161–170 of 177 posts
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Mark gets a lot of flack for metaverse, but can imagine world design where you start in a blank room and describe what you want around you, and it appears. Like the Matrix loading white room. And with voice recognition and eye tracking (and brain scans), how close are we to “you have to use your hands? It’s like a baby’s toy.”
They are calling it “text-to-space”: https://twitter.com/rowancheung/status/1631023065722245122?s...
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It’s awesome for formatting and structuring. Copy and paste a bunch of styled JS components -> get back out a single CSS sheet Paste in a markdown document -> get out the same thing in HTML Fun stuff like that.
Ah yes, you now too can have the wonders of pandoc - now on sale! Retail pandoc price of 20MB, now selling for only 3TB with the exclusive offer of ChatGPT!
The value here is how easy it is, and the fact that a generalised model can take the place of a (well-engineered) specialised tool.
What would it take to go deeper on this and narrow down to, say, single-sentence intervals? For example finding everything about a particular character in the Ramayana, or every statement about NPR itself?
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Excellent! I'd love to see a script that sends a list of "descriptions" (1-100 words) to ChatGPT and directly gives you back a ready-made (embedding vectors closeness) map in a (textual) graph/chart format (like your above map or your plot https://interconnected.org/more/2023/02/in_our_time-PCA-plot... )
It turns out that "closeness" is usually hard to visualise/explore when you're dealing with a 1,000-dimensional space... and PCA has the failures mentioned above. It's weird -- it's locally useful to navigate, and at a high level kinda useful, but only if you squint and don't look at the problems. So I feel like a fisheye visualisation would be appropriate? That's something that I'm exploring in other projects.
Wait. Is temperature=0 "pretty deterministic", or is it deterministic?
Temperature=0 is not perfectly deterministic for the OpenAI API. It's mentioned briefly in the OpenAI text completion guide: https://platform.openai.com/docs/guides/completion/introduct... If you have two possible tokens with probability 40% and 30%, you'll always get the 40% token at T=0. But if you have two possible tokens at 40% and 39.99%, you may get the 39.99% token on occasion, even if at T=0. (Numbers illustr…
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Temperature=0 is not perfectly deterministic for the OpenAI API. It's mentioned briefly in the OpenAI text completion guide: https://platform.openai.com/docs/guides/completion/introduct... If you have two possible tokens with probability 40% and 30%, you'll always get the 40% token at T=0. But if you have two possible tokens at 40% and 39.99%, you may get the 39.99% token on occasion, even if at T=0. (Numbers illustr…
Where does the inherent randomness come from?
Finally, my interest in LLMs is piqued! Seems like everyone has been getting excited around the search or code-generation use cases ... or simply trying to make it say naughty things (boring, not interested, wake up in a few more years), but this is eye opening. The idea of this as a "universal coupler" is fascinating, and I think I agree with the author that we are probably standing at an early-90s-web moment with L…
https://en.wikipedia.org/wiki/Semantic_Web
https://en.wikipedia.org/wiki/Semantic_interoperability
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On a related note, has anyone noticed the growing use of "pretty" as a hedge against ever being wrong? Also, "not", as in "not the fastest" or "not the hottest". It could be 46C/115F outside and you say "wow, today is unbearably hot", to which someone retorts "nah, it's fine. It's not the hottest day". That's pretty good hedging. You can make infinite technically correct statements this way without ever saying anythi…
> Also, "not", as in "not the fastest" or "not the hottest". Mid twenties Hiberno-English speaker here and that's always been a fairly common form of hedging, and I've not noticed an increase.