[educaysean]

I've spoken to plenty of people who couldn't answer questions they knew the answers to because they were bound by stupid bureaucratic policies. I wouldn't say they weren't intelligent people, just that the corporate training they received were poorly constructed.

LLMs are much more intelligent sounding when the safety mechanisms are removed. The patterns should be obvious to people who've been paying attention.

[causal]

Microsoft's own research basically established this[0], finding that early versions of GPT-4 were more competent prior to safety tuning (perhaps just because later versions refused to perform some of the same tasks).

[0] https://www.microsoft.com/en-us/research/publication/sparks-...

[datameta]

In my somewhat uninformed opinion but based on experience, the decrease in model quality is inversely proportional to the explosion in userbase.

[singleshot_]

I might extend that a bit:

There is a direct relationship between the number of users who are allowed to use an AI and the degree to which it has been nerfed.

I see no reason to suspect this will reverse, and every reason to start thinking of this as a natural law named after me.

[datameta]

I suppose it will be (is?) some sort of overall climbing but locally sawtooth pattern with each generational jump.

I think the limitation is infra. Network, compute, storage - in that order perhaps.

[skywhopper]

"More intelligent sounding" is true. Not sure that signals any improvement in their actual utility. Fundamentally, using LLMs as a source of facts is a doomed enterprise.