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This isn't an argument against platforms like Vapi or ElevenLabs. Those systems offer far more than orchestration: APIs, observability, reliability, and deep config options that would take real effort to reproduce. For most teams, rebuilding all of that would be a mistake - being able to test and validate a voice agent app without getting to this level of technical depth is truly amazing, and that's how I first got excited about the technology.
It’s time to pull the plug on plug-in hybrids
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Can these agent-benchmaxxed implementations actually beat the existing machine learning algorithm libraries, despite those libraries already being written in a low-level language such as C/C++/Fortran? Here are the results on my personal MacBook Pro comparing the CPU benchmarks of the Rust implementations of various computationally intensive ML algorithms to their respective popular implementations, where the agentic Rust results are within similarity tolerance with the battle-tested implementations and Python packages are compared against the Python bindings of the agent-coded Rust packages:
When those councils are factored in, more than a third of councils will still not be collecting food waste from all homes by March.，更多细节参见夫子