For training track, develop the Volcano Ark training platform, enabling both internal and external users to perform serverless post-training (e.g., Supervised Fine-Tuning (SFT) and Reinforcement Learning (RL)) on the Ark platform.
Design elastic training solutions for complex multi-tenant workloads, supporting mixed-tenant training across multiple data centers and heterogeneous hardware while optimizing training throughput, resource utilization, and system stability.
Build next-generation reinforcement learning infrastructure to improve training efficiency, while designing intuitive and developer-friendly APIs for RL training workflows.
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Exploring Cutting-Edge NLP Technologies: From basic tasks like word segmentation and Named Entity Recognition (NER) to advanced business functions like text and multimodal pre-training, query analysis, and fundamental relevance modeling, we apply deep learning models throughout the pipeline where every detail presents a challenge.
Cross-Modal Matching Technologies: Applying deep learning techniques that combine Computer Vision (CV) and Natural Language Processing (NLP) in search, we aim to achieve powerful semantic understanding and retrieval capabilities for multimodal video search.
Large-Scale Streaming Machine Learning Technologies: Utilising large-scale machine learning to address recommendation challenges in search, making the search more personalized and intuitive in understanding user needs.
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