Model inversion and membership inference attacks create unique risks to organizations that are allowing artificial intelligences to be trained using their data. Companies may wish to begin to evaluate ...

Enterprises expanding AI deployments are hitting an invisible performance wall. The culprit? Static speculators that can't keep up with shifting workloads. Speculators are smaller AI models that work ...

JMIR Publications today released a report on developments in the evidence gap in drug safety during pregnancy in its News and ...

A startup specializing in AI inference pulled in $20 million in funding from investors including AMD, Nvidia, and neocloud ...

As AI continues to revolutionize industries, new workloads, like generative AI, inspire new use cases, the demand for efficient and scalable AI-based solutions has never been greater. While training ...

Nebius (NASDAQ: NBIS), the AI cloud company, today announced that the core engineering and research team from Clarifai, led by founder and CEO Matthew Zeiler, is joining Nebius. Nebius has also agreed ...

The AI industry stands at an inflection point. While the previous era pursued larger models—GPT-3's 175 billion parameters to PaLM's 540 billion—focus has shifted toward efficiency and economic ...

Global technology intelligence firm ABI Research forecasts that AI inference workloads will grow at a 42% CAGR to surpass 46 Gigawatts of capacity consumption by 2035, overtaking training workloads by ...

RIT computer science professor Weijie Zhao has earned a National Science Foundation CAREER Award to defend machine learning ...

In data analysis, time series forecasting relies on various machine learning algorithms, each with its own strengths. However, we will talk about two of the most used ones. Long Short-Term Memory ...