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It is not at all surprising that “The Soul of a New Machine” resonates with people in Hacker News. And it is a tremendous book. But for me, his book about Paul Farmer, “Mountains Beyond Mountains”, was even more meaningful. Tracy met Paul by happenstance and in a short encounter recognized the stubborn greatness that was Paul. He was an amazing character who sadly is no longer with us, but captured in a book worthy of his life. Read the book and contribute to Paul’s life work “Partners in Health”.

House was also a wonderful read. In many ways I enjoyed it more than SoaNM due to the parallels with software development but in a completely different domain. Building a house is remarkably similar to building an application.

His whole catalogue is fantastic really. Definitely a favourite author of mine.


Agreed. The Soul of a New Machine is my personal favorite but I think Mountains Beyond Mountains as well as Strength in What Remains are the more powerful and interesting books.

Kind of amazing that that book was written in 2003. Farmer would've only been about 42 around then and he'd already done so much that Kidder wrote this book about him.

If you’re only make on average 500k/year after 10y — you’re not really in the game at all


there are a lot of quants who aren't at T1 firms or in the hottest seats. plenty make less than this. obviously if you are top of class and getting headhunted by XTX, your offers will be much bigger than $500k ... but it's kind of obnoxious to claim that QRs making less than this aren't even players


The term "player" tends to imply something more than just someone employed in a field. I don't support all this insane inequality, but the other commenter is not wrong on the relative value assessment.


Feel free to do more accurate math! I don't think you'd be doing $500k right out of college either, so it was intended to be a rough average. The person I know I'm finance is doing well over $1,000,000/yr, but I have no idea how average that is.


Lua uses the table type to represent both dictionaries (hash tables) and arrays of values. This seems to have been predicated on keeping the language “simple” with a minimal number of defined types. A laudable goal.

However, arrays of a single type are just enormously common in applications. Support for arrays is pretty much ubiquitous in other languages, including ones that are in the same general dynamic space.

Internally Lua does treat arrays in their own pathway to keep performance reasonable. There is also some user facing special syntax for arrays. Arrays should be part of the core language — some learning overhead for the newcomer but worth it.


I think the real issue here is not whether there is a separate type for tables and arrays, but whether the arrays are homogenous (all elements must have the same type). In most dynamic languages, the arrays are heterogeneous. For example, Python has a separate array type, but if you want homogenous arrays you have to reach for something like numpy.


For a more full featured Xoshiro/Xoroshiro implementation see

https://github.com/nessan/xoshiro

Documented at: https://nessan.github.io/xoshiro/

Handles the full family of these generators featuring arbitrary jump sizes, stream partitioning for parallel applications, and, like this library, a number of convenience sampling methods to shield the casual user from the complexities of using <random>.

Can be used with a companion `bit` library (https://github.com/nessan/bit) that performs efficient linear algebra and polynomial reduction over GF(2) for those that want to explore some of the mathematics behind these linear generators.


Why are you doing numerical code in single precision? If no one in your group did a numerical analysis course at college it’s time you moved on to think about some other problem more suited to your experience set.


No need to be snarky. The choice to default to FP32 is inspired by the fact that most typical use cases don't need double-precision (GPU shader languages and game engines do this all the time). This in turn allows us to vectorize code for 2x throughput compared to using FP64. We're gonna add a flag to change the default floating-point precision for devs who need extra precision.

See docs: https://docs.fxn.ai/predictors/requirements#floating-point-v...


Just look at the work to date as a portfolio for your resume and go get a job with someone that will pay you and perhaps give you some small amount of equity. You don’t have the skills to sell. Move on


People are lazy.

American students are mostly rich by any global standard and very, very lazy. Doesn’t matter a huge amount as they don’t matter — they will amount to nothing anyway. The States imports enough talent to make up for the lacuna. In the meantime, their parents pump cash into what will become their Alma Maters.

When I went to an Ivy League US university as a grad student I was astonished at the remedial nature of undergraduate courses. Content that students in my country mastered at 13 needed to be spoon-fed to US students that were 5-6 years older.

Even back then almost nobody failed a course in the US. It was a major deal to fail someone. I came from a culture where the standard was absolute. No curve. Get below z% and you spent the Summer getting ready for a retake. Fail that, and you were out.

Education was paid by the State so it wasn’t a business. Profs could fail 20 - 40% of a class and often did.

It is astonishing that a Philosophy prof is seeing this. Who the fuck does philosophy at Uni and can’t be arsed to read the recommended texts?

He/she is a full Prof. Almost impossible to fire. So fail the lot of those entitled, lazy, bums I say. Enjoy that tenure!


I graduated from top university. I wasn't a particularly bright student, so I had to study very hard in order to pass classes. Just like you say, professor could fail a third of the class and that was normal. Having a weekend off meant that I was forgetting about something.

After graduation, I stopped learning. The older I get, the less point I see in endless grinding. Sometimes I watch some pop-sci shows on YouTube, but pretty much without any actual knowledge retention. At my work I do the bare minimum not to get fired.

I wonder what does this all mean. On one hand I think that if I worked hard again I could achieve great things. But on the other... god damn, I was constantly depressed as a student. Now that I spend my time just dicking around, at least I don't want to kill myself.


The pricing of all these AI models is so opaque. Can’t they hire someone with common sense who realizes that $x/token is absurd!!!

Totally brain-dead. Like pricing a car by the number of o-rings in the engine.


Jamie decided that he gets more out of his vast workforce if they are on site and, given his tenure, he has the data that backs that up.


As mentioned in the article all MD’s are back since mid 2023 so zero.


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