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Benchmarking Amazon Nova and GPT-4o models with FloTorch

AWS Machine Learning

OpenAI launched GPT-4o in May 2024, and Amazon introduced Amazon Nova models at AWS re:Invent in December 2024. How do Amazon Nova Micro and Amazon Nova Lite perform against GPT-4o mini in these same metrics? Amazon Bedrock APIs make it straightforward to use Amazon Titan Text Embeddings V2 for embedding data.

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Your guide to generative AI and ML at AWS re:Invent 2024

AWS Machine Learning

Gain insights into training strategies, productivity metrics, and real-world use cases to empower your developers to harness the full potential of this game-changing technology. Discover how to create and manage evaluation jobs, use automatic and human reviews, and analyze critical metrics like accuracy, robustness, and toxicity.

APIs 91
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Principal Financial Group uses QnABot on AWS and Amazon Q Business to enhance workforce productivity with generative AI

AWS Machine Learning

In business for 145 years, Principal is helping approximately 64 million customers (as of Q2, 2024) plan, protect, invest, and retire, while working to support the communities where it does business and build a diverse, inclusive workforce. The platform has delivered strong results across several key metrics.

Chatbots 114
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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 114
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How Formula 1® uses generative AI to accelerate race-day issue resolution

AWS Machine Learning

During these live events, F1 IT engineers must triage critical issues across its services, such as network degradation to one of its APIs. This impacts downstream services that consume data from the API, including products such as F1 TV, which offer live and on-demand coverage of every race as well as real-time telemetry.

APIs 70
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Build your gen AI–based text-to-SQL application using RAG, powered by Amazon Bedrock (Claude 3 Sonnet and Amazon Titan for embedding)

AWS Machine Learning

Additionally, the complexity increases due to the presence of synonyms for columns and internal metrics available. I am creating a new metric and need the sales data. Firstly, LLMs dont have access to enterprise databases, and the models need to be customized to understand the specific database of an enterprise.

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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. To effectively optimize AI applications for responsiveness, we need to understand the key metrics that define latency and how they impact user experience. These metrics are shown in the following diagram.