What are the risks associated with memory reclamation in AI systems?
Memory reclamation in AI systems can lead to data loss, performance issues, and unintended behavior if not managed properly.
Can you explain how data loss occurs during memory reclamation?
Data loss can occur if the system mistakenly frees memory that is still in use or if it fails to properly save important data before reclamation.
What performance issues might arise from improper memory reclamation?
Improper memory reclamation can lead to memory leaks, increased latency, and overall system instability, affecting user experience.
Are there any best practices to mitigate these risks?
Yes, implementing thorough testing, using memory management tools, and following coding standards can help mitigate these risks.
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