4.4 • 1.1K Ratings
🗓️ 24 September 2024
⏱️ 32 minutes
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0:00.0 | There will be a lot more divergence between the law of the labs in terms of what |
0:04.8 | research directions they choose to explore and which ones ultimately have |
0:08.5 | breakthroughs at various times. One of the hallmarks of this next phase is actually going to be data production. |
0:15.4 | Basically no agent really works. Well, it turns out there's just no agent data on the internet. |
0:20.2 | The pricing for model imprints fall dramatically dramatically |
0:26.0 | dramatically like order of it. Yeah orders order. Order. Yeah two orders of magnitude over two years. |
0:32.2 | If you've been listening to the A16Z podcast for a while, |
0:35.0 | you'll know we talk a lot about AI. |
0:38.0 | We've covered the algorithms at PowerLMs |
0:40.0 | and the compute required to run them. |
0:42.0 | But equally important is data. |
0:44.9 | Our guest today is as deep as you can get |
0:46.9 | in this world of data, the fuel behind LMPS. |
0:50.0 | In fact, he even recently said, |
0:51.8 | quote, |
0:52.5 | as an industry, we can either choose data abundance or data scarcity. |
0:57.1 | So what data exist today and what needs to be created, |
1:00.0 | either measured or synthesized? |
1:02.1 | Listen in to find out. As I pass it over to A16Z growth, general partner, Sarah Wang, |
1:07.8 | to properly introduce this episode. |
1:09.8 | Hey guys, I'm Sarah Wang, general partner on the A16Z growth team. |
1:15.0 | Welcome back to our AI Revolution series, where we talk to industry leaders about how they're |
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