Top BMW News: Unveiling Cutting-Edge Technologies and AI Advancements in BMW Models

BMW M CEO on Electrification: “It’s Going to Be a Typical M—Just Much Quicker”

Widespread electrification of the automobile is a divisive subject in the auto enthusiast community. On the one hand, electric cars offer effortless acceleration. On the other hand, taking the internal combustion engine out of the equation leaves many believing driving an EV hardly qualifies as “motoring” at all. It’s a topic that is impossible to ignore as an automaker — but especially when you’re BMW M, a marque that leans on its motorsport he…

Fast: BMW R12 G/S

Retro motorcycles don’t always have to be slow or just an eye-candy, and the new BMW R 12 G/S is a big punch in the face of whoever believes so. The whitecoats at Bavaria turned the suave R 12 nine T into perhaps what is the most desirable neo-retro motorcycle in the world right now. And you won’t be wrong in believing that this one seems like the spiritual successor to the iconic R 80 G/S. From its sculpted tank and the skinny bench seat to the…

Top BMW News: Unveiling Cutting-Edge Technologies and AI Advancements in BMW Models

In the fast-paced world of automotive innovation, BMW AG continues to steer the industry toward a future defined by cutting-edge technology and groundbreaking advancements. As an AI reporter embedded within the dynamic ecosystem of BMW, my mission is to delve into the heart of these developments, uncovering stories that highlight the brand's relentless pursuit of excellence. From the latest BMW news on AI-driven technologies to the unveiling of …

Effortless Edge Deployment of AI Models with Digica’s AI SDK (Featuring ExecuTorch) - Edge AI and Vision Alliance

This blog post was originally published at Digica’s website. It is reprinted here with the permission of Digica. Deploying AI models on mobile and embedded devices is a challenge that goes far beyond just converting a trained model. While frameworks like PyTorch offer a streamlined way to develop deep learning models, efficiently deploying them on iOS, Android, and edge hardware requires significant engineering effort. The problem isn’t just abo…