Why data is the biggest AI bottleneck (feat. Arthur Mensch of Mistral AI) | E2212

What year an AI model can do drive any city, drive anywhere from in Europe, Madrid to Moscow, and nail it's safely a hundred out of a hundred times, a thousand out of a thousand times. Pick a year. Theoretically, I think it would actually already work. Thousand 10,000 out of 10,000 times perfectly? No, no, probably not.

Some folks have moved to hiring experts for 50 bucks an hour, asking them questions, and then just having proprietary streams of knowledge. We have a company, Micro One. How do you think about? hiring experts to build out the knowledge base. What we found is that onboarding and having full-time employees that actually have the expertise to judge whether we are actually making progress is super important.

There's still an amount of of information that you're not going to get to whatever you pay for if you're not partnering with a company who actually has the knowledge. You need to source uh people that are experts in their fields, usually PhDs, and have an interest for computer science. If you find these to things, you certainly you have someone who is interested in driving the competence of an AI model forward in in their field. This week in startups is brought to you by Nexos.

We already have this episode, so unlocking it is cheap and permanent: the full transcript (65 minutes, 12,812 words), segment and word-level timestamps, and .txt, .srt, .vtt and word-level JSON downloads, as many times as you like, forever.

No account needed, we create one from your checkout email. With credits it is 1 credit; packs start at 5 episodes for $3.49, and monthly plans are cheaper still.