clpmsf

Trump will be a lame duck soon, and it's likely that the next president will be far less extreme. Some sense of American normalcy will likely return relatively soon.

my mental model:

guess about the future (no money involved) = "prediction"

guess about the future (money involved) = "gambling"

I'm not reading too much into it. SF Bay Area is still the startup HQ of the world. Gary probably just wanted to hire this guy despite his desire to live in Cambridge. Plus YC is leaning harder into their preference for college-age founders, so having a partner next to Harvard&MIT doesn't hurt.

I don't think that now is the best time to learn software development, but I do think that now is the best time to learn computer science.

You've built a great product IMO. I'm a happy customer.

Why is this guy so popular of late? Is it because he manages to book interesting podcast guests? He doesn't seem to have any particularly interesting or impressive original thoughts on display...

The Taiwanese tourists seem to have a significantly more favorable reputation in Japan (in comparison to the Chinese tourists).

He (along with Jack Ma) is certainly among the luckiest people on Earth... I'm not sure if it's just consistently poor translation / English skills, but every time I hear either of those guys speak it's a visceral reminder that you don't need to be super smart to get super rich.

That seems like a very strange opinion... "the professor's time was wasted"?? The pursuit of education (and often degrees) is meaningful on a personal level. A productive research career is simply one of infinitely many paths that a person could choose to take.

Most likely for the same reason that so many people seem to think they need a vector-specific database and a framework like langchain to build any type of GenAI-enabled application... the content marketing is working.

Not all (or most) people-problems can be solved with software. Recruiting/hiring is a pure people-problem. No two people are the same. No two groups of people (i.e., companies) are the same. It's a "problem" that everyone has felt, but it honestly seems like an unsolvable problem... and "problem" mostly likely isn't even the right word - more of an uncomfortable reality.

It seems YC is trending younger with this AI wave (I believe average age of the most recent batch was ~26) - kids dropping out of college to build startups without ever having worked at a real software engineering job... I imagine this type of story is not at all uncommon at the moment.

I listened to a talk to that Jim Simons gave at San Francisco State University about a decade ago in which he mostly recounts his life and career. Towards the end when he was describing the state of the fully realized RenTech firm, he mentioned that they collect approximately 7TB of data per day, and that the #1 investment rule is that a human never, under any circumstances, intervenes with what the model (he said "the computer") decides.

From a high level engineering perspective (and not being an expert in blockchain systems), the amount of complexity in the Ethereum ecosystem seems... excessive? And it seems likely the amount of complexity will only continue to increase over time. We tend to prefer 'elegant solutions' and simple systems in engineering, and this seems quite the opposite. Is it truly necessary to solve the problems that it's trying to solve?

It's truly hard to believe that Michael Seibel wasn't appointed as CEO, and equally hard to believe that Garry Tan was.