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Testing times: testingRTC is the smart, synchronized, real-world scenario WebRTC testing solution for the times we live in.

Spearline

And testingRTC offers multiple ways to export these metrics, from direct collection from webhooks, to downloading results in CSV format using the REST API. Flip the script With testingRTC, you only need to write scripts once, you can then run them multiple times and scale them up or down as you see fit. Happy days!

Scripts 98
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Accelerate Amazon SageMaker inference with C6i Intel-based Amazon EC2 instances

AWS Machine Learning

Refer to the appendix for instance details and benchmark data. Use the supplied Python scripts for quantization. Run the provided Python test scripts to invoke the SageMaker endpoint for both INT8 and FP32 versions. Quantizing the model in PyTorch is possible with a few APIs from Intel PyTorch extensions.

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Amazon Comprehend announces lower annotation limits for custom entity recognition

AWS Machine Learning

For example, you can immediately start detecting entities such as people, places, commercial items, dates, and quantities via the Amazon Comprehend console , AWS Command Line Interface , or Amazon Comprehend APIs. In this post, we walk you through the benchmarking process and the results we obtained while working on subsampled datasets.

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How to Successfully Start A New Communication Channel In A Call Center?

NobelBiz

Key Points CCaaS is paramount to successfully add a new communication channel You must consider the tone, scripts and pace of new channels Your Call Center must track the right KPIs for every new channel How to add a new communication channel in a call center? Integration with your current software (CRM, API etc.)

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Super-Agents Are Real (Blog #4)

Enghouse Interactive

As noted in the 2019 Dimension Data Customer Experience (CX) Benchmarking report: 88% of contact center decision-makers expect self-service volumes to increase over the next 12 months. These interactions will become longer – so traditional productivity measurements and benchmarks will no longer be relevant and will have to be redefined.

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Build a robust text-based toxicity predictor

AWS Machine Learning

The Trainer class provides an API for feature-complete training in PyTorch. We observe that the adversarial trained model has a lower ASR, with an 62.21% decrease using the original model ASR as the benchmark. For more information about this up-and-coming topic, we encourage you to explore and test our script on your own.

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FMOps/LLMOps: Operationalize generative AI and differences with MLOps

AWS Machine Learning

In this scenario, the generative AI application, designed by the consumer, must interact with the fine-tuner backend via APIs to deliver this functionality to the end-users. Some models may be trained on diverse text datasets like internet data, coding scripts, instructions, or human feedback. 15K available FM reference Step 1.