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Introducing DSGym, a holisti evaluation and training framework for LLM-based data science agents. Features 90+ bioinformatics tasks, 92 Kaggle competitions, and synthetic trajectory generation.
Learn how to reduce inference latency without massive cost using proven inference optimization tactics, improving throughput, GPU utilization, and cost efficiency while balancing throughput vs. latency tradeoffs.
Together AI teamed with Cursor to build the real-time inference stack that keeps in-editor agents fast and reliable. They productionized NVIDIA Blackwell (B200/GB200), tuning ARM hosts, kernels, and FP4/TensorRT quantization for low...
Learn how foundation models are trained at scale using multi-node GPU clusters, including distributed training techniques, infrastructure requirements, and practical steps to scale training efficiently.
Learn how to choose the right open-source model for production by evaluating model quality, benchmarking performance, and deploying open models that balance cost, speed, and accuracy.
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