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13 results for “data moats”
Concept3 mentions across episodes
moats
...that I'm gonna use to differentiate relative from my competitors, and how am I gonna produce that data? And what is the long term durable advantage created by that? I actually expect that, you know, everything we've been talking around data around mo
19:40 / 21:26
from transcript19:40 – 21:26
...of data as a moat. You know, there's the Feet. There's Axel Springer. These are the first indications of this. But in the future, these labs are gonna be thinking a lot about, okay, what's the data that I'm gonna use to differentiate relative from my
19:30 / 20:46
from transcript19:30 – 20:46
“The death of proprietary data moats is coming next”
...data. Because so far, what you're seeing is you have proprietary data stuck in, for example, the CRM vendor
4:58 / 5:36
prediction4:58 – 5:36
...moats. Well, that could be another whole panel. So, yeah, I think it's a good point to to stop there. Thank you so much to our amazing panel.
44:57 / 46:02
from transcript44:57 – 46:02
or a new moats created? I I think defensibility still exists and still matters. Like, networks are the gold standard and they still are. You know, a network effect product is incredibly powerful. Now look, you might argue that something like MoltBook
24:45 / 25:45
from transcript24:45 – 25:45
...has many other moats, but AI can wipe code, the ability to access restaurants, but it can't wipe code liquidity,
11:56 / 13:37
from transcript11:56 – 13:37
...not data network effects are real. But it's something that really it's almost like gravity gravity actually like, one atom actually has exerts gravity on you, but you only really see it at, like, very, very large scale. Like, the Earth, you notice th
3:43 / 4:46
from transcript3:43 – 4:46
...data motes, which we all talk about, but it's truly has to be proprietary. It has to be data that nobody else has access to. I think Spotify is a good example. If you look at their Discover product, it uses a decade of listening behavior across hundr
11:00 / 12:19
from transcript11:00 – 12:19
...data network effects are real. But it's something that really it's almost like gravity
2:57 / 4:01
from transcript2:57 – 4:01
...of data network effect. You know, that was like this thing that got thrown out a lot when you couldn't think of what mode to say. But today, if you look at companies that have proprietary datasets and not just proprietary, Open Evidence is a good exa
25:13 / 26:58
from transcript25:13 – 26:58
I I would say the TAM for these platforms still exist, and the TAM is still large. So that's a good thing. Because if you feel like your TAM is decreasing or all of a sudden not relevant anymore, that's an issue. But whether it's MongoDB or anybody h
12:44 / 13:48
from transcript12:44 – 13:48
...becomes the long pole in the tent. At some point, the quality of the algorithms becomes a long pole in the tent, and more compute is not going to change that. We I don't think we're there yet. That's the one thing that counters the cheap AI means mor
1:08:58 / 1:10:03
from transcript1:08:58 – 1:10:03
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