The simple answer is what the study showed was that 10,000 hours was the average amount of time that an expert violinist had spent practicing by the time they reached 20 years old. That's what the study showed. They weren't even experts by that point.
So, we are hiring more people who can look across all the business domains and abstract that to here's the building blocks we're going to need in a world with AI.
Your understanding of somebody else's problem is bounded because you're not in the middle of it. You don't have the same skin in the game. If you're not semiconductor test engineer, you don't have as much skin in the game as somebody who is because they're going to have to be using this interface for a long time after you're gone.
but that's my guess on what most of the useful progress uh from these models will look like like in the next five years is just really filling in that landscape of like connections that you can draw if you're an expert in multiple fields.
And I think they're at a point now where they've actually been at a point for a while now where I feel like I can just trust the outputs arguably more than I could trust the output from from a human,
And I like to say we we don't we haven't earned the right to innovate on the camera until we are the world's leading PhD on the best mobile cameras that already exist.
But you if you also become an expert in a specific industry, that's like a deadly combo. Um if you are like just pick any industry, let's say let's say farming, let's say you understand that farming industry really well and you're also a decent software engineer, you're probably like the top 10 people in the world for that combination that the whole industry will want to hire.
so for example, micro GPT, like I asked I tried to get an agent to write micro GPT. So, I told it like try to boil down the simplest things. Like try to boil down my um neural network training to the simplest thing and it can't do it.
And we failed horribly, and we had the best of the best on that team. And it’s because everybody was too much of an expert on how to make a groundbreaking phenomenon MMO.
I don’t think this is very productive (expert users of a piece of software are notoriously bad at being able to tell if an explanation will be clear to non-experts), so I needed to find a way to identify problems with the man pages that was a little more evidence-based.
you are you are a sales operations expert, right? Like what is that? That's that's that that's like a title for a particular way how companies end up solving a particular operational problem they had at some point.
So there is an angle of, the US' actions, from the angle of the expert controls, have been so inflammatory at slowing down China's progress on the leading edge that they've turned around and have accelerated their progress elsewhere because they know that this is so important.
If there are ways that you can help improve the governance of AI in these and other countries, you should be doing it now or in the next few months, not planning for ways to have an impact several years from now.
C# is the language I probably understood down to the nitty-gritty details. Just when I thought myself of being an expert - knowing all that is to know on memory allocation, garbage collection, LINQ - I read this book. It made me realize how many things I did not know.
This fits with some of the studies of chess experts and so forth that it’s not so much that you learn the patterns passively. You learn what to look for. You learn what’s important and what’s not.
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