What are the benefits of distributed computing for AI?
Distributed computing allows AI systems to process large datasets more efficiently by leveraging multiple machines.
Can you explain how it improves processing speed?
By distributing tasks across several nodes, it reduces the time needed for computations, enabling faster model training.
Are there any specific examples of AI applications that use distributed computing?
Yes, applications like deep learning, natural language processing, and big data analytics often utilize distributed computing.
What challenges come with implementing distributed computing for AI?
Challenges include network latency, data synchronization, and the complexity of managing distributed systems.
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