In the last few years, startups offering serverless GPU inference gained significant traction, filling a gap that major cloud providers like Google Cloud Platform (GCP) and Microsoft Azure had yet to address.

The concept was straightforward: provide GPU power for cloud functions that developers could easily deploy without managing the underlying infrastructure. For many backend developers, this seemed like a dream come true.

I had considered pursuing a similar startup idea when I first delved into cloud computing. Having developed a system that mimicked serverless inference on GCP for my backend architecture, I understood the potential cost savings and efficiency gains. However, I ultimately decided against it. My guiding principle is simple: don't compete directly with big tech giants. Over the years, I've shelved 20-30 startup ideas for this very reason.

Despite my reservations, many startups did pursue this space, even receiving backing from accelerators like Antler and Y Combinator. To me, it seemed like a risky bet, and recent developments have validated that view. This month, Google Cloud announced that its cloud functions would now support Nvidia GPUs.

This announcement is a game-changer for two reasons. First, it allows me to leverage serverless GPU power directly on GCP, simplifying my workflow. Second, and perhaps more significantly, it likely spells the end for many of these serverless GPU startups. Faced with competition from Google, these companies will now need to pivot quickly to avoid obsolescence.

While it may seem harsh to take satisfaction in the downfall of these ventures, it's a stark reminder of the risks of betting against tech giants.