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The other mainstream definition comes from Peter Norvig , author of the most mainstream textbook on artificial intelligence (or at least the most cited). He def
by dr_dshiv 3y ago
The other mainstream definition comes from Peter Norvig , author of the most mainstream textbook on artificial intelligence (or at least the most cited). He defines AGI relative to narrow AI, using the development of general purpose digital computing as an analogy. Before general purpose digital computing, there were a wide range of specialized narrow forms of computing.
Thus, he concludes that AGI is already here (it is similarly general purpose) but in the early days.
I find his view pragmatic and helpful. https://www.noemamag.com/artificial-general-intelligence-is-already-here https://www.noemamag.com/artificial-general-intelligence-is-...
- pointlessone 3y agoI don't buy this argument. Specifically, Modalities. The claim is that "[b]y using modality-specific tokenizers or processing raw data streams, frontier models can, in principle, handle any known sensory or motor modality". Sure, you may get some sort of output but I'm quite confident you won't get anything useful without training the model on that kind of input. We barely started sticking narrow AI together. E.g. ChatGPT (LLM) can invoke Dall-e (text to image). Maybe AGI will turn out to be a bunch of narrow AIs in a trench coat. So far I haven't seen such a system. Tasks claim is a little stretched, too. For example, simple arithmetic. Does model actually do arithmetic or does it do text generation and the right answer just happens to be the most likely next token? Can we reliably tell one from the other to claim that model actually perform tasks other than just text generation?