Being able to deploy machine learning applications at the edge bears the promise of unlocking a multi-billion dollar market. For that to happen, hardware and software must work in tandem. Arm's ...

Diagrams can represent details of the parallelized operations that deep-learning models consist of, revealing the relationships between algorithms and the parallelized graphics processing unit ...

Machine learning is a rising star in the compute constellation, and for good reason. It has the ability to not only make life more convenient – think email spam filtering, shopping recommendations, ...

If you’ve looked into GPU-accelerated machine learning projects, you’re certainly familiar with NVIDIA’s CUDA architecture. It also follows that you’ve checked the prices on… ...

Arm says that Project Trillium machine learning hardware, which remains unnamed, will be landing in RTL form sometime mid-2018. To expedite development, ...

That is to say, machine learning is a subset of AI, and deep learning is a subset of ML (see diagram). General artificial intelligence is a set of instructions that tell a computer how to act or ...

Machine-learning algorithms can run on microcontrollers, but for complex applications, one really needs hardware acceleration. ... Accelerating Machine Learning Means New Hardware. May 15, 2020.

The trend so far has suggested that machine learning requires a dedicated piece of hardware, like a Neural Processing Unit (NPU), IPU, or “Neural Engine”, as Apple would call it. However, the ...

Google Launched a New Machine Learning Journal and it support reactive diagrams September 4, 2018 March 31, 2017 by Brian Wang In collaboration with OpenAI, DeepMind, YC Research, and others, Google ...

A new technical paper titled “A Survey on Machine Learning in Hardware Security” was published by researchers at TU Delft. Abstract “Hardware security is currently a very influential domain, where ...