BatMan: Mitigating Batch Effects Via Stratification for Survival Outcome Prediction Real-world data (RWD) derived from electronic health records (EHRs) are often used to understand population-level ...

AI inference uses trained data to enable models to make deductions and decisions. Effective AI inference results in quicker and more accurate model responses. Evaluating AI inference focuses on speed, ...

Expertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. We are still only at the beginning of this AI rollout, where the training of models is still ...

As frontier models move into production, they're running up against major barriers like power caps, inference latency, and rising token-level costs, exposing the limits of traditional scale-first ...

The major cloud builders and their hyperscaler brethren – in many cases, one company acts like both a cloud and a hyperscaler – have made their technology choices when it comes to deploying AI ...

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 is strategically positioned to dominate the rapidly growing AI inference market, which could be 10x larger than training by 2030. The MI300X's memory advantage and ROCm's ecosystem progress make ...