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Key Learning from 15 Years of Net Promoter Stats

Beyond Philosophy

In their 15th annual Net Promoter Benchmark Study, he gave a great presentation of some really interesting stats on NPS. Rocks and I will be presenting more information from Satmetrix’s 15th Annual Net Promoter Study in the upcoming webinar: “ 15 Years of Tracking Net Promoter: What Have We Learned? ” Quite a lot, it turns out.

Banking 383
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Benchmark and optimize endpoint deployment in Amazon SageMaker JumpStart 

AWS Machine Learning

This post explores these relationships via a comprehensive benchmarking of LLMs available in Amazon SageMaker JumpStart, including Llama 2, Falcon, and Mistral variants. We provide theoretical principles on how accelerator specifications impact LLM benchmarking. Additionally, models are fully sharded on the supported instance.

Benchmark 115
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Emotions Drive Spending, But Do You Know Which Ones Drive the Most?

Beyond Philosophy

In 2004, I presented to an insurance company in Germany about how they should be evoking the proper emotions in their customers. Once you have the buy-in from your organization, you need to figure out what you need to change in your present experience to evoke these emotions. It was a tough audience.

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3 Tools to Measure Authentic Customer Emotions in Real-Time

Beyond Philosophy

I went to a presentation about the results of our research concerning customer satisfaction with some of our key products and services. I was taken by the fact the person presenting was presenting it as if to say, “I don’t know why I bother in presenting this to you.” I stopped her and asked her why.

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Cohere Embed multimodal embeddings model is now available on Amazon SageMaker JumpStart

AWS Machine Learning

Cohere Embed 3 makes it simple to locate specific UI mockups, visual templates, and presentation slides based on a text description. All text-to-image benchmarks are evaluated using Recall@5 ; text-to-text benchmarks are evaluated using NDCG@10. Generic text-to-image benchmark accuracy is based on Flickr and CoCo.

Benchmark 101
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2020 Call Center Metrics: 6 Key Metrics for Your Call Center Dashboard

Callminer

To get the most out of this metric, use it to inform budgeting and infrastructure-related decisions as opposed to using it for agent benchmarking purposes. By harnessing the information each of the above metrics presents you with, it is possible to consistently improve your call center’s performance over time.

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

AWS Machine Learning

To address these challenges, we present an innovative continuous self-instruct fine-tuning framework that streamlines the LLM fine-tuning process of training data generation and annotation, model training and evaluation, human feedback collection, and alignment with human preference.