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Benchmarking Amazon Nova and GPT-4o models with FloTorch

AWS Machine Learning

Using its enterprise software, FloTorch conducted an extensive comparison between Amazon Nova models and OpenAIs GPT-4o models with the Comprehensive Retrieval Augmented Generation (CRAG) benchmark dataset. OpenAI launched GPT-4o in May 2024, and Amazon introduced Amazon Nova models at AWS re:Invent in December 2024.

Benchmark 103
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GraphStorm 0.3: Scalable, multi-task learning on graphs with user-friendly APIs

AWS Machine Learning

adds new APIs to customize GraphStorm pipelines: you now only need 12 lines of code to implement a custom node classification training loop. To help you get started with the new API, we have published two Jupyter notebook examples: one for node classification, and one for a link prediction task. Specifically, GraphStorm 0.3

APIs 115
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From RAG to fabric: Lessons learned from building real-world RAGs at GenAIIC – Part 2

AWS Machine Learning

An alternative approach to routing is to use the native tool use capability (also known as function calling) available within the Bedrock Converse API. In this scenario, each category or data source would be defined as a ‘tool’ within the API, enabling the model to select and use these tools as needed.

APIs 117
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Optimizing AI responsiveness: A practical guide to Amazon Bedrock latency-optimized inference

AWS Machine Learning

During re:Invent 2024, we launched latency-optimized inference for foundation models (FMs) in Amazon Bedrock. Consider benchmarking your user experience to find the best latency for your use case, considering that most humans cant read faster than 225 words per minute and therefore extremely fast response can hinder user experience.

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Mistral-Small-24B-Instruct-2501 is now available on SageMaker Jumpstart and Amazon Bedrock Marketplace

AWS Machine Learning

The 2501 version follows previous iterations (Mistral-Small-2409 and Mistral-Small-2402) released in 2024, incorporating improvements in instruction-following and reliability. At the time of writing this post, you can use the InvokeModel API to invoke the model. It doesnt support Converse APIs or other Amazon Bedrock tooling.

APIs 83
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A progress update on our commitment to safe, responsible generative AI

AWS Machine Learning

red teaming) In April 2024, we announced the general availability of Guardrails for Amazon Bedrock and Model Evaluation in Amazon Bedrock to make it easier to introduce safeguards, prevent harmful content, and evaluate models against key safety and accuracy criteria. In February 2024, Amazon joined the U.S.

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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.

Benchmark 126