Manufacturing
For years, AI development has been dominated by a handful of tech giants with the resources to train and deploy advanced foundation models. The high costs, complex infrastructure, and specialized engineering expertise required for large-scale AI have made it difficult for most enterprises to compete. Ceramic.ai, founded by former Google VP of Engineering Anna Patterson, aims to change that by making AI training not just faster, but fundamentally more scalable and accessible to businesses beyond Silicon Valley’s elite. To understand how this landscape is shifting, AIM Research sat down with Anna Patterson, in an exclusive interview.
Anna Patterson’s decision to launch Ceramic.ai was driven by a firsthand understanding of AI’s infrastructure challenges. “At Google, I saw how the scale and efficiency of AI infrastructure determined who could successfully train and deploy foundation models,” Patterson explained. “Only a handful of tech giants have the resources to develop high-performance AI models, while most enterprises struggle with skyrocketing compute costs, slow training cycles, and infrastructure bottlenecks. This is what drove me to start Ceramic.ai—to level the playing field and give any company the ability to train their own models at a fraction of the cost and time.”
The biggest challenge in bringing Ceramic.ai from concept to reality was ensuring it was not just incrementally better, but fundamentally different. “We knew improving training speed alone wouldn’t be enough,” Patterson said. “We had to rethink how data, compute, and scaling worked together. That meant tackling long-context training, optimizing data ordering, and creating infrastructure that scales efficiently.”
