EmTech MIT: Giving machines common sense
We have lot of AI technologies, but no real artificial intelligence. MIT's Josh Tenenbaum leads a moonshot effort to close this gap by reverse engineering how children learn.
Latest from John Morris
Nvidia aims to run neural nets faster, more efficiently
As data gets bigger and models grow larger, deep learning is once again "completely gated by hardware." At the VLSI Symposia, Nvidia suggested some ways to address this problem.
How Facebook scales AI
Facebook's products and services are powered by machine learning. Powerful GPUs have been one of the key enablers, but it takes a lot more hardware and software to serve billions of users.
Wave Computing close to unveiling its first AI system
The chip startup's novel architecture promises to make training neural networks faster and easier.
Nvidia makes the case for GPU accelerators
Moore's Law is slowing down as emerging AI workloads are demanding more performance. But Nvidia says it's got a plan. At this year's GPU Technology Conference, it announced powerful hardware and software for deep learning.
IBM talks about progress on Watson, OpenPower
Five years after Watson won Jeopardy, IBM says cognitive computing is catching on. At the GPU Technology Conference, the company talked about the evolution of Watson services accelerated on Power servers and GPUs.
Nvidia goes all in on AI
The company is making a big bet on deep learning with its Tesla P100 GPU and DGX-1 server.