Salvatore Salamone

In 2025, in-cabin sensing is the underlying foundation needed for legal compliance, semi-autonomous driving, safety ratings, and the premium user experience consumers now expect.

In this week’s real-time analytics news: MIT focuses on making AI-generated code more accurate in any language.

Does every AI application need a human in the loop? No. Of course not. The challenge is determining which applications need human input and when.

Long-range EVs use high-capacity battery packs, advanced energy management systems, lighter weight materials, and highly efficient electric motors to extend their driving range beyond 300 miles on a single charge.

By embracing a generative design methodology, automotive companies can navigate the complexity of EV development, improve design performance, and speed innovation.

In this week’s real-time analytics news: NVIDIA announced that it will build AI supercomputers entirely in the U.S.

CDOS is not just a technological shift but a new way of thinking about vehicle engineering. As EVs become more complex, software-driven, and reliant on system-wide optimization, CDOS will be indispensable for automakers seeking to innovate quickly and efficiently.

As the volume of video data continues to grow, the ability to understand and act on it — in real time — will become a competitive differentiator across sectors. That’s where visual analytics comes in.

Building a real-time visual intelligence system requires the tight integration of multiple architectural elements, including those that perform edge processing, visual analytics, and more.

In this week’s real-time analytics news: Google and many of its partners made announcements at the Google Cloud Next 2025 conference.

In this week’s real-time analytics news: The latest round of MLCommons Inference benchmark tests show that hardware and software advances optimized for generative AI have led to dramatic performance improvements over the past year.

In this week’s real-time analytics news: AWS expands access to expert-level analysis via natural language processing.