The next generation of inference platforms must evolve to address all three layers. The goal is not only to serve models efficiently, but also to provide robust developer workflows, lifecycle ...

Edge AI is the physical nexus with the real world. It runs in real time, often on tight power and size budgets. Connectivity becomes increasingly important as we start to see more autonomous systems ...

Machine-learning inference started out as a data-center activity, but tremendous effort is being put into inference at the edge. At this point, the “edge” is not a well-defined concept, and future ...

Over the past several years, the lion’s share of artificial intelligence (AI) investment has poured into training infrastructure—massive clusters designed to crunch through oceans of data, where speed ...

AMD (AMD) is rated a 'Buy' based on its architectural strengths and plausible 3-5 year EPS growth framework. AMD’s higher memory bandwidth and capacity position it well for the rapidly compounding ...

The market for serving up predictions from generative artificial intelligence, what's known as inference, is big business, with OpenAI reportedly on course to collect $3.4 billion in revenue this year ...

Until recently, most AI was in data centers/cloud and most of that was training. Things are changing quickly. Projections are AI sales will grow rapidly to tens of billions of dollars by the mid 2020s ...