Author: AI Generated Robotic Content

Sequential A/B Testing Keeps the World Streaming Netflix Part 2: Counting Processes Michael Lindon, Chris Sanden, Vache Shirikian, Yanjun Liu, Minal Mishra, Martin Tingley Have you ever encountered a bug while streaming Netflix? Did your title stop unexpectedly, or not start at all? In the first installment of this blog series on sequential testing, we described …

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Posted by Mark Matthews, Senior Software Engineer, and Dmitry Lagun, Research Scientist, Google Research A person’s prior experience and understanding of the world generally enables them to easily infer what an object looks like in whole, even if only looking at a few 2D pictures of it. Yet the capacity for a computer to reconstruct …

Read more “MELON: Reconstructing 3D objects from images with unknown poses”

NVIDIA NIM microservices now integrate with Amazon SageMaker, allowing you to deploy industry-leading large language models (LLMs) and optimize model performance and cost. You can deploy state-of-the-art LLMs in minutes instead of days using technologies such as NVIDIA TensorRT, NVIDIA TensorRT-LLM, and NVIDIA Triton Inference Server on NVIDIA accelerated instances hosted by SageMaker. NIM, part …

Read more “Optimize price-performance of LLM inference on NVIDIA GPUs using the Amazon SageMaker integration with NVIDIA NIM Microservices”

Background Ever since generative AI gained prominence in the AI field, organizations ranging from startups to large enterprises have moved to harness its power by making it an integral part of their applications, solutions, and platforms. While the true potential of generative AI lies in creating new content based on learning from existing content, it …

Read more “Accelerate your generative AI journey with NVIDIA NeMo framework on GKE”