Scoring internet points that can be converted into CV line items and promotion package paragraphs is vastly better than squandering it all for a quick dunk.
Most of the world’s free time has now been monetized by tech companies. In fact, the monetization of leisure time is how Silicon Valley execs make their billions.
It’s a very interesting book, but for some reason Michio Kaku’s style doesn’t spark me as much as Briane Greene’s or Stephen Hawking’s or Neil deGrasse Tyson’s.
much cultural success is stochastic (the experimental evidence suggests that talent only moderately predicts success in culture markets), and that path dependence shapes chances of success
And that kind of compiling of information about the materials is something other fields do that we don't do. An analogy that I would think of in software would be something like a 500-page book on how to version an API.
But I think it is more useful for most developers to have an exposure to like what math has in the various fields versus just going all in every single field when they see them, right? You've got to know what's available to know what's most useful for you. And most math will not be useful for you.
while we are a lot better at iterating than other fields, we're worse at the planning part. Like we still need to do some kind of planning before we iterate and we just aren't as good as those other fields.
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.
Since I mostly work on Laravel projects or packages, I usually enable the Laravel Idea plugin. It's a paid plugin, but it's definitely worth the money since it can provide stuff like auto-completions for route names, request fields and more.
To be clear, these criteria are not best derived by looking at what would have worked in the past and assuming that it will work in the future—i.e., data mining—or simply asking an AI what to do. They are based on logical understandings converted into decision-making systems.
if somebody, you know, is standing behind the dessert table and is replenishing, restocking the desserts and keeps kind of you know, adding adding new ones in, it may turn out that you know, a little bit later a much better desserts appear.
There has to be sound business model that makes sustained profit, right? Growth and profit. Growth alone eventually burn, you know, money and that's not good.
but I think he can build the uh clean room. It'll take a year or two. Maybe initially it won't be super fast, but then over time you'll get faster and faster at it. But then the really complex part is actually developing the process technology and building wafers. And I don't think he can develop that uh quickly. I think that has a lot of built-up knowledge.
I initially assumed this was a temporary divide. New users tend to watch closely and check the system's progress, but as trust builds, that scrutiny fades and monitoring starts to feel like a chore. Yet it still seems like there's two camps (for now).
That's the opening of "The Green Fields of the Mind," collected in this slim, wonderful volume. Recommended if you like thinking about America, baseball, and The Odyssey.
So, I think it'll be the same thing that that we'll see an increase in the scope that we're giving that we're willing to give to the robots as they get better and better where initially the scope might be like there is a particular thing you do like you're making the coffee or something. Uh whereas as they get more capable, as their ability to have common sense and a broader repertoire of tasks increases, then we'll give them greater scope. Now you're running the whole coffee shop.
While the same does not directly apply in other fields, working with others to produce the best results for everyone will be much better in the long-term than focusing solely on what Amazon needs right now.
I initially started making Anki (well, Mochi) cards to keep track of Google DeepMind's LLM lineage—Gopher, Chinchilla, Gato, PaLM, Sparrow, Meena, LaMDA, Bard, Gemini, etc.
If you have a nation of 1 million people and you are ruling over hundreds of millions of people, hundreds of millions of people, China, Russia, the Middle East, you do not do that through warfare. You conquer them initially through warfare, but you do not rule them through warfare. You've got to be offering something that they want, something that they like.
I'm much more comfortable with the fox paradigm. Yeah. So yeah, I like looking for analogies, narratives. I spend a lot of time… If there's a result, I see it in one field, and I like the result, it's a cool result, but I don't like the proof, it uses types of mathematics that I'm not super familiar with, I often try to re-prove it myself using the tools that I favor.
Luis and Walter Alvarez, who made that incredible discovery, initially their discovery was based entirely on impact proxies, just as the Younger Dryas is. There was no crater. And for a long time they were disbelieved because they couldn’t produce a crater.
The answer is not more fields, which means destroying even more wild ecosystems. It is partly better, more compact, cruelty-free and pollution-free factories.
Although his training is not in economics, Richard Reeves draws on economic research, as well as research from the fields of sociology, psychology, and political science, to tell an under-told story. The book explores the problems faced by boys and men, the roots of those problems, and possible policy solutions.
And I had suggested that that’s linked to the electrical fields on the membranes themselves and that they give some indication of how am I doing in relation to my environment as a real-time feedback on the world.
And frankly biologists, most biologists are still very reluctant to even get themselves tangled up in questions like electrical fields influencing development. It seems like mumbo jumbo to a lot of biologists and it should not be because this is the 21st century biology.
pop history will not get you tenure, which leads to neglect in the academy and consequently the big pop-history books are often not written by the best historians in their fields.
Information theory has a way of shaping the way you view many things in math, computer science, physics, and beyond. It's one of those fields that takes ideas that you wouldn't think of as being quantifiable or rigorous and makes them so.
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