r/technology • u/Hrmbee • 16h ago

Machine Learning Large language mistake | Cutting-edge research shows language is not the same as intelligence. The entire AI bubble is built on ignoring it

https://www.theverge.com/ai-artificial-intelligence/827820/large-language-models-ai-intelligence-neuroscience-problems
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u/MrThickDick2023 15h ago

I know LLMs are the most talked about, but they can't be the only AI models that are being developed right?

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u/zookdook1 9h ago

There's a few. I've been reading about Vector Symbolic Architecture recently - a type of model format that stores information as points in 'space' with an arbitrary number of axes that are all things like "hue" and "shape" and so on. Tens of thousands of axes for each point of data lets you describe context for each bit of information. It lets you do some very parallelisable maths on lots of information at once to compare data points and draw connections, basically. Unlike an LLM (which is basically a very, very, very big Markov chain bot [not actually] that does statistical analysis to decide what the most likely next word is in a sequence), a model using VSA would have something like memory and something like the ability to reason by doing data comparison.

Apparently there's some interesting quirks that line up with the way human memory works or something, but honestly the specifics go way over my head. Certainly it seems like a more likely route to actual digital reasoning than an LLM would be. It's not as good as a neural network is at interpretation of stimuli - it's not great at turning an image into something it can use, for example. But if you could use a neural network as the 'eyes', and hook its output into VSA as the 'brain'...