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- NVIDIA details Shopify's Nemotron 3.5 Lightning post-training for Sidekick
NVIDIA published a blog post describing European retailers using open models and physical AI across commerce and fulfillment, led by Shopify's work on its Sidekick merchant assistant. According to the post, Shopify post-trained NVIDIA Nemotron 3.5 Lightning for a GraphQL subagent inside Sidekick, using the NVIDIA Megatron Bridge library for fine-tuning and NVIDIA NeMo RL for reinforcement learning, with the subagent retrieving store data for features such as Sidekick Pulse. NVIDIA says that on Shopify's internal benchmark the post-trained model surpassed a leading frontier model in accuracy while cutting serving costs by 90% and responding 7x faster, and that NVIDIA CCluster vLLM optimization delivered 4.5x faster performance and up to 12x lower inference cost across five other use cases. The post also cites Zooplus rebuilding product discovery with the Nemotron Retriever library to reach 86% search accuracy in a prototype, plus Photoroom, Omi with L'Oréal, Otto Group and Mirakl deployments.
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