AI agents are transforming business operations by automating processes, optimizing decision-making, and streamlining actions. Their effectiveness hinges on expert reasoning, enabling smarter planning and efficient execution. Agentic AI applications could benefit from the capabilities of models such as DeepSeek-R1. Built for solving problems that require advanced AI reasoning…
]]>Evaluating large language models (LLMs) and retrieval-augmented generation (RAG) systems is a complex and nuanced process, reflecting the sophisticated and multifaceted nature of these systems. Unlike traditional machine learning (ML) models, LLMs generate a wide range of diverse and often unpredictable outputs, making standard evaluation metrics insufficient. Key challenges include the…
]]>Generative AI has evolved from text-based models to multimodal models, with a recent expansion into video, opening up new potential uses across various industries. Video models can create new experiences for users or simulate scenarios for training autonomous agents at scale. They are helping revolutionize various industries including robotics, autonomous vehicles, and entertainment.
]]>For organizations adapting AI foundation models with domain-specific data, the ability to rapidly create and deploy fine-tuned models is key to efficiently delivering value with enterprise generative AI applications. NVIDIA NIM offers prebuilt, performance-optimized inference microservices for the latest AI foundation models, including seamless deployment of models customized using parameter…
]]>One challenge organizations face when customizing large language models (LLMs) is the need to run multiple experiments, which produces only one useful model. While the cost of experimentation is typically low, and the results well worth the effort, this experimentation process does involve “wasted” resources, such as compute assets spent without their product being utilized…
]]>The Llama-3.1-Nemotron 70B-Reward model helps generate high-quality training data that aligns with human preferences for finance, retail, healthcare, scientific research, telecommunications, and sovereign AI. This post was updated on August 16, 2024 to reflect the most recent Reward Bench results. Since the introduction and subsequent wide adoption of large language models (LLMs)…
]]>Large language models (LLMs) have revolutionized natural language processing (NLP) in recent years, enabling a wide range of applications such as text summarization, question answering, and natural language generation. Arctic, developed by Snowflake, is a new open LLM designed to achieve high inference performance while maintaining low cost on various NLP tasks. Arctic Arctic is…
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