Bigger Models Aren’t the Only Path Forward
For the last few years, the artificial intelligence industry has been obsessed with size.
Every few months a new model arrives with more parameters, more computing power, and a larger training budget. The assumption seems obvious: if you want better AI, you build a bigger AI.
But history suggests there may be another path.
To see it, we need to leave ...
This piece presents a compelling critique of the "bigger is better" paradigm in AI, using the industrial revolution as a metaphor to argue for architectural innovation over brute-force scaling. The strongest version of this narrative highlights real inefficiencies in current AI systems—centralized, resource-intensive, and inflexible—while offering a plausible alternative: modular, task-specific workflows that could reduce costs and improve quality. The analogy to factories is effective, groundin...