in

NVIDIA: Implementing strategic workloads for AI!

A quick look at how NVIDIA is using technology to support AI workloads.

In electronics, PCs, and gaming consoles, NVIDIA develops integrated circuits. GPUs (graphics processing units) are the company’s main products. Artificial intelligence drives change in every industry around the world. From speech recognition and recommender systems to medical imaging and improved supply chain management, artificial intelligence provides enterprises with the tools, algorithms, and compute power they need to do their best work.

Artificial intelligence drives change in every industry around the world. From speech recognition and recommender systems to medical imaging and improved supply chain management, artificial intelligence provides enterprises with the tools, algorithms, and compute power they need to do their best work.

For more than 25 years, NVIDIA has developed computer graphics solutions that can solve challenges that ordinary computers can’t, and its partners have helped bring those solutions to market. Today’s machine learning and artificial intelligence (AI) workloads require an accelerated compute platform designed for machine learning and AI workloads. NVIDIA-accelerated computing opens up tremendous new markets for its entire ecosystem at the intersection of virtual reality, high-performance computing, and artificial intelligence.

GPUs from NVIDIA are based on a platform strategy. This means the hardware and software are combined to offer a set of services and tools to enhance their capabilities. As an example, its software libraries, SDKs, and API frameworks contribute to the smooth and efficient running of deep and machine learning models.

It is crucial for cloud data providers who serve primarily the artificial intelligence and machine learning industries. Cloud computing, in fact, is the foundation upon which entire industries have been built (the entire SaaS industry has been built on top of these cloud providers, as well as Netflix, Spotify, YouTube, and major streaming services).

Therefore, GPUs have a unique value proposition in that they can handle large amounts of data. In this case, NVIDIA emphasizes performance and efficiency. With its accelerator libraries, APIs, and tools, along with NVIDIA’s programming models (like CUDA), NVIDIA’s offering is well suited to these enterprise customers.

Written by IOI

Get the latest stories from Tech & Innovation from around the globe. Subscribe Now!

Leave a Reply

Your email address will not be published. Required fields are marked *

134

Satellites orbit the Earth in what number?

Space

Red Planet floods caused by climate change: Perseverance rover!