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That doesn't really track. There's no obvious link between video games and machine learning, it's just that video games graphics were the one sector demanding l

That doesn't really track. There's no obvious link between video games and machine learning, it's just that video games graphics were the one sector demanding low latency sky-high performance at the time the hardware became possible, so that's where the money went. If video games didn't exist and instead we had found some extremely valuable ore that could only be mined by performing lots of hash calculations (so like bitcoin, but actually valuable), machine learning would have developed on miner asics, and then people would be telling stories about how of course sentient machines could only come from hashing numbers together because hashing is what our brain does or whatever.

seanthemon 3y ago
Frankly, the link is linear algebra and matmul operations, exactly what's used to drive cameras, movement and much more in video games.
tnecniv 3y ago
As someone else said, not really. The link is linear algebra which is perhaps the best computational tool we have. In many areas of applied math, as soon as things get nonlinear (or non-quadratic if we’re taking derivatives since those derivatives become linear), it is impossible to find closed-form solutions (I.e., solutions you can write in a simple form). A big reason for this is that solving Ax = b might require a matrix (pseudo)inverse, but once you have that inverse, you have the solution for any pair (x, b), whereas if you had to solve f(x) = b, a new pair requires a fresh computation. Put in other terms, for linear problems, local properties are often global properties when studying linear problems. A lot of the numerical methods we use to solve hard problems are based on solutions to linear problems (or quadratic problems if we’re taking derivatives) that predate computer graphics because those problems are simple to solve. We can just solve them a lot faster now so approximating nonlinear things with linear things iteratively becomes a lot more computationally tractable.

seanthemon 3y ago

Frankly, the link is linear algebra and matmul operations, exactly what's used to drive cameras, movement and much more in video games.

tnecniv 3y ago

As someone else said, not really. The link is linear algebra which is perhaps the best computational tool we have. In many areas of applied math, as soon as things get nonlinear (or non-quadratic if we’re taking derivatives since those derivatives become linear), it is impossible to find closed-form solutions (I.e., solutions you can write in a simple form). A big reason for this is that solving Ax = b might require a matrix (pseudo)inverse, but once you have that inverse, you have the solution for any pair (x, b), whereas if you had to solve f(x) = b, a new pair requires a fresh computation. Put in other terms, for linear problems, local properties are often global properties when studying linear problems. A lot of the numerical methods we use to solve hard problems are based on solutions to linear problems (or quadratic problems if we’re taking derivatives) that predate computer graphics because those problems are simple to solve. We can just solve them a lot faster now so approximating nonlinear things with linear things iteratively becomes a lot more computationally tractable.