the math community needs to adopt a version of the ethical standards of experimental science. If you are using AI agents, you can't just give a proof (formalized or not), but need to also provide a detailed explanation of how these agents were used to get the result.
Those include that having that sense of purpose, making sure that you have a network of people, that you're socially connected as your age, and also remaining curious, open to new ideas. Those factors turn out to be almost as important as some of the physical things we do.
He ruled out all the actual, measurable variables because they were an imperfect explanation, and instead offers a vague, diffuse variable, for which he has no measure, and which is not actually included in his model.
It’s one of those things that make perfect sense once you think about it. Great book, very important premise and a short and concise explanation. Can’t recommend enough.
And so, in this study on curiosity, we found that older adults tend to remember the things that they're most curious about, but they're also really good at forgetting the things that they just didn't care about in the first place.
but as you get older that tends to decline with age which I thought was kind of perplexing because I you know a lot of curious people but we found that levels of state curiosity when I give you some interesting bit of information but I don't give you the answer if it's something you care about that actually increases with age your level of curiosity and learning.
I kind of suspect that actually they'll also be like quite good at doing that and probably just like better than most humans are at like doing the explanation half and distilling half and that's actually not what's left for the mathematicians is like digesting and and explaining what was going on.
One is it seems like there's a really strong correlation between the people who come up with genuinely novel insights and also who are actually quite clear in their communication of it.
And what this is is that in the guide level explanation, you explain your feature as if you were writing a guide as if the feature already existed. And in the reference level explanation, you explain your feature again as if it already existed, but as if it would be in the language reference instead of a tutorial.
And so one possible explanation for that is just that there's only a handful of generations maybe five over which the natural selection would operate. And so maybe if the selection was 2% a generation you would still only see maybe a 10% compounded effect and there's just not enough time to detect it. But the Bronze Age is not 300 years, it's 3,000 years. It's the power of compound interest and you have enough time to begin to see a strong effect.
And I think the like the third and the most interesting possibility is no, that like they're they're a new type of object in some in some sense. They should be taken very seriously as as explanations, but where in the past we haven't had the ability to really do anything with them.
Um and so, it's not a big leap to realize, "Oh, we have a big problem here." Um and so, you know, that's kind of the that's the forcing function there. It's it's you've realized that your old explanation is not sufficient. You need something new.
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.
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.
Any performance test should be accompanied by an explanation of the limiting factor, since no explanation will reveal the test wasn't analyzed and the result may be bogus.
I think the first point is the extreme loyalty of the people whom Genghis Khan chose. His kinsmen, as we said, had deserted him, his anda was a questionable relationship but all the others that he found were just common people, herders or hunters, very common, and they were loyal to him and never, ever revolted against him, never betrayed him.
I don’t believe it’s providing a kind of formal explanation of the different positions. It’s just saying which position is better or not that you can intuit as a human being, and then from that, we humans can construct a theory of the matter.
What makes humans special though, is our curiosity. Even if AI’s cracked this, it’s us still asking them to go explore something. And one thing that I feel like AI’s haven’t cracked yet, is being naturally curious and coming up with interesting questions to understand the world and going and digging deeper about them.
There is a skill to asking good questions, and everyone’s curious though. Curiosity is unbounded in this world. Every person in the world is curious, but not all of them are blessed to translate that curiosity into a well-articulated question.
That is absolutely possible. I’m actually putting less credence on that one just because you need to happen every single time. If even one, I mean, this goes back to John von Neumann pointed out that you don’t need to send the aliens around the galaxy. You can build self-reproducing probes and send them around the galaxy.
But I think your intuition is right that it would’ve been easy for there to be lots of civilizations then we would’ve noticed them already and we haven’t. Absolutely the simplest explanation for why we haven’t is that they’re not there.
Ben Strak's short and sweet Monday newsletter offers weekly inspiration to designers and anyone else curious about the world around them. A good example of how newsletters thrive on the authentic curiosity of the people who write them.
Our best explanation is that the UK adopted what we call the globalized system of procurement, privatizing planning functions to consultants and privatizing risk to contractors, which creates more conflict; the UK also has an unusually high soft cost factor.
But there’s a very interesting deep split in life between bacteria and what are called archaea, which look just the same as bacteria. And they’re not quite as diverse, but nearly, and they are very different in their biochemistry. And so any explanation for the origin of life has to account, as well, for why they’re so different and yet so similar. And that makes me think that life probably did arise only once.
Julia Galef, The Scout Mindset – A charming and original contribution to the genre on being open-minded and curious. Great stories and ideas, alongside a serious argument for the virtues of exploring rather than defending ideas.
If you're curious how Google built it's culture and the processes thanks to their extremely data & engineering driven nature, this is a great book. What held it back was being ~100 pages too long and Bock didn't always understand where what they did only fit at a $100Bn+, mega-profitable company. Still, the insights on the studies on their 50,000+ employees is well worth the read since so few of us can get similar statistical significance to apply to our teams.
I follow Ed Latimore on twitter. He writes a lot of interest things there, so I was curious to pick up his book to see what he'd say in a longer form. This book is like getting beers and talking life with Ed for about 5-6 hours. Lots of truisms and life lessons that should resonate in the world we live in today. It's no Earth-shattering, but it is a great way to get more good ideas in your head.
I read this because I was curious what sets the greatest entrepreneurs apart from everyone else? Where do they get their inspiration and how did they do it? While this book isn't completely satisfying, it does provide a number of interesting insights into the likes of Steve Jobs and other such icons.
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