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Benchmarking Amazon Nova and GPT-4o models with FloTorch

AWS Machine Learning

Five domains in CRAG dataset are Finance, Sports, Music, Movie, and Open (miscellaneous). simple Finance Did meta have any mergers or acquisitions in 2022? Amazon Bedrock APIs make it straightforward to use Amazon Titan Text Embeddings V2 for embedding data. simple_w_condition Open Can i make cookies in an air fryer?

Benchmark 106
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Unlocking insights and enhancing customer service: Intact’s transformative AI journey with AWS

AWS Machine Learning

The goal was to refine customer service scripts, provide coaching opportunities for agents, and improve call handling processes. Frontend and API The CQ application offers a robust search interface specially crafted for call quality agents, equipping them with powerful auditing capabilities for call analysis.

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Enterprise-grade natural language to SQL generation using LLMs: Balancing accuracy, latency, and scale

AWS Machine Learning

Enterprise data by its very nature spans diverse data domains, such as security, finance, product, and HR. Additionally, if temporary tables or views are used for the data domain, a SQL script is required that, when executed, creates the desired temporary data structures needs to be defined. A domain-specific user prompt.

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Amazon SageMaker model parallel library now accelerates PyTorch FSDP workloads by up to 20%

AWS Machine Learning

Customers are now pre-training and fine-tuning LLMs ranging from 1 billion to over 175 billion parameters to optimize model performance for applications across industries, from healthcare to finance and marketing. For more information on how to enable SMP with your existing PyTorch FSDP training scripts, refer to Get started with SMP.

Scripts 121
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Few-shot prompt engineering and fine-tuning for LLMs in Amazon Bedrock

AWS Machine Learning

Traditionally, earnings call scripts have followed similar templates, making it a repeatable task to generate them from scratch each time. On the other hand, generative artificial intelligence (AI) models can learn these templates and produce coherent scripts when fed with quarterly financial data.

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CBRE and AWS perform natural language queries of structured data using Amazon Bedrock

AWS Machine Learning

Services range from financing and investment to property management. AWS Prototyping successfully delivered a scalable prototype, which solved CBRE’s business problem with a high accuracy rate (over 95%) and supported reuse of embeddings for similar NLQs, and an API gateway for integration into CBRE’s dashboards.

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Configure and use defaults for Amazon SageMaker resources with the SageMaker Python SDK

AWS Machine Learning

Enterprise customers in tightly controlled industries such as healthcare and finance set up security guardrails to ensure their data is encrypted and traffic doesn’t traverse the internet. Additionally, each API call can have its own configurations. Then it copies the file into the default location for Studio notebooks.

APIs 105