However, GPUs are not all that. As I’ve pointed out here many times, GPUs may be overengineering AI systems when commoditized CPUs would do just fine. Indeed, I see a future when GPUs won’t be discussed at all. Instead, they will just bake into AI architectures. I’m not sure why we focused so much on that part of AI architecture in the first place.
Quantum computing’s potential
Quantum computing, while promising, is still mainly in the realm of future potential. The industry is making strides towards more advanced qubits and increased stability. However, the practical utility of these advancements remains over the horizon for many organizations. This timeline, coupled with the steep learning curve and investment required, has positioned quantum computing as a slower-evolving technology compared to AI.
Moreover, the current quantum offerings, often accessed via cloud platforms, are still primarily experimental. They require specialized knowledge to leverage effectively, whereas GPUs integrated into cloud services can be readily used to scale existing AI operations with relatively lower barriers to entry.
