The history of neural networks is longer than most people think. While the idea of “a machine that thinks” can be traced to the Ancient Greeks, we’ll focus on the key events that led to the evolution of thinking around neural networks, which has ebbed and flowed in popularity over the...
The history of neural networks is longer than most people think. While the idea of “a machine that thinks” can be traced to the Ancient Greeks, we’ll focus on the key events that led to the evolution of thinking around neural networks, which has ebbed and flowed in popularity over the...
I hope I've given you a taste of how powerful Convolutional Neural Networks are. You give them example images with some labels, they learn to recognize those things automatically, and it all works very well and is very fast (at least at test time, once it's trained). Of course, we'v...
Given his well-publicized attacks on the field, it might surprise you that Marcus still believes AGI is on the horizon. It’s just that he thinks today’s fixation on neural networks is a mistake. “We probably need a breakthrough or two or four,” he says. “You and I might not li...
The context for this paper is that, in the last few years, speech recognition technology has been gradually replacing its acoustic models with neural networks. A speech recognition system works by examining at the acoustics at each time point to decide what sound is being pronounced. Each sound...
A spiking neural network is essentially the hardware version of an artificial neural network, which is a series of algorithms run on a regular computer that mimics the logic of how a human brain thinks.How Neuromorphic Computing Differs From Traditional Computing...
And what happens if Moore's law stops? Someone says he's already stopped. Someone thinks that this has not happened yet. Why did the problem of stopping Moore's law arise, and does it exist at all? Let's try to figure it out. ...
An algorithm that combines Q-learning with neural networks, helping the model to learn optimal strategies in complex environments. Note: For each type of learning there are dozens of different algorithms with more being developed, customized and released every week. How is machine learning used in...
So when the mind thinks about itself, it will again make a model. Our experiences may start by making models of the “outside world”. But then we’ll recursively make models of the models we make, perhaps barely distinguishing between “raw material” that comes from “inside”...
What an ANN thinks dumbbells look like, from training with photos. Things are just getting started. Google's been training its photo-analysis algorithms with more and more pictures of animals, and they're getting pretty good at telling dogs from cats in regular photographs. Both translation a...