One unpopular position I’ve stuck to over the years is that a strong bureaucracy is good. I don’t mean “bureaucracy” as in red tape and regulation; I mean a competent, empowered civil service that can perform crucial government functions efficiently and well using in-house expertise. This is also called state capacity.
At a fundamental level, they’re just hostile to the idea of expertise in any domain, in pretty much every agency where there’s something to know, where there’s technical stuff that you need to know to make good decisions. The people who actually know things, or the people who are willing to speak up about what they know, have been silenced, purged.
Paradigms of Artificial Intelligence Programming by Peter Norvig. Learning the AI described in this book probably won't land you a job today. But reading the code examples will transform how you think about source code. The book shines when it comes to code comments, a topic that I've never seen demonstrated well in other sources. Here we get to see how comments become valuable as a narrative that explains both intent and reasoning. Brilliant, just brilliant.
In addition to reliability issues, it often engenders a mind-numbing workflow and an environment where junior developers will never acquire the expertise to become senior developers capable of designing complex systems.
if you don't actually push yourself down to sit alongside your IC engineers and your IC designers and your IC PMs, you don't actually know that stuff. So you can't make good macro decisions without the micro.
My view is that an appreciation of China's REER is very much to be desired, but the real (haha) way to get there is through higher inflation domestically, and that means different macro policies.
But I think it would be a mistake to say design and deep design expertise and thinking gets squeezed out just because we can write code faster. We can do data analysis faster.
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.
here prices are adjusting in this interesting way that too many macro models don't allow for, right? So, that what what a what's happening is what would be called investment specific technical change where yeah, the price of capital is like falling relative to the price of consumption instead of like the standard doing the standard macro thing of saying there's just output.
Doing "the hard thing" means pursuing the highest-value problem you can find that still sits inside your zone of expertise; the hardest problem you're personally in a position to win.
And so our expertise um helps our our our um uh our AI labs partners get another 2x out of their stack easily. Often times it's not unusual that we you know by the time that we're done optimizing their stack or optimizing a particular kernel their model sped up by 3x 2x 50%.
Yeah, so they excel at breadth and humans excel at depth. Um like human experts at least. Yeah, so um I think they're very complementary. Um but our current uh way of doing math and science is focused on depth because that that's where the human uh expertise cuz humans can't do breadth.
The stand-out non-fiction book of the year was Rory Stewart's Politics on the Edge. I have a lot of disagreements with Stewart's political positions (the more I listen to him, the more disagreements I find), but he is an excellent memoirist who skewers the banality, superficiality, and contempt for competence that has become so prevailing in centrist and right-wing politics. It's hard not to read this book and despair of electoralism and the current structures of governments, but it's bracing to know that even some people I disagree with believe in the value of expertise.
I just think about like really simple things like access to mental health care, access to education, access to medical advice, access to legal advice. We're essentially taking expertise and making it a commodity. And I think that will is generally democratizing.
The bar I typically suggest is that the people manager doesn't need to have the most technical depth on the team, but they need enough depth that they can follow most discussions without slowing them down, understand who's correct in most debates without needing to rely on trust, and generally stay oriented easily.
Clients still pay a fixed monthly retainer to ensure the professional maintenance of the whole portfolio, and to get access to the expertise of all of Geomys’ maintainers.
My hot take is that JS has the lowest bar of entry to building and being productive (a good thing) but one of the highest bars of any language and stack to building high quality, stable, and reliable software. Very few devs have the expertise to pull off the latter
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.
This book surveys theories of creativity, contrasting four competing explanations: expertise, genius, society, and chance, in offering a model for how creativity works. Simonton's work provides a nice hybrid between the purely anecdotal work of biographers and the data-driven work of experimental scientists.
Despite evaluations, we cannot consider coming powerful frontier AI systems "safe unless proven unsafe". With current testing methodologies, issues can easily be missed. Additionally, it is unclear if governments can quickly build the immense expertise needed for reliable technical evaluations of AI capabilities and societal-scale risks. Given this, developers of frontier AI should carry the burden of proof to demonstrate that their plans keep risks within acceptable limits.
Friedman’s focus on the money supply has not held up, as Samuelson suggested, but the alternative Keynesian macro models recommended by Samuelson in the same interview have not done better and they were not outperforming simple random walk models of predicting the macroeconomic future.
I may have I may be an investor. I have a track record of calling the market right in the last five times. People say, "Wow, he really knows what he's talking about." But there are lots of people who are trying to predict which way the market is going to go. And some of them are going to get it right by chance. And people assume it's because they know what they're what they're doing, and in fact they're just the lucky ones.
Work that’s too fine, too early commits everyone to the wrong details. Designers and programmers need room to apply their own judgement and expertise when they roll up their sleeves and discover all the real trade-offs that emerge.
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