driving cars don’t use Large Language Models, they don’t need to process language at all.
I mean, they would need to if they got good enough. Rare or obscure road signs that are just text. But self driving cars haven’t even perfected how to take a turn correctly.
The fundamental architecture of an LLM is used across all these services - and that’s reaching its limits.
I get that neural networking itself is used, but I doubt they’re using specifically a LLM and fine tuning it for driving purposes. Pattern matching and fuzzy logic for inputs of driving conditions is a lot different than prompting a textual or visual response.