Guest Talk with Daniel Bashir | A Survey of AI for the Protocol-Minded
Daniel Bashir, ML engineer at AWS and host of The Gradient podcast, surveys how protocol thinking applies across AI—from funding and scaling laws (like DeepMind's Chinchilla compute-optimal training protocol) to benchmarks (perplexity vs. François Chollet's ARC benchmark for measuring sample-efficient generalization) to regulation (the EU AI Act's risk-tiered categorization). He argues that nearly every layer of AI development—research, engineering, deployment, and governance—can be reframed as a set of competing or evolving protocols, using examples like Sarah Hooker's 'hardware lottery' and Tolga Bolukbasi-style debates over fair/responsible AI operationalization.
Daniel Bashir
