One signal

AI inference providers and neoclouds may need to sell more than access to computing power to escape commodity pricing pressure, argues a ScaleVP blog post published on 11 November.

Its proposed route is to use low-cost compute to win customers, then offer higher-value services such as fine-tuning, reinforcement learning and custom model serving. Those services could improve margins and make customers less likely to switch. The catch, the author argues, is that climbing the software stack is harder now than it was for AWS, with established rivals and aggressive hyperscalers already in place. Cheap compute gets the conversation started; it may not be a business model on its own.

Discuss: Can inference providers build durable businesses by adding software services, or will hyperscalers make that climb too difficult?

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