AI systems, the study shows, have enhanced accuracy, efficiency, and inclusivity in decision-making. For instance, urban management platforms powered by AI can process massive streams of real-time ...

Synthetic data, artificially generated datasets used to train AI models when real data are limited, private, or biased, has become central to modern machine learning. Companies and institutions ...

The brain’s function and integrity emerge not only from properties of individual regions, but, more fundamentally, from the intricate web of connections ...

SLMs targeted at specific workloads could change the relationship between edge devices and the cloud, creating new opportunities for chipmakers, EDA companies, and IP vendors.

As David Patterson observed in 1980, “A RISC potentially gains in speed merely from a simpler design.” Patterson’s principle of simplicity underpins a new alternative to speculation: A deterministic, ...

AI & Automation: Supply privacy-safe unstructured datasets for training and validating document AI models. For more information, visit their website. About GenRocket GenRocket is the global leader in ...

In an era defined by increasing volatility from climate change and complex infrastructure challenges, Canadian 6D simulation ...

SMHX focuses on fabless semiconductors with top AI exposure, cost-efficient foundry partnerships, and long-term growth potential. Learn why SMHX ETF is a buy.

Apple CEO Tim Cook confirms more AI models like ChatGPT, Gemini, and Claude are coming to Apple Intelligence. Here’s what that means for iPhone and Siri users in Nigeria.

From designing proteins not found in nature to extending healthy lifespan, Retro Biosciences is applying AI models to advance cellular reprogramming for aging research. The company operates across ...

Make responsible AI part of system design and deployment, not an afterthought. Industry experts offer guidelines for building and managing responsible applications.

A machine learning model using basic clinical data can predict PH risk, identifying key predictors like low hemoglobin and elevated NT-proBNP. Researchers have developed a machine learning model that ...