"Startup founders are being pushed to move faster than ever, using AI while facing tighter funding, rising infrastructure costs, and more pressure to show real traction early. Cloud credits, access to GPUs, and foundation models have made it easier to get started, but those early infrastructure choices can have unforeseen consequences once startups move beyond free credits and into real cloud bills."
"On this episode of TechCrunch's Equity podcast, Rebecca Bellan caught up with Darren Mowry, Google Cloud's vice president of global startups who is right at the center of those tradeoffs. Watch as they discuss what Mowry's seeing across the startup ecosystem, how Google Cloud is competing for AI startups, and what founders should be thinking about as they scale. Subscribe to Equity on YouTube, Apple Podcasts, Overcast, Spotify and all the casts. You also can follow Equity on X and Threads, at @EquityPod."
Startups face accelerating timelines to build AI capabilities while navigating tighter funding, rising infrastructure costs, and pressure to show early traction. Cloud credits, accessible GPUs, and foundation models lower the barrier to experimentation and initial deployment. Early infrastructure choices often become costly when free credits expire and operations move to full cloud billing. Cloud providers actively compete to attract AI startups by offering credits, tooling, and access to models and hardware. Founders should prioritize cost-aware architecture, scalability planning, and infrastructure tradeoffs to avoid surprises and manage long-term cloud expenses while scaling AI products.
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