Ceramic.ai, a startup for training AI by Anna Patterson, ex-Google VP of Engineering and founder of Gradient Ventures, has raised $12 million in seed funding to revolutionize large-scale AI training. The funding round was supported by NEA, IBM, Samsung Next, and Earthshot Ventures, who appreciated the startup’s innovations in long-context training and 2.5x faster training times than current state-of-the-art techniques.
This would mean that AI industry players will have to meet massive computational requirements, which are weeks or months for models such as GPT-4, with 1.7 trillion parameters. These are just for the tech giants with deep pockets. Ceramic.ai is focused on dramatically accelerating training times while reducing compute costs so that the field is leveled out for enterprises and researchers.
Breaking AI Training Barriers: The Power of Ceramic.ai
Established in early 2024 by Anna Patterson and Chief Scientist Tom Costello, Ceramic.ai addresses distributed AI training inefficiencies through optimizing GPU utilization and eliminating bottlenecks due to limited chip availability. The platform allows AI training with unparalleled scale and efficiency, making it possible for businesses to develop powerful AI models without the billion-dollar infrastructure spend.
Anna Patterson described the vision of the company:
“At Google, I saw firsthand how only the biggest tech companies could afford to train massive AI models. Enterprises were left behind. AI training can scale 10x, but not 100x—until now. Ceramic.ai is here to change that. We’re making high-performance AI training radically more efficient and accessible, ensuring businesses don’t need billions in compute resources to compete.”
A Next-Gen AI Training Platform for the Enterprise:
Ceramic.ai is not another AI infrastructure solution—it’s an end-to-end AI training backbone for business. Contrary to the usual brute-force approach of GPU scaling, Ceramic trains AI at the algorithmic level, providing:
2.5x Speedup Training – Beyond open-source efficiency
Enterprise Scalability – Efficient handling of 70B+ parameter models
Best Model Performance – 92% Pass@1 accuracy on GSM8K (compared to Meta’s Llama70B with 79% and DeepSeek R1 at 84%)
Intelligent Data Reordering – Aligning training batches by topic for better efficiency
By optimizing long-context model training, Ceramic.ai eliminates inefficiencies like token masking issues, ensuring AI models process high-fidelity, large-scale data without waste.
What’s Next?
The $12M funding will be used to:
Refine Ceramic.ai’s AI training infrastructure
Expand enterprise adoption, making AI training as easy as cloud deployment
Push the limits of compute efficiency, empowering businesses to build their own foundation models affordably
Patterson concluded:
“The AI boom is just beginning, but businesses are still struggling with scaling costs and infrastructure constraints. Ceramic.ai is here to change that—democratizing AI training so enterprises can compete at the highest level. If AI adoption were a baseball game, we’d still be singing the national anthem.”
With state-of-the-art technology and powerhouse leadership, Ceramic.ai is geared toward defining the new standard for AI training generation that can open up high-performance AI development to become accessible, efficient, and cost-effective.
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