Google recently announced that it will be purchasing chips from Movidius, which makes low-power machine-learning processors.
First, we used shotgun proteomics to generate fragmentation spectra, and we assigned a peptide to each spectrum using a database search procedure coupled with a machine learning post-processor.
In our previous work, depending on the execution characteristics of real-time tasks, DVFS decisions were made using machine learning method in unicore processors.
There is no doubt that we are now swimming in an expanding sea of data that is too voluminous to train a machine learning algorithm with a central processor and storage.
There Google scientists created one of the largest neural networks for machine learning by connecting 16,000 computer processors, which they turned loose on the Internet to learn on its own.
But the combination of 3D cameras, real-time processors and machine learning is poised to make an impact that is broader and deeper.
After moving into GPUs in recent years, the company today announced that it will now offer its partners machine learning and dedicated object detection processors.
Announced last month, Arm's Project Trillium is a series of scalable processors designed for machine learning and neural networks.
Before the processors required for machine learning were too large an energy drain for power-hungry smartphones, but Movidius' new chips purport to be very low energy, allowing the complex processes required for deep learning to take place -- without completely draining your phone's battery in minutes.
The recent advances in data science and computing disciplines neuromorphic processors, big data, predictive modeling, machine learning, natural language understanding, and cloud computing are accelerating advances in cognitive science and cognitive computing.
