107 karma · joined March 17, 2017
I guess you could argue that AlexNet was the product of one very motivated CS student who was very proefficient with C++ and CUDA. This particular skill set had a very deep impact on the computer vision community. Today, how ever, you don't need it because all that has been abstracted away. But someone had to lead the way.
Well, that's a truth with modifications [1]
I don't find this to be the case with most ML researchers. Is it possible you have misunderstood some of these papers? It is, after all, hard to jump straight into a new field.
> The second paper converted float to bool and then tried to use the gradient for training.
This sounds like binarized neural networks. If that's the case, they keep the activation before binarization to use for backpropegation.
> The third paper only used a 3x3 pixel neighborhood for learning long-distance moves.
A single layer of 3x3 convolutions would not be able to model long-distance moves. But I have not read a single paper where they have only used one layer. Is it possible they stacked multiple conv + pooling layers? The receptive field of each unit higher up in the stack grows pretty large in the end.
This is not at all obvious to this casual observer. Earth radiates heat away at a constant rate. We can never produce more energy than the earth radiates away, for obvious reason. With current trajectories we will release more energy than earth radiates away in less than 200 years. I'm not sure how the price of a limited resource can go to zero, but I'm also not very well versed in economics.
Not sure why this is a problem
- Norway
> I'm now comfortable suggesting that this approach is overlooked by mainstream medicine to the great detriment of many people suffering chronic illness
If people are interested in this, checkout https://www.amazon.com/Healing-Back-Pain-Mind-Body-Connectio...