India, Aug. 26 -- Cloud AI has made experimentation easier. But once artificial intelligence (AI) workloads move into continuous inference, model testing, and sensitive-data processing, enterprises can find themselves dealing with recurring graphics processing unit (GPU), storage, and application programming interface (API) costs.

For Indian technology leaders, the question is therefore shifting from whether AI should be adopted to where those workloads should run.

Apple's newly launched M5 Ultra Mac Studio brings that decision into sharper focus. The system supports up to 512GB of unified memory, offers 1.2TB/s of memory bandwidth, and allows multiple Mac Studio systems to be clustered for distributed AI workloads.

It is one example o...