“Second-tier cloud providers like Vultr, Akamai, IBM, Alibaba, Tencent, and Huawei differentiate themselves by focusing on niche markets and specific customer needs, as opposed to the hyperscalers’ broad, one-size-fits-all approach,” says David Linthicum, a cloud and AI thought leader who previously served as managing director and chief cloud strategy officer at Deloitte Consulting. “These providers thrive in areas where specialization, flexibility, and cost efficiency matter most.”
Intellectual property protection was a significant reason behind Athos’ move to Vultr’s GPU cloud, Guo says, as doing so would better protect its model IP, while conforming with industry regulations and compliance. The GPU-as-a-service model also minimizes the constantly evolving maintenance requirements of an AI infrastructure, including downloading massive amounts of genomics data, internet updates, and swapping Nvidia cards in and out, he says.
Athos could have opted for one of the big three hyperscalers — AWS, Google Cloud, or Microsoft Azure — but training its algorithms and scaling various types of scientific omics data would be prohibitively expensive on those platforms, Guo says.
