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[–]redpnd 31 points32 points  (4 children)

This might be the transcript: https://chat.openai.com/share/44a0c5b6-c629-470a-992f-8cdbbecd64a2

From: https://twitter.com/DongwooKim/status/1667444368129785862

Some takeaways:

  • Focus on building durable businesses on top of the API
  • Structured API responses coming (eg. JSON)
  • "we do a lot of quantization"
  • Whole year of failed attempts at exceeding GPT-3; had to rebuild the whole stack
  • Took months till Code Interpreter started working, plugins still don't really work
  • GPT-V is the internal name for the vision model
  • Slow rollout due to GPU shortage
  • Function call model is coming to the API in ~2 weeks (uses same mechanism as the plugins model)
  • They're surprised by the number of non-English users, future models will take this into account (tokenization!)
  • They did the 10x price reduction for 3.5, can do the same for 4 (in 6-12 months)
  • More model customization coming (swapping the encoder?)
  • Fine tuning will enable Korean alphabet?
  • Conversations will be more interactive -- going back and forth will enable more creativity (been waiting for this personally)
  • Semiconductors are a good analogy for how they make progress: "solve hard problems at every layer of the stack"

Update (video): OpenAI Sam Altman & Greg Brockman: Fireside Chat in Seoul, Korea | SoftBank Ventures Asia

Edit: transcript is different, this seems to be the fireside chat, not the roundtable one

[–]gwerngwern.net 15 points16 points  (2 children)

Whole year of failed attempts at exceeding GPT-3; had to rebuild the whole stack

Interesting. I speculated that this might've happened because the timelines for GPT-4 didn't make much sense unless you included roughly a wasted year. This also suggests that GPT-3 in some sense got lucky (which is something I've been thinking given how hard it seemed for all the competitors to simply match GPT-3, never mind beat it, despite all the advantages they should've had in starting later).

They're surprised by the number of non-English users, future models will take this into account (tokenization!)

Finally.

[–]-ZeroRelevance- 0 points1 point  (0 children)

Finally I'll be able to translate novels from Asian languages without an unreasonable amount of tokens.

[–]someone_else_today 0 points1 point  (0 children)

Well-known rumor is that OpenAI's initial 175B run completely failed and they had to restart it with tricks for stability. That's probably why it was so hard for non-G/A competitors to match GPT-3, because they had to re-derive these tricks. And if it wasn't those tricks, then other issues like not spending time on getting proper data.

[–]hold_my_fish 1 point2 points  (0 children)

This is incredible info, thanks for summarizing. (I wonder why OpenAI chooses to release information in these awkward game-of-telephone type ways.)

[–]sanxiyn[S] 14 points15 points  (0 children)

The implication was that it wasn't running quantized before the Turbo update.

[–]NNOTM 1 point2 points  (2 children)

What does quantized mean in this context?

[–]YouAgainShmidhoobuh 7 points8 points  (0 children)

Each weight is less than 4 bytes each (or equal to, but that is the baseline)

[–]ItsJustMeJerk 4 points5 points  (0 children)

Basically they compressed the model's parameters, so it might run much more efficiently but with slightly reduced output quality.

[–]markschmidty 0 points1 point  (5 children)

Is there a recording of this somewhere?

[–]sanxiyn[S] 1 point2 points  (3 children)

Maybe there is, but I don't have one.

[–]markschmidty 0 points1 point  (2 children)

Where you at the round table? I'm just wondering if there's a way for me to verify this is more than hearsay.

[–]sanxiyn[S] 3 points4 points  (1 child)

I heard it from Dongwoo Kim, who was at the round table. See https://twitter.com/DongwooKim/status/1666799741001424896.

[–]markschmidty 0 points1 point  (0 children)

thanks

[–]Lumpy-Warning-2317 1 point2 points  (0 children)

The twitter thread (https://twitter.com/DongwooKim/status/1667444368129785862) links to a youtube video (https://www.youtube.com/watch?v=JwtKAspJRzA&t=762s) where the first comment says "If you are curious about the full event video: https://www.youtube.com/watch?v=MyTYAz82-V4" .

That last video is an hour of Sam Altman & Greg Brockman talking in Seoul. But it doesn't seem to match the transcript at https://chat.openai.com/share/44a0c5b6-c629-470a-992f-8cdbbecd64a2 -- I think because the "fireside chat" is different to the "round table talk"?