https://youtu.be/wPonuHqbNds?t=1199
Chomsky's apparently erroneous critique of Transformer-based LLMs is actually correct in the larger sense. His apparent error? Ask ChatGPT the following: "What is the grammar diagram for the sentence: The friends of my brothers are in England." Contrary to what Chomsky says, it will produce the correct structure and, indeed, if asked "Who is in England, my brother or their friends?" It will answer correctly. The larger sense in which Chomsky is correct is given in the paper "Neural Networks and the Chomsky Hierarchy". See, in particular, Figure 1, which classifies Transformers as at the bottom rung in the Chomsky Hierarchy of grammars. The reason for this classification is similar to the reason that diagram places RNNs just above Transformers despite the fact that topologically speaking, they are capable of emulating a universal Turing machine (which is at or next to the top grammar, depending on how strict one wants to be): The pragmatic limits on gradient descent training algorithms combined with that of attempting to represent a UTM's writable store in RNN form. Transformers can, within the context length they provide, learn grammars with recursion depth to some extent (much shorter than their context length) -- but aside from the limited recursion per sentence, there is also the fact that that number of parameters goes up as the square of the context length, which makes total document comprehension subject to limits that natural language understanding is not. This distinction becomes crucial when the field of AI ethics refuses to address the IS vs OUGHT distinction head-on and, instead, comes up with all manner of unprincipled "metrics" that they use to "quantify" properties of LLMs such as "bias" or "safety" or "toxicity" or "hallucination" or... the list goes on and on. By conflating IS with OUGHT they commit the first and most egregious transgression against ethics and they even do so in the name of "ethics". AIs that cannot comprehend the cognitive _structure_ of the _entire_ corpus on which they are trained, cannot critically examine the utterances contained therein for self-consistency. That means they are incapable of _constructing_ truth even as defined _relative_ to the corpus as the universe of observations being modeled. I one pointed Chomsky to his colleague, Marvin Minsky's final plea to the field of AI, that they take seriously Algorithmic Information Theory's power in discerning truth. Minsky was so forceful in his admonition that he recommended everyone spend the rest of their lives studying it. Chomsky's response? People should take Minsky's advice. ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/Tc63b3ba66d5ff6e7-M57c8e2476636fdf536dff426 Delivery options: https://agi.topicbox.com/groups/agi/subscription
