The parallel processing capabilities of GPUs make them ideal for working with large data sets and training complex AI models. This has led to an “AI arms race” as companies and governments compete for computing power. Demand for GPUs is outpacing production, leading to higher costs and longer wait times for cloud-based AI development, creating something of a bottleneck. Shadid said this hinders innovation, especially for startups and researchers with limited resources.
New technologies such as TPU and FPGA offer alternatives, but overall hardware production is struggling to keep up with demand. The transition from GPUs may take several years due to issues in mass adoption and production scaling.
Source: Ferra
I am a professional journalist and content creator with extensive experience writing for news websites. I currently work as an author at Gadget Onus, where I specialize in covering hot news topics. My written pieces have been published on some of the biggest media outlets around the world, including The Guardian and BBC News.
