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17 results for “ai native”
Concept7 mentions across episodes
AI native
I, I almost felt like I was like processing some sort of like ethical boundary, but we were just talking about like the stock market, but it still felt different in the interesting way. Almost like I was talking to a person, even though I knew better
51:42 / 52:50
from transcript51:42 – 52:50
Obviously, your your your your actions are you know, if you assume they're rational actors, which they are mostly, your what you do in a two year AGI versus five year versus ten years, very, very, very different. Right? Do you think agents are promis
4:31:20 / 4:32:35
from transcript4:31:20 – 4:32:35
There's a lot of term agent applied to things like Apple Intelligence, which we still don't have after the last WWDC, which is orchestrating between apps. And that tool use thing is something that language models can do really well. Apple intelligenc
4:32:07 / 4:33:15
from transcript4:32:07 – 4:33:15
...none of the native audio stuff, obviously, real time interaction, none of that actually had happened yet. It's hard to even imagine how far we've come even in just the two year time frame as a part of that. Yeah. I mean, it's really remarkable, like,
2:10 / 3:25
from transcript2:10 – 3:25
But ultimately, I think what this promise is, right, is that the interactions we have with our computers are gonna be much more natural the way our brains are wired process information. Right? Like, you know, like using a keyboard and a mouse, it's n
53:16 / 54:18
from transcript53:16 – 54:18
The other one is more academic Yeah. Because as a kid, I've always been interested in the nature of consciousness, nature of intelligence. I was always interested in AI and reading the literature there. And I would point to the RL, literature. So Ric
48:45 / 49:50
from transcript48:45 – 49:50
“AI models are finally mature enough to create entirely new user experiences”
sessions were increasing over time. So if you trace it back to 2023 and look at every cohort for every quarter since then, you can see how session lengths have been increasing, and there would be infl
21:29 / 22:08
market insight21:29 – 22:08
“AI agents interviewing AI agents - are human conversations becoming obsolete?”
everyone are, like, using some sort of AI in in either end. I think that the running joke with with interviews is that you have somebody being prepped by their AI agent to know what to say, and then t
15:18 / 15:53
prediction15:18 – 15:53
longer horizon tasks are newly unlocked, I would say. And so encoding in particular, we've seen, some customers using it for many, many hours unattended and doing giant refactors on its own. That's been really exciting to see. But in non coding use c
3:48 / 4:51
from transcript3:48 – 4:51
“AI native isn't the future - it's the obvious present”
...AI nativeness is an obvious future. Like, it's an obvious present, actually, not even a future. You have to think AI natively. You have to think,
5:31 / 6:04
market insight5:31 – 6:04
creatures, I would say. Like, language is probably one of our last forms of evolution. As the three of us are talking, I think we're constantly getting so many signals. I'm like, oh, Lenny is not in his head, so probably I would go in this direction
1:07:23 / 1:08:30
from transcript1:07:23 – 1:08:30
I don't need a lot of compute performance for that. Does that sound about right? Yeah. Yeah. I totally agree. The interesting architectural question for me has always been how do you handle the kind of nondeterminism that may come? Many of these succ
27:02 / 28:05
from transcript27:02 – 28:05
and it gets the wrong answer, it doesn't know how to solve the problem. You look at it and go, okay, I'm using AI to try to do a hard math problem. This language model versus the other one got it right, got it wrong. I my prompt was changed. It's all
19:20 / 20:35
from transcript19:20 – 20:35
One of the most important things is that that AI is not just AI is software, but it's not prerecorded software as you know. For example, Excel was written by several 100 engineers. They compiled it. It's prerecorded, and then they distribute it as is
5:20 / 6:29
from transcript5:20 – 6:29
a technology that understands information. And there's human information, and so we oftentimes think about AI as a chatbot. Mhmm. But remember, there's biological information, there's chemical information, there's physical information, information of
17:19 / 18:31
from transcript17:19 – 18:31
shared things they shouldn't have shared, customer data, marketing plans, financial data. So the first layer was, how do we make sure our employees are using somebody else's AI in the form of some chatbot, ChatGPT, Gemini, so forth and so on, safely.
1:29 / 2:33
from transcript1:29 – 2:33
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