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Each of these categories opens up challenging problems in AI/visual algorithms, high-density computing, bandwidth/latency, distributed systems. Such innovation in AI algorithms and approaches results in an increase in model size, exponential growth in the compute needs, caching of temporal states, and multiple models to run simultaneously.
This approach was touted to be better for fine-grained caching because each subresource could be cached individually and the full bundle didn’t need to be redownloaded if one of them changed. Finally, not inlining resources has an added latency cost because the file needs to be requested. Large preview ). What Does It All Mean?
Because we are dealing with network protocols here, we will mainly look at network aspects, of which two are most important: latency and bandwidth. Latency can be roughly defined as the time it takes to send a packet from point A (say, the client) to point B (the server). Two-way latency is often called round-trip time (RTT).
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