Utilize AI to analyze application runtime data (e.g., rendering time, communication latency), obtain optimization suggestions (such as reducing component re-rendering, reusing hardware connections), ...

In software development, success means going beyond meeting requirements. We must create products that surprise and delight ...

For IT and HR teams, SLMs can reduce the burden of repetitive tasks by automating ticket handling, routing, and approvals, ...

Step aside, LLMs. The next big step for AI is learning, reconstructing and simulating the dynamics of the real world.

At the core of every AI coding agent is a technology called a large language model (LLM), which is a type of neural network ...

Upcoming software purchases should no longer be one-time contracts; they're living partnerships built on shared data and trust.

There's a rush to amass as much data as possible to train AI models. Amazon is trying to scrape Microsoft's Github for some of the data it needs.

Try Gemini 3.0 Flash via AI Studio and APIs, with up to 90% savings from context caching to cut costs on high-volume ...

Anthropic releases its Agent Skills framework as an open standard, with Microsoft, OpenAI, Atlassian, and Figma already ...

C compiler, LustreC, into a generator of both executable code and associated specification. Model-based design tools are ...

AI Impact highlights Rivian’s autonomy strategy, hybrid AI gains in healthcare, AGI skepticism, exec moves and AI Impact ...

For learning here, let’s thank IBM for explaining that, “Diffusion algorithms, particularly Diffusion Models, are advanced AI ...