Every technology has a lifecycle, and generative AI (GenAI) is no exception. While it continues to quickly evolve with innovations like retrieval augmented generation (RAG) and multi-agent or agentic AI, the core of generative AI large language models (LLMs) is beginning to mature. And with that maturity comes opportunities for organizations to optimize performance, increase efficiency and become more secure.
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Intel NN News
- AutoRound Meets SGLang: Enabling Quantized Model Inference with AutoRound
We are thrilled to announce an official collaboration between SGLang and AutoRound, enabling […]
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In this guide, you'll learn multiple aspects of optimizing the Search and Recommendation model […]
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Researchers at the U.S. Department of Energy’s (DOE) Argonne National Laboratory introduce AERIS, […]
- AutoRound Meets SGLang: Enabling Quantized Model Inference with AutoRound
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