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 ...

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 ...

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

Google has introduced the Coral Board, a compact single-board computer designed for local AI inference and edge computing applications. Announced during the Google I/O 2026 developer conference, the ...

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 answer to token maxing is not less AI. It is purpose-built machine learning and right-sized models, says Zoho’s Ramprakash Ramamoorthy.

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

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 ...

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 ...

Samuel Kaski’s two-part research lab in ELLIS Institute Finland (Probabilistic Machine Learning, Aalto University) and the Centre for AI Fundamentals in University of Manchester, is searching for ...