[spathi_fwiffo]

Replace 2 word instruction ('be concise') with a 38 word instruction.

Human can no longer be concise when asking for a few sentences instead of 20 paragraphs of BS they don't want to read when all they want is a summary to verify the general direction of the prompt-work before digging into the details.

such progress!

[osigurdson]

I don't know how intentional it is / was, but LLMs in general just love to hear themselves talk!

[arjie]

They do, and I want to encourage them to do so because they think through talking. What I don’t want to do is spend time reading all that.

We will probably just get reader-side affordances for this like auto-folded justification and introduction sections and so on.

Doubtless some chat interface will add this the way they’ve added reasoning folding.

[bcrosby95]

Thinking models think through talking, don't reveal that talking, then answer by again thinking through talking. It's kinda funny in a way.

[mdgld]

I always expose reasoning traces. How else can you seriously debug?

[girvo]

The closed models aren't giving you the real thinking traces, though.

[alfiedotwtf]

It’s wild the people don’t want to see the thinking

[joquarky]

Those traces are just summaries of the reasoning.

[mr_toad]

> LLMs in general just love to hear themselves talk!

Because that’s what’s in the training set. Reticent humans don’t have blogs.

[flir]

Interesting idea. I think they're getting more wordy over time, personally, so I think it's more to do with the training than the raw data.

[jimbokun]

Is it just a coincidence that the companies creating them charge by the token?

[pizzafeelsright]

The aligned incentive appears to be realigning in favor of the corporation.

Pray they do not realign them further.

There are times I require single word answers. I will use whatever model responds as I desire and at this point those models are just a few.

[minimaxir]

The cost-per-task benchmarks align incentives toward more efficient output and those are the ones gaining steam.