1 karma · joined November 25, 2024
We use a large dataset of play-by-play NBA data to determine when yanking foul-plagued starters is optimal by applying insights and tools from finance. We find that a team performs significantly worse if a starter with foul trouble is allowed to remain in the game, and that this effect is strongest in the third quarter. We use a novel win-probability technique that is sufficiently general to be useful for other questions simply by appropriately redefining the state variables. Thus, our two contributions are to introduce the new approach and also to demonstrate its usefulness by solving the problem of early foul trouble that had remained unaddressed in the academic literature.
On the other hand, the fact that you hear about 'new-hot-startup' on all hi-tech sites doesn't mean it'll survive it's first year.
http://news.ycombinator.com/item?id=1949158
tl;dr Before IPO Google made several seminars so it's employees can get investment advice on how to invest their future millions. The advice was to invest in index funds.
"Education is what is left after you've forgotten everything you've learned."
Learning only things you think you'll need (e.g. coding) limits your thinking considerably. I always find it amazing how knowledge from absolutely unrelated fields helps me to solve specific problems.
GS was founded in 1869; Facebook in 2004.
Here is an abstract for those who don't want to download the full PDF
In this paper I describe the design, implementation, and features of ML/OS, an operating system with an embedded ML compiler. ML/OS supports a continuation-based thread model of concurrency with non-blocking, interrupt-driven input/output. By embedding the ML compiler into the operating system, ML/OS attempts to eliminate levels of abstraction that are present in traditional interactions between compilers and operating systems. By using a continuation-based scheduler, I demonstrate the use of advanced programming language features such as continuations and type safety in system-level programming.
Moreover GPUs have problems with double precision floating point numbers which are a must for most scientific problems (though sometimes you can utilize mixed precision approaches -> estimate in single precision, then get a correction in double).
Another problem is having ECC (error correction). You don't want to run a computation for a week to find out that it crashed because of data corruption. Latest generation of Teslas has ECC, consumer cards don't.
By the way here is another picture: http://en.wikipedia.org/wiki/File:Atmospheric_CO2_with_glaci...
Enable gzip in SSH -> SSH to some machine that has unlimited Internet access (if you have one; AWS etc.) -> Use text browser from there (Elinks is nice - http://elinks.or.cz/).
This will allow you to browse Internet with bytes of traffic.
The less you have the more you should think about doing things right.