Part 7/20:
Inference vs. Model Size: Increasing model size isn’t straightforward. Bigger models deliver better performance but are slower and more expensive to serve. The diminishing returns on scaling are contrasted with the exponential benefits of advanced algorithms and hardware optimizations.
Speed, Capacity, and User Experience: Improving inference speed (latency) may unlock bigger, smarter models that can serve more users faster. The ideal scenario combines maximum capacity with minimal latency, but the engineering trade-offs make this a persistent challenge.