Startups can now train trillion-parameter models without owning a cluster. For years, scaling AI was an "arms race" only big tech could afford. GPU scarcity and cluster management meant smaller teams were locked out. Now, on-demand GPU access lets startups and research labs experiment with huge models without massive CapEx, spin up temporary clusters for heavy workloads, & pay only for what they use. AI experimentation is finally democratized! Curious to hear: how are small teams approaching large-scale model training today? Are we seeing innovation shift because compute is now elastic?