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Philips accelerates development of AI-enabled healthcare solutions with an MLOps platform built on Amazon SageMaker

AWS Machine Learning

Enable a data science team to manage a family of classic ML models for benchmarking statistics across multiple medical units. Users from several business units were trained and onboarded to the platform, and that number is expected to grow in 2024. Another important metric is the efficiency for data science users.

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Get started with Amazon Titan Text Embeddings V2: A new state-of-the-art embeddings model on Amazon Bedrock

AWS Machine Learning

We published a follow-up post on January 31, 2024, and provided code examples using AWS SDKs and LangChain, showcasing a Streamlit semantic search app. A common way to select an embedding model (or any model) is to look at public benchmarks; an accepted benchmark for measuring embedding quality is the MTEB leaderboard.

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Mixtral 8x22B is now available in Amazon SageMaker JumpStart

AWS Machine Learning

What is Mixtral 8x22B Mixtral 8x22B is Mistral AI’s latest open-weights model and sets a new standard for performance and efficiency of available foundation models , as measured by Mistral AI across standard industry benchmarks. making the model available for exploring, testing, and deploying. Therefore, she sold the car for $18,248.33.

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The executive’s guide to generative AI for sustainability

AWS Machine Learning

Figure 1: Examples of generative AI for sustainability use cases across the value chain According to KPMG’s 2024 ESG Organization Survey , investment in ESG capabilities is another top priority for executives as organizations face increasing regulatory pressure to disclose information about ESG impacts, risks, and opportunities.

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Boost inference performance for Mixtral and Llama 2 models with new Amazon SageMaker containers

AWS Machine Learning

In January 2024, Amazon SageMaker launched a new version (0.26.0) In this post, we explore the latest features introduced in this release, examine performance benchmarks, and provide a detailed guide on deploying new LLMs with LMI DLCs at high performance. of Large Model Inference (LMI) Deep Learning Containers (DLCs).

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Enable data sharing through federated learning: A policy approach for chief digital officers

AWS Machine Learning

Furthermore, model hosting on Amazon SageMaker JumpStart can help by exposing the endpoint API without sharing model weights. It also takes away potential high-level compute challenges with on-premises hardware with Amazon Elastic Compute Cloud (Amazon EC2) resources.