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Introducing Fast Model Loader in SageMaker Inference: Accelerate autoscaling for your Large Language Models (LLMs) – Part 2

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In Part 1 of this series, we introduced Amazon SageMaker Fast Model Loader , a new capability in Amazon SageMaker that significantly reduces the time required to deploy and scale large language models (LLMs) for inference. 70B model with the model name meta-textgeneration-llama-3-1-70b in Amazon SageMaker JumpStart.

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Transforming real-time monitoring with AI-enhanced digital twins

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A recent McKinsey report found that 75% of large enterprises are investing in digital twins to scale their AI solutions. Enhancing digital twins with generative AI reshapes how real-time monitoring interprets massive volumes of live data, enabling the reliable and immediate detection of anomalies that impact operations.

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LLMs No Longer Require Powerful Servers: Researchers from MIT, KAUST, ISTA, and Yandex Introduce a New AI Approach to Rapidly Compress Large Language Models without a Significant Loss of Quality

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HIGGS the innovative method for compressing large language models was developed in collaboration with teams at Yandex Research, MIT, KAUST and ISTA. Combined, these methods can reduce model size by up to 8 times while maintaining 95% response quality.

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Ordnance Survey: Navigating the role of AI and ethical considerations in geospatial technology

AI News

As we approach a new year filled with potential, the landscape of technology, particularly artificial intelligence (AI) and machine learning (ML), is on the brink of significant transformation. The Ethical Frontier The rapid evolution of AI brings with it an urgent need for ethical considerations.

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SepLLM: A Practical AI Approach to Efficient Sparse Attention in Large Language Models

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Large Language Models (LLMs) have shown remarkable capabilities across diverse natural language processing tasks, from generating text to contextual reasoning. Dont Forget to join our 60k+ ML SubReddit. However, their efficiency is often hampered by the quadratic complexity of the self-attention mechanism.

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Mini-InternVL: A Series of Multimodal Large Language Models (MLLMs) 1B to 4B, Achieving 90% of the Performance with Only 5% of the Parameters

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Multimodal large language models (MLLMs) rapidly evolve in artificial intelligence, integrating vision and language processing to enhance comprehension and interaction across diverse data types. Check out the Paper and Model Card on Hugging Face. Don’t Forget to join our 55k+ ML SubReddit.

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Fin-R1: A Specialized Large Language Model for Financial Reasoning and Decision-Making

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In conclusion, Fin-R1 is a large financial reasoning language model designed to tackle key challenges in financial AI, including fragmented data, inconsistent reasoning logic, and limited business generalization. Check out the Paper and Model on Hugging Face.