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Agree, humans can "arrive at a reasonable approximation of the truth" even without the direct knowledge of the capital of Connecticut. A human has some other in

Agree, humans can "arrive at a reasonable approximation of the truth" even without the direct knowledge of the capital of Connecticut. A human has some other interesting data points that allow them to probabilistically guess that the capital of Connecticut is not Moscow and those might be things like: - Moscow is a Russian city, and they probably aren't a lot of cities in the US that have strong Russian influences especially in the time when these cities might have been founded - there's a concept of novelty in trivia, whereby the more unusual the factoid, the better the recall of that fact. If Moscow were indeed the capital of Connecticut, it seems like the kind of thing I might've heard about since it would stand out as being kind of bizarre. Noticeably this type of inference seems to be relatively distinct from what LLMs are capable of modeling.

int_19h 2y ago
I was actually quite surprised at the ability of top-tier LLMs to make indirect inferences in my experiments. One particular case was an attempt to plug GPT-4 as a decision maker for certain actions in a video game. One of those was voting for a declaration of war (all nobles of one faction vote on whether to declare war on another faction). This mostly boils down to assessing risk vs benefits, and for a specific clan in a faction, the risk is that if the war goes badly, they can have some of their fiefs burned down or taken over - but this depends on how close the town or village is to the border with the other faction. The LM was given a database schema to query using SQL, but it didn't include location information. To my surprise, GPT-4 (correctly!) surmised in its chain-of-thought, without any prompting, that it can use the culture of towns and villages - which was in the schema - as a sensible proxy to query for fiefs that are likely to be close to the potential enemy, and thus likely to be lost if the war goes bad.
danielbln 2y ago
I don't understand, this sort of inference is not an issue for an LLM. Have you tried?
adamc 2y ago
Another might be that usually state capitals are significant cities in their state -- not necessarily the biggest, but cities you have at least heard of. Given that I have never heard about Moscow in Connecticut, it seems unlikely (not impossible, but).

int_19h 2y ago

I was actually quite surprised at the ability of top-tier LLMs to make indirect inferences in my experiments. One particular case was an attempt to plug GPT-4 as a decision maker for certain actions in a video game. One of those was voting for a declaration of war (all nobles of one faction vote on whether to declare war on another faction). This mostly boils down to assessing risk vs benefits, and for a specific clan in a faction, the risk is that if the war goes badly, they can have some of their fiefs burned down or taken over - but this depends on how close the town or village is to the border with the other faction. The LM was given a database schema to query using SQL, but it didn't include location information. To my surprise, GPT-4 (correctly!) surmised in its chain-of-thought, without any prompting, that it can use the culture of towns and villages - which was in the schema - as a sensible proxy to query for fiefs that are likely to be close to the potential enemy, and thus likely to be lost if the war goes bad.

danielbln 2y ago

I don't understand, this sort of inference is not an issue for an LLM. Have you tried?

adamc 2y ago

Another might be that usually state capitals are significant cities in their state -- not necessarily the biggest, but cities you have at least heard of. Given that I have never heard about Moscow in Connecticut, it seems unlikely (not impossible, but).