I think people are hesitant to call ML “statistical modeling” because traditional statistical models approximate the underlying phenomena; e.g., a logarithmic regression would only be used to study logarithmic phenomena. ML models, by contrast, seldom resemble what they’re actually modeling.

I can appreciate that contemporary neural networks are very different from organic intelligence, but consciousness is most definitely equivalent to a computer program. There are two things preventing us from reproducing it:

1. We don’t know nearly enough about how the human mind (or any mind, really) actually works, and
2. Our computers do not have the capacity to approximate consciousness with any meaningful degree of accuracy. Floating point representations of real numbers are not an issue (after all, you can always add more bits), but the sheer scale and complexity of the brain is a big one.

Also, for what it’s worth, most organic neurons actually do use binary (“one bit”) activation, while artificial “neurons” use a real-valued activation function for a variety of reasons, the biggest two being that (a) training algorithms require differentiable models, and (b) binary activation functions do not yield a lot of information per neuron while requiring effectively the same amount of memory.

It only works on a small handful of freeways (read: no pedestrians) in California/Nevada, and only under 40 MPH. The odds of a crash within those parameters resulting in a fatality are quite low.

FPGA

Awww, I thought this was an ASIC. Slapping an FPGA on a PCIe card is decidedly less cool. Still, props for creating a usable GPU circuit description, that must have been a nightmare.

How do I enable developer mode on iOS?

banned

“Garfield is a cat”: “Garfield belongs to the cat species”.

They had me until this one lmao

…Have you seen almost any other highway in the U.S. ever?