Context
The demand for AI computation is growing faster than the availability of high-end GPUs and dedicated infrastructures. Cupseli’s vision is to harness underused distributed power for large-scale AI workloads, without building new data centers, thus lowering costs and carbon footprint.
Ambition
- Fine-tuning & inference across volatile resources
- Optimized memory, computation, and communications
- Security, privacy, and fault tolerance by design
- Greener, sovereign alternative to centralized data centers
Axis 1 — Frugality
Adapt training and inference to limited, dynamic resources: fault tolerance, activation/weight compression, memory offloading, partitioning, and re-materialization.
Axis 2 — Security & Confidentiality
Protect data and models: encryption, homomorphic operations, confidential computing, and poisoning/backdoor defenses.
Axis 3 — Volatility
Resilient scheduling, failure-aware execution, checkpointing, and straggler mitigation on heterogeneous, intermittent resources.