The next phase of AI infrastructure will not be defined by a single destination called “the cloud” or “the edge.” ...

The simplest definition is that training is about learning something, and inference is applying what has been learned to make predictions, generate answers and create original content. However, ...

Just when investors may have gotten a firm grasp on artificial intelligence (AI), the game is changing again. According to Deloitte Global's TMT Predictions 2026 report, inference will account for two ...

Optimizing AI inference through real time infrastructure visibility, continuous capacity planning, and intelligent DCIM for ...

However, the AI market is also splitting into two as it expands. Let's take a look at those two markets -- training and inference -- and see which one will grow faster in 2026 and beyond. The AI ...

When it's all abstracted by an API endpoint, do you even care what's behind the curtain? Comment With the exception of custom cloud silicon, like Google's TPUs or Amazon's Trainium ASICs, the vast ...

LLM training data mixture optimization breaks when training pools shift — every prior proxy experiment becomes stale.

Enterprise conversations around artificial intelligence are beginning to shift noticeably. For the past few years, much of ...

AI/ML can be thought about in two distinct and essential functions: training and inference. Both are vulnerable to different types of security attacks and this blog will look at some of the ways in ...

Artificial Intelligence chip startup Etched has secured $800 million in total funding, positioning itself to ship inference-focused silicon to customers this ...