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Generative AI's Act Two

sequoiacap.com

51–60 of 125 posts

Re: Generative AI's Act Two

#51
post #40
post #29

Earlier quoted context omitted.

The counterpoint to this is always "models work with numerical vectors and we translate those to/from words" These things feel sentient because they talk like us, but if I told you that I have a machine that takes 1 20k-dimensional vector and turns it into another meaningful 20k-dimensional vector, you definitely wouldn't call that sentience.

What if I told you I have a machine that takes 1 20k-dimensional vector and turns it into another meaningful 20k-dimensional vector, but the machine is made of a bunch of proteins and fats and liquids and gels? Would you be willing to call it sentient now?

That's ridiculous. You're asking me to believe in sentient meat?

https://www.mit.edu/people/dpolicar/writing/prose/text/think...

Re: Generative AI's Act Two

#52

  "AI-first infrastructure companies like Coreweave, Lambda Labs, Foundry, Replicate and Modal are unbundling the public clouds and providing what AI companies need most: plentiful GPUs at a reasonable cost, available on-demand and highly scalable, with a nice PaaS developer experience."
Oddly to me, this is playing down the point in the "what we got wrong" section... "2. The bottleneck is on the supply side."

Try signing up for a Coreweave account.

Re: Generative AI's Act Two

#53
post #37

“Four decades of the internet (accelerated by COVID) has given us trillions of tokens’ worth of training data.” What’s up with the “accelerated by COVID”? It feels completely out of place. Would we have not had enough training data if COVID didn’t happen? Blessings in disguise, I guess.

I’m mildly curious if those additional tokens will make AI better, or worse.

We arguably trained AI on the good stuff first. Novels. Wikipedia entries. GitHub open-source projects with a lot of stars. What’s left but mediocrity and our “baser” internet ramblings?

Some researchers already found out that AI-sourced content can affect the models, but what about content from increasingly out-of-touch people?

Re: Generative AI's Act Two

#54
post #19

Just a bunch of hype marketing. I didn't read anything of real substance, granted I didn't read the whole thing because it seemed pointless.

Two parts I found mildly beneficial.

- The lists at the bottom (Generative AI Marketing Map). Bunch of companies I had never heard of. At the very least it gives me an idea of what somebody who is pouring out hype for AI looks at.

Marketing Map and Model Stack. Give nice little summaries by topic.

- https://www.sequoiacap.com/wp-content/uploads/sites/6/2023/0...

- https://www.sequoiacap.com/wp-content/uploads/sites/6/2023/0...

Also, the Character.ai site mentioned at the beginning is like every lawsuit ever.

Re: Generative AI's Act Two

#57
post #25

The moment that generative AI became something crazy for me was when I said "holy shit, maybe Blake Lemoine was right". Lemoine was the Google engineer who made a big fuss saying that Google had a sentient AI in development and he felt there were ethical issues to consider. And at the time we all sort of chuckled- of course Google doesn't have a true AGI in there. No one can do that. And it wasn't much later I had my…

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Re: Generative AI's Act Two

#58

"AI-first infrastructure companies like Coreweave, Lambda Labs, Foundry, Replicate and Modal are unbundling the public clouds and providing what AI companies need most: plentiful GPUs at a reasonable cost, available on-demand and highly scalable, with a nice PaaS developer experience." Oddly to me, this is playing down the point in the "what we got wrong" section... "2. The bottleneck is on the supply side." Try sign…

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Re: Generative AI's Act Two

#59
post #37

“Four decades of the internet (accelerated by COVID) has given us trillions of tokens’ worth of training data.” What’s up with the “accelerated by COVID”? It feels completely out of place. Would we have not had enough training data if COVID didn’t happen? Blessings in disguise, I guess.

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Re: Generative AI's Act Two

#60
post #34

Classic Sequoia piece: VCs sharing lengthy, jargon-filled thoughts specific to their worldview (supplemented with narrowly relevant charts!) to imply that they have a grand unifying vision. Interesting that Sonya and Pat credited GPT-4 as an author; they could've used it to make things concise!

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