Comment on Major shifts at OpenAI spark skepticism about impending AGI timelines
Petter1@lemm.ee 1 month agoSo, the only problem what stops LLM from getting AGI is the lack of an efficient method of train the LLM on the device it is used?
If that what you wanted to say 😁 I agree
MentalEdge@sopuli.xyz 1 month ago
Hardly.
How did you interpret the issues inherent in the structure of how LLMs work to be a hardware problem?
An AGI should be able to learn the basics of physics from a single book, the way a human can. But LLMs need terabytes of data to even get started, and once trained, adding to their knowledge by simply telling them things doesn’t actually integrate that information into the model itself in any way.
Even if your tried to make it work that way, it wouldn’t work, because a single sentence can’t significantly alter the model to match way humans can internalise a concept being communicated to them in a single conversation.
Petter1@lemm.ee 1 month ago
Not a hardware problem, the learning algorithm just needs to be approved to be able to filter input like humen brain filter (which includes fact checking and critical analysis of input while training) i bet 99% of the data AI are trained on is hust useless data which should have been filtered out in the training process, just as humans do.
MentalEdge@sopuli.xyz 1 month ago
Your claiming all we need to do is “tweak the code a little” so it’s already capable of human-level critical thinking before it even starts training?
You’re basically saying that all we need to make an AGI using machine learning, is an already functioning AGI.
Petter1@lemm.ee 1 month ago
Hu? No, that is not what I meant, well it surly can be a machine learning based filter, but why has it to be AGI? This filtering is a job that we can give to a “traditionally” trained AI or some human genius algorithm crafter finds a way to achieve this using pure logic 🤷🏻♀️ For me it feels like this is the way, it goes.