The cloud giants are giving away billions in free compute to AI startups, but the credits are a loss leader designed to lock in the next Anthropic before it outgrows the platform
The vendor lock-in angle here is way more critical than people realize. Saw a team last year burn through their AWS credits training a model, then discover migrating to GCP would mean rewriting half their infra. The switching costs aren't just technical either, once your team learns one ecosystem's quirks (IAM policies, specific SageMaker workflows) the cognitive load of migrating is brutal even if the actual code ports cleanly.
For sure, another consideration is latency. GenAI can move much faster if the data is on one server compared to multi-cloud. So even if you hedge yourself with multiple hyperscalers, you could compromise your internal or external products.
It's actually driven some companies to move more data on-prem, I bet this was a consideration for Twitter.
The vendor lock-in angle here is way more critical than people realize. Saw a team last year burn through their AWS credits training a model, then discover migrating to GCP would mean rewriting half their infra. The switching costs aren't just technical either, once your team learns one ecosystem's quirks (IAM policies, specific SageMaker workflows) the cognitive load of migrating is brutal even if the actual code ports cleanly.
For sure, another consideration is latency. GenAI can move much faster if the data is on one server compared to multi-cloud. So even if you hedge yourself with multiple hyperscalers, you could compromise your internal or external products.
It's actually driven some companies to move more data on-prem, I bet this was a consideration for Twitter.