The trade-off is performance. Every syscall goes through user-space interception, which adds overhead. I/O-heavy workloads feel this the most. For short-lived code execution like scripts and tests, it is usually fine, but for sustained high-throughput I/O, it can matter.
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Merlin, a vision–language foundation model trained on a large dataset of paired CT scans, patient record data and radiology reports, demonstrates strong performance across model architectures, diagnostic and prognostic tasks, and external sites.
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