AI's enterprise payoff still lacks scaled proof

Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

1. 1:16:00

   Market today, Jamal. Yeah, I mean, I'll just do it again. But I think the the Schiller PE, Nick, I sent it to you, shows near all time highs. Then the second is the Buffett index, which is the sum of all US equities divided by GDP is also at all time highs. So this would generally mean that you need to be increasingly a little bit more risk off. But then the opposite side of that, and I sent you a third one, and this is why it's so confounding is you have signals showing everything which is which typically doesn't happen and this is this dispersion point where when you see this performance and it's up five percent in the first you know half of april typically the market is up almost 32 percent on average for the rest of the year and we were already up as sac said you know seven and a half percent already i'm trying to read this graph this

2. 1:16:51

   is crazy i don't even know what's going on here this is just this is just the dispersion but the the the idea of all of this is i think we're in a moment where you can find a piece of data to underwrite your bias and i think that's where there's a lot of danger i don't know for me personally i'm generally more risk off right now and more importantly i'm waiting for these ipos so that i can to be very honest with you delever and get some chips off the table i think that it is crucial that this spacex ipo get done asap and then i think it's even more crucial that one of anthropic and open ai front run the other one and get out first and the first two charts are the reasons why it's fairly obvious to me what's going on here you have these multiple trends going on at the same time the reason people are traders are valuing this and i think there is

3. 1:17:46

   some smart money in the market right now is what you're seeing in terms of the earnings potential of these companies as they deploy AI, as they have unlimited intelligence, and the top employees at the top companies become 10 or 20 or 30 times more productive. That's never been seen before. Microsoft Office may have made you 30% more efficient. The internet may have made you 50% more efficient. But none of these things made you 10 times. And you had a really interesting point that you slipped in earlier, Chamath, which was nobody knows how to harness these things yet, right? And it's producing slop. The truth is 10% of people do know how to harness it, 20% maybe.

4. 1:18:23

   And I watch this in my own organizations and I watch it in 600 portfolio companies. The ones that do deploy it correctly, they are running the table on the ones that are not. So the efficiency boom that we're going to see at these companies, whether it's Meta or Uber or Airbnb or whoever i'm just whoever executes it properly is going to be phenomenal the earnings will be insane maybe i'm an idiot but it has not translated into a tsunami of more revenue and more profit for me yet maybe i'm the only one and maybe it's everybody else but me but i haven't seen it i see it in a lot of companies so i think in private companies we have two companies as just two examples micro one which is doing data you know dark pools of data for these language models, and they have built technology that allows them to build data and allows them to

5. 1:19:11

   collect data to help the large language models companies grow. And they are on a tear by using this to identify and find great people who can then contribute to these corpuses. And then we have one tax GPT that is making the accountants, I think they have six or 7% of all accountants using their platform. They're just ripping the productivity of accountants. I hope you can agree with me with the following statement. Small companies nibbling at the edges is not where these guys will build a multi-trillion dollar market cap. I think we're both in alignment.

6. 1:19:42

   Big companies, dumb companies, slow to implement the technology, startups. No, they are dumb when it comes to implementing new technology. They're always the laggards when it comes to implementing new technology. The reason that they are slow is not because they are dumb. The reason that they're slow is their business is much more sophisticated and much more complicated than and money other businesses.

7. 1:20:00

   And what I'm saying is, if you can't prove that this works in the big-time, prime-time, big-league use cases, it's a toy. All right, Sachs, where do you stand? Are you in the JCal position? The startups are showing the way. They're being massively efficient. They're growing revenues like we've never seen in the startup community before with less people. Or are you in the Chamath camp? Hey, big companies are not having a drop to the bottom line, and they're smart.

8. 1:20:26

   Or both things are true. Where do you stand, Sachs? be the adjudicator of this case. I mean, honestly, I'm probably closer to you, J. Cal. I hate to say that. Yeah, listen. Because, look, I think people are still figuring out how to drive business value out of AI. And change management is hard, and the bigger the company, the harder it is. So, what's happening right now is there are a lot of transformation projects at large enterprises that are failing. There's like a big McKinsey study on that.

9. 1:20:53

   But, if you look at activity from the bottom up, I think it's very interesting it's becoming more interesting and over the last several months obviously with coding reaching a new level we're starting to see very interesting things happening there and obviously the revenue that's now being generated from these coding models is you know again it's exponential like we've never seen before so the roi is finally there at the model layer meaning before you know people were saying that it's a bubble because you had all this massive capex at the data center level and there was no roi coming at the model layer now we have the roi at the model layer and i guess we're sort of questioning whether the roi will be there at the application level but in any event i think things are progressing i mean look i fundamentally i'm

10. 1:21:42

    bullish on this whole thing okay no no sorry let me be clear hold on hold on obviously i'm bullish i'm in this i'm in the space i'm doing it you're in the arena we have seen in every single wave in the mobile wave we needed consumers to show up at scale so we needed consumer experiences and it was very obvious that there were these consumer businesses that were going to be if not already incredibly incredibly profitable google and facebook were profitable within the first few years they never look back and all i'm trying to point out to you guys is there is not one great example yet if we believe enterprise is where all the money is and if we believe that's what's going to underpin these trillion dollar valuations. Just please somebody show me a couple of good examples of scaled profits. Okay, fair enough. Travis, final word here on-

11. 1:22:33

    But by the way, can I say one other thing? I think Chamath has a good point about being risk off right now, because if you just look at valuation metrics, they do seem to be quite high. And I've seen other versions of those metrics as well. So look, it's very, very hard to time the market. I don't try. But I think you could make an argument just based purely on valuation levels, not events, that you want to adopt a more conservative posture right now.

12. 1:22:57

    I think the bet you're making then, Travis, is are these valuations so high right now on the standards that the efficiency that AI could bring to these companies is not real enough to continue the growth from here it's not a catalytic enough technology and you know when you look at the opposite all these traditional companies have horrible valuations they've been crushed so my point is if ai is real the upside is also real all i'm saying is the details guys matter it's very hard to take a very complicated business and all of a sudden quote-unquote transform it it's not as easy as it sounds that word is easy to say for sure travis go ahead Final word.

13. 1:23:45

    Final word from Travis, please. A couple things.