I chuckled at this bit

I decided to conduct the "model of the world" test on my bot running gpt-0613

Comparing the performance of gpt-4-0613 (left) vs gpt-3.5-16k-0613 (right) as a search engine GPT-4 finds the show on the first try but stumbles on the actress once Gpt-3.5-16k on the other hand gets the show wrong at first and goes through half the cast guessing the actress

realized LLM solve my biggest friction point in querying the internet - before composing a query i often have to google translate to find the right english word or one with better connotation similarity I can just use russian words midsentence and LLM still understands perfectly

LLMs should be good at distilling knowledge of specialized communities like r/bodybuilding above. It might confabulate, of course, and with bodybuilding the danger of it is quite real, but i'd guess confabulations are in the right general direction and a good place to start

gpt4-0314 has some problems with the number pi if you ask it about zeroes in it - it inserted 0 at arbitrary position (left) but it has no problem reciting 100 digits of pi; if you ask pi until 1000 digits it gives the correct order but lost count and stoped on 666 digits (right)

Recently started using GPT-4 as calories/weight DB for food. Sometimes it does math and I find myself surprised that math for small numbers consistently checks out (even with decimal numbers!) Here is its result for counting milk weight in a latte.

I think it's the first time I've seen multi-step thinking with prompting the user before doing further actions in gpt4. The code it produced didn't work. Instead of generating new code and guessing what's wrong GPT here asks me to do some debugging and provide feedback.

Okay, it asks me what I want to do instead of generating a suggestion and going forward with it :o