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Pixtral-12B-2409 is now available on Amazon Bedrock Marketplace

AWS Machine Learning

Overview of Pixtral 12B Pixtral 12B, Mistrals inaugural VLM, delivers robust performance across a range of benchmarks, surpassing other open models and rivaling larger counterparts, according to Mistrals evaluation. Performance metrics and benchmarks Pixtral 12B is trained to understand both natural images and documents, achieving 52.5%

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The state of CX: Trends and predictions for 2025

3CLogic

As a result, agents can spend less time documenting interaction details and get back to helping the next customer faster. These solutions are setting new benchmarks for customer satisfaction by empowering organizations to solve more issues faster at a lower cost. Investments in EX, including AI Coaching, real-time feedback, etc.,

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LLM continuous self-instruct fine-tuning framework powered by a compound AI system on Amazon SageMaker

AWS Machine Learning

Continuous fine-tuning also enables models to integrate human feedback, address errors, and tailor to real-world applications. When you have user feedback to the model responses, you can also use reinforcement learning from human feedback (RLHF) to guide the LLMs response by rewarding the outputs that align with human preferences.

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Evaluate RAG responses with Amazon Bedrock, LlamaIndex and RAGAS

AWS Machine Learning

Optimized for search and retrieval, it streamlines querying LLMs and retrieving documents. Build sample RAG Documents are segmented into chunks and stored in an Amazon Bedrock Knowledge Bases (Steps 24). For this purpose, LangChain provides a WebBaseLoader object to load text from HTML webpages into a document format.

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Study: The Health of the Contact Center

What does it take to engage agents in this customer-centric era? Download our study of 1,000 contact center agents in the US and UK to find out what major challenges are facing contact center agents today – and what your company can do about it.

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How to Establish a Net Promoter Score Benchmark for Your Call Center

Fonolo

This approach allows you to evaluate customer feedback and information to improve your call center. The best strategy is to use a combination of data reports and benchmarking to ensure your findings reflect “the big picture” Creating a Customer Service Strategy That Drives Business Growth. 1: Diversify your NPS surveys.

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LLM-as-a-judge on Amazon Bedrock Model Evaluation

AWS Machine Learning

By using the same evaluator model across all comparisons, youll get consistent benchmarking results to help identify the optimal model for your use case. The following best practices will help you establish standardized benchmarking when comparing different foundation models. 0]}-{evaluator_model.split('.')[0]}-{datetime.now().strftime('%Y-%m-%d-%H-%M-%S')}"

Metrics 93
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The Health of the Contact Center: Are You Ready for 2019?

A survey of 1,000 contact center professionals reveals what it takes to improve agent well-being in a customer-centric era. This report is a must-read for contact center leaders preparing to engage agents and improve customer experience in 2019.