What are parallel systems in AI?
Parallel systems in AI refer to architectures that process multiple tasks simultaneously, improving efficiency.
Can you give me examples of parallel systems used in AI?
Sure! Examples include multi-core processors, GPUs, and distributed computing frameworks like Apache Spark.
What are the benefits of using parallel systems in AI?
The benefits include faster processing times, improved performance on large datasets, and enhanced scalability.
Are there any challenges associated with parallel systems?
Yes, challenges include complexity in programming, data synchronization issues, and potential bottlenecks.
How do parallel systems compare to traditional systems in AI?
Parallel systems can handle larger workloads and perform tasks more efficiently than traditional sequential systems.
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