3 ms·
While I won't dispute that many in AI thought machine learning was the correct path, the majority of researchers in machine learning in the 2000s were dismissiv
by chriskanan 9y ago
While I won't dispute that many in AI thought machine learning was the correct path, the majority of researchers in machine learning in the 2000s were dismissive of neural networks as the way forward. When I started my PhD in 2007 with the specific goal of studying deep learning, many of my peers told me this was a very bad career move, because neural networks were a dead technology. Convex optimization, kernels, and variational Bayesian methods were the future. They were wrong.
AI has had a lot of fads, but neural networks are here to stay, in my opinion.
- robotresearcher 9y agoConvex optimization, kernels and Bayesian methods are also here to stay. They are all in the toolbox. Optimization-based methods are still rapidly spreading in robotics, for example, even as we add CNNs to the mix.
- shaklee3 9y agoConvex optimization is heavily used in industry for real problems. It just doesn't have the sexiness that neural networks too, so it doesn't get as much attention.
- chriskanan 9y agoI agree. My comment about being wrong was regarding neural networks being a dead end. Convex optimization and Bayesian techniques are both incredibly useful.