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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. How do Amazon Nova Micro and Amazon Nova Lite perform against GPT-4o mini in these same metrics? Each provisioned node was r7g.4xlarge,

Benchmark 115
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20 Call Center Pros Share the Most Undervalued Call Center Metrics and How To Better Leverage Them

Callminer

From essentials like average handle time to broader metrics such as call center service levels , there are dozens of metrics that call center leaders and QA teams must stay on top of, and they all provide visibility into some aspect of performance. Kaye Chapman @kayejchapman. First contact resolution (FCR) measures might be…”.

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Key Benchmarks Should You Target In 2025 for your Contact Center

NobelBiz

With the advancement of the contact center industry, benchmarks continue to shift and challenge businesses to meet higher customer expectations while maintaining efficiency. In 2025, achieving the right benchmarks means understanding the metrics that matter, tracking them effectively, and striving for continuous improvement.

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

AWS Machine Learning

This approach allows organizations to assess their AI models effectiveness using pre-defined metrics, making sure that the technology aligns with their specific needs and objectives. Prerequisites To use the LLM-as-a-judge model evaluation, make sure that you have satisfied the following requirements: An active AWS account.

Metrics 111
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LLM continuous self-instruct fine-tuning framework powered by a compound AI system on Amazon SageMaker

AWS Machine Learning

Besides the efficiency in system design, the compound AI system also enables you to optimize complex generative AI systems, using a comprehensive evaluation module based on multiple metrics, benchmarking data, and even judgements from other LLMs. The DSPy lifecycle is presented in the following diagram in seven steps.

Benchmark 104
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10 Key Metrics and KPI’s for Contact Centre Performance

Call Design

Understanding how to make a profit on the double bottom line (DBL) involves employing a broad range of KPIs and key metrics to ensure a contact centre meets every need that a business may have in supporting their customers. of the 380 contact centre professionals they asked thought customer satisfaction was one of the most important metrics.

Metrics 148
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Anthropic Claude 3.5 Sonnet ranks number 1 for business and finance in S&P AI Benchmarks by Kensho

AWS Machine Learning

Sonnet currently ranks at the top of S&P AI Benchmarks by Kensho , which assesses large language models (LLMs) for finance and business. For example, there could be leakage of benchmark datasets’ questions and answers into training data. Anthropic Claude 3.5 Kensho is the AI Innovation Hub for S&P Global. Anthropic Claude 3.5

Finance 126