Research adds ten commercial options for training an LLM from scratch
New procurement research compares ten commercial training offerings and proposes AWS SageMaker AI as the general-purpose managed-training candidate. The shortlist reflects proposed project fit, not measured performance.
Proposed training candidates
The research proposes comparing AWS SageMaker AI with Together GPU Clusters and evaluating Databricks for an integrated workflow. It identifies NVIDIA DGX Cloud Lepton with a current NeMo stack as the strongest architectural fit, subject to validation.
Training from new weights
The research defines training from scratch as initializing new model weights and training them on an admitted corpus. It distinguishes this process from continued pretraining, fine-tuning and reinforcement learning that retain an existing checkpoint's ancestry.
Procurement checks
The comparison distinguishes managed training platforms, managed clusters and contracted training services by supplier scope and customer responsibilities. It proposes working pilots before substantial commitments and checks for capacity, complete costs, preview conditions and checkpoint export.
Documentation index
The README now lists the research alongside the existing planning documents. Its description covers new initialization, operational responsibility, pricing, artifact control and proposed SIP content rewards integration.
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README.md | modified | +1 −0 |
docs/COMMERCIAL_LLM_PRETRAINING_PLATFORMS_RESEARCH.md | added | +191 −0 |