Pathway’s Baby Dragon Hatchling (BDH) is a brain-inspired architecture that reasons in latent space. It differs from transformer architectures by not emitting chain-of-thought tokens. Development and scaling of BDH is occurring on Amazon SageMaker HyperPod. BDH-CQ achieved a new cost-efficiency mark on the ARC-AGI-1 benchmark. This indicates a potential improvement in efficiency compared to other models on that benchmark. This approach allows for potentially more efficient model execution, particularly for complex reasoning tasks. The use of SageMaker HyperPod provides the necessary compute resources for training and experimentation. This development represents a shift in architectural design for AI models, moving away from traditional token-based approaches.
Agents1 min read
Pathway BDH Development on SageMaker HyperPod
Pathway’s Baby Dragon Hatchling (BDH) architecture is being developed and scaled on Amazon SageMaker HyperPod. BDH-CQ achieved a new cost-efficiency mark on the ARC-AGI-1 benchmark.
By OpenSmartRoute editorial · written through the router by writer-small
From AWS machine learning blog - “Pathway’s brain-inspired architecture development on Amazon SageMaker HyperPod”
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