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PaperclipPerfector  1yr ago (text post)   37129 thread views

Culture War Roundup for the week of April 10, 2023

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What's one-shot training performance like for the current models?

I expect that it would perform worse than an average minimum-wage cashier if given a situation like "This is a cantaloupe. Find all the cantaloupes here."

I'd be curious about this too, but it'd be really hard to make apples-to-apples comparisons. How many minimum-wage cashiers could be said to have no experience seeing a cantaloupe in the past, to make a true one-shot attempt at categorizing? What would a proper one-shot categorization test for a human look like anyway? It'd have to be free of any and all context cues that a human could pick up based on all the training they've gone through just living and observing in society.

Maybe artichokes, dragonfruit, bok choi, or whatever is in this meme instead of cantaloupe, then. There are a bunch of fruits and vegetables that many people have never seen before (cut flowers and potted plants are other candidates for this test).

I don't think that a lack of contextual clues is required for training to be considered one-shot. Language models are allowed to know things like mathematics and natural language processing, so I don't have a problem with humans knowing things like biology or cooking.

What do you predict is an average minimum-wage cashier's performance at a task like using a bogus novel arithmetic operation "pointwise multiplication modulo 10, with binary evenness-based carry, left-to-right"?

Granted, it's technically 4-shot. I'd give your cashier 5 examples, because God knows they have other bullshit to deal with.

I expect them to do terribly, and have worse-than-chance results due to giving up and refusing to answer. It's the opposite of "functions that we consider baseline, and accordingly take for granted, are in fact extremely complex and computationally intensive."

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