New Signalful Analysis Which AI bottleneck takes longest to fix? Power takes years to expand. Models can change in months. Google is expected to spend more than $200 billion on AI infrastructure this year, mostly on data centers. Yet a voice-agent customer cut costs by switching models on ordinary Nvidia GPUs. Both are responses to constraints, but they require different commitments. Which AI bottleneck takes longest to fix, and what should you do about it? Link below to the free article. (From interviews with Walter Goodwin of Fractile, Thomas Sohmers of Positron AI, Stefano Ermon of Inception, Amin Vahdat of Google, Zach Dell of Base Power, Jensen Huang of Nvidia and Pat Gelsinger of Playground Global)