THE VOCABULARY OF AI
NVIDIA
graphics was also a perfect fit for the complex parallel computing required by deep learning . This form of artificial intelligence enables computers to learn from data and write software that is too complex for people to code .
NVIDIA recognised the opportunity presented by this affinity between deep learning and the GPU . Since then , it has been investing in a new computing model , GPU-accelerated deep learning , which is helping to create computers , robots and self-driving cars that can perceive and understand the world .
“ Although AI has been around for a long time , before now the processing power needed for it to succeed just wasn ’ t available ,” explains Jackson . “ Now , NVIDIA is working to democratise AI for all .”
Pure Storage also recognised data is the fuel to drive deep learning , and parallel architecture is the future . It built a new data platform from the ground-up to keep pace with the innovation curve of GPUs .
“ Deep learning is unique among all learning algorithms in that it keeps getting better with more data ,” says James Petter , VP EMEA
Jensen Huang - NVIDIA CEO
at Pure Storage . “ At Pure , we believe data should never be the bottleneck for data scientists .”
THE VOCABULARY OF AI
The first step in realising the business benefits of AI is to understand a few fundamentals . When we talk about AI , three terms tend to be used interchangeably : artificial intelligence , machine learning and deep learning . Their relationship
42 October 2017