Now that the dust from Nvidia’s unveiling of its new Ampere AI chip has settled, let’s take a look at the AI chip market behind the scenes and away from the spotlight

Few people, Nvidia’s competitors included, would dispute the fact that Nvidia is calling the shots in the AI chip game today. The announcement of the new Ampere AI chip in Nvidia’s main event, GTC, stole the spotlight last week.

There’s been ample coverage, including here on ZDNet. Tiernan Ray provided an in-depth analysis of the new and noteworthy with regards to the chip architecture itself. Andrew Brust focused on the software side of things, expanding on Nvidia’s support for Apache Spark, one of the most successful open-source frameworks for data engineering, analytics, and machine learning.

Let’s pick up from where they left off, putting the new architecture into perspective by comparing against the competition in terms of performance, economics, and software.

The gist of Ray’s analysis is on capturing Nvidia’s intention with the new generation of chips: To provide one chip family that can serve for both “training” of neural networks, where the neural network’s operation is first developed on a set of examples, and also for inference, the phase where predictions are made based on new incoming data.

Read the full article on ZDNet