Local AI, Rethinking Neural Networks, and Talking Pumpkins
How much would you pay to keep your AI out of the cloud?
Sara and Becca work through the economics of running models locally: the hardware bill, the privacy benefits, and why fitting a massive model on two Mac Studios is only part of the equation. Sara also explains how agents and verification loops could tackle one of engineering’s most expensive headaches: software migrations that never seem to end.
Then, interpretability researcher Nick Cammarata is revisiting some of the field’s foundational assumptions. What if neural networks are more understandable than we thought? We unpack his…
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