I’ve done research in the topic before and stopped at Convolutional Neural Networks. So to me this claim sounds misleading and it’s been used every now and then by people who got carried by the hype. As far as I know the core behind neural network never changed, the model ingests training data, iterates over the best answer (Gradient Descent), generates it’s parameters in a multidimensional space, and hence is allowed to converge into an “answer” when on a question about data of the same sort. Why is it that if it takes a trillion calculations to detect a hand written N°4 people go out assuming we don’t know how it works internally? All papers I’ve read up to know talk about changes in architecture, attention and such, but it’s all the same concept. submitted by /u/nezvanovova
Originally posted by u/nezvanovova on r/ArtificialInteligence
You must log in or # to comment.