Social media is destroying out society. Quitting doesn't help because everyone else is still on it. It's a bad equilibrium. It needs to be solved with government regulations.
Germany is in trouble. But the trouble goes deep and cannot be addressed by "more of the same" socio-economic measures in the domain of taxes or social spending or regulation.
I agree with Jakub that alignment is not a side problem, it is the central problem, if you ‘solved alignment’ in the relevant senses the rest becomes easy and if you don’t the rest is impossible or worse
Currently I believe that no lab has solved alignment and monitoring to a sufficient degree to continue responsibly scaling at maximum speed for much longer.
there's still a lot of startups in this batch that are not shipping fast enough. And so obviously there's variation in shipping speed. It's not just the rate at which you can produce things. You have to think of these ideas first, right?
In most of the world there is: no real willingness to solve problems nor an acceptance of people offering to solve their problems (out of pride) simply too much regulation so the problem cannot be solved without a license or long approval time very low standards of what is deemed acceptable so the problem isn't seen as a problem in the first place
I want to be clear, you can't throw edtech in. You can't take our time back and throw it into a school. It's not going to work cuz you haven't solved any of the other problems. And so edtech is not a magic, you know, it's not a silver bullet.
Ignorance is not a temporary defect that we will eventually eliminate. It's the permanent burden of increasing specialisation and living in a complex world.
if you're looking at the nuclear space today, you don't expect people to have this problem solved in 2031. In fact, I would say even 2035, a lot of these companies are still not going to get there because they have the wrong mindset.
Maybe I would pick something again that's that's in the category hard and boring because that's usually a category that is a little bit easier to actually find people that will appreciate when you solved something. If you pick something that is fun, even if it's hard, you're gonna have a very tough time, especially in a time where people can just prompt things into existence.
that child who learns about what you say kitty cat would not have the chance to download the internet of images of cat. They likely have seen three cats, 10 cats at most, but yet they're able to identify that tail as a cattail instead of a fox tail through a different kind of learning pathway.
you know, because sometimes if you just squint at a problem and you think about not necessarily being anchored on exactly how that problem is solved today, but how you would solve it from first principles, you can come up with really good ideas that are, you know, maybe not what other people are thinking about.
So coding is solved for the kind of coding that I do. It's not solved for everyone. You know, there's still code bases that are like super deep systems code bases where quad still struggles.
fossil fuel money is an immensely powerful, intensely corrupting force in American politics that limits not only what conversations we can have about massive problems, but what we can do to solve them
Uh but I don't think it's easy but I do think it's something you would have to do in order to uh reward the gawwa like instinct rather than just rewarding have you solved a problem.
it's just right team, right project, cuz if you don't get the right project, there's no way you can prove yourself. You could be a 10x, 100x engineer, and if you're working on relatively easy stuff, you can't really say that you solved like a really hard problem.
So often with new software paradigms, what looks like inevitability turns out to be just design failure that can be solved with the right guardrails or affordances or system instructions.
The thing that I find interesting is that's not novel. This has been the thing we've always been trying to do forever. How do we get a junior engineer to ship code safely without breaking stuff? Right? How do we make patterns in the codebase? How do we make tests? Like it's it's all the old stuff that we've always wanted to do.
The more ants you put in the puzzle, the faster the solution. But the more humans you add, the worse. Unless the humans are very carefully aligned, this is the key lesson for organizational design.
Um So, like with the Erdős problems, you know, like almost all of the 50 problems that were solved by AIs were ones for which basically there was no literature.
I mean, some problems have been basically solved by pure brute force. The four color theorem is is a famous example. Um, we have still not found a conceptually elegant proof of this theorem.
I think the trillions of dollars a year market, maybe all of the national security implications and the safety implications that I wrote about in adolescence of technology can happen without it, but I I I also think we, and I imagine others, are working on it. And I think there's a good chance that that, you know, that we get there within the next year or two.
I sincerely find these blocks to be perfect and transcendent to play with—it's about the dimensions, they all fit together perfectly like you've just beautifully solved a complex math problem.
when you learn to play chess you have the grand the long-term goal is winning the game and yet you you can't you um you want to be able to learn from shorter term things like you know taking the your opponent's pieces um and so you do that by having a value function which predicts the long-term outcome
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.
While the fact that merely scaling up AI models often results in qualitative leaps in performance may seem empirically mysterious, in retrospect it should be seen as a rational necessity.
Roberts reflects on the wild problems we face in our lives and how to navigate them—like career changes, marriage, or children—that can't be solved on a spreadsheet.
So Tesla hasn’t found a different, better way to bring driverless technology to market. Waymo is just so far ahead that it’s dealing with challenges Tesla hasn’t started thinking about.
So it feels to me that the US is treating its deficiencies — an inability to build stuff or create a functional system for admitting high-skilled migrants — as mysteries to be endured rather than problems to be solved.
Mind candy horror/mystery, stalking and being stalked by the somewhat-supernatural serial killer, with extensive local color for contemporary South Africa. There are rough patches, but it's a perfectly enjoyable specimen of this type of novel. It's obviously the set-up for a series, and I'm not sure I need to follow these characters, but I would be happy to read more by Snyman.
The only interesting problem is dramatically reducing the cost of access to orbit, which is, if you can do that, you open up a bunch of new endeavors that lots of start-up companies everybody else can do. One of our missions is to be part of this industry and lower the cost to orbit, so that there can be a renaissance, a golden age of people doing all kinds of interesting things in space.
Mind candy: black comedy crime fiction / murder mystery, in rural Finland. I enjoyed both the comic darkness and the convincing happy endings all around. (At least, happy by the characters' own lights...) My first Tuomainen, but I'd read more if they crossed my path and I was in the right mood.
while decoherence has the potential to solve this aspect of the measurement problem, it hasn't yet been satisfactorily done. Decoherence also certainly does not return us to Local Causality.
Give me a degraded pasture and a bunch of money, and even I can probably increase its beef yields 400 percent. I’m just not sure how to make the bunch-of-money part happen.
Despite these advances, contemporary physical and evolutionary-history-based approaches produce predictions that are far short of experimental accuracy in the majority of cases in which a close homologue has not been solved experimentally and this has limited their utility for many biological applications.
I've never read a book before that captures the journey of going from meh to amazing when building a product. This book does it. Part Apple / Steve Jobs pron, part memoir, and part product insights, this book is a great read on how the iPhone came to be and how they solved really hard problems. For anyone that remarks "Apple isn't what it used to be," this book helps you see what made the difference then.
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