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Two Indispensable Tools for Measuring the Quality of AI Systems

ODSC - Open Data Science

Measuring the quality of free text responses is not trivial compared to traditional ML models and requires semantic comparisons to approach parity with human evaluation. He joined Humana in late 2015 and spent his first few years focused on solving business problems by applying data science with a clinical focus.

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Evaluating Long-Context Question & Answer Systems

Eugene Yan

In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 6162–76. RefChecker: Reference-Based Fine-Grained Hallucination Checker and Benchmark for Large Language Models.” © Eugene Yan 2015 - 2025 • Feedback • RSS [link] Feng, Song, Siva Sankalp Patel, Hui Wan, and Sachindra Joshi.

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Tensor Processing Units (TPUs)

Dataconomy

These specialized processing units allow data scientists and AI practitioners to train complex models faster and at a larger scale than traditional hardware, propelling advancements in technologies like natural language processing, image recognition, and beyond. What are Tensor Processing Units (TPUs)?

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Build a scalable AI assistant to help refugees using AWS

AWS Machine Learning Blog

Amazon Simple Storage Service (Amazon S3) provides secure storage for conversation logs and supporting documents, and Amazon Bedrock powers the core natural language processing capabilities. In the process of implementation, we discovered that Anthropics Claude 3.5 Taras is an AWS Certified ML Engineer Associate.

AWS 100
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Machine Learning and Language (ML²) at CDS: Moving NLP Forward

NYU Center for Data Science

It’s a pivotal time in Natural Language Processing (NLP) research, marked by the emergence of large language models (LLMs) that are reshaping what it means to work with human language technologies. A Vision for ML² In the beginning, ML² was simply the hub for NLP research at NYU.

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Zero-shot text classification with Amazon SageMaker JumpStart

AWS Machine Learning Blog

Natural language processing (NLP) is the field in machine learning (ML) concerned with giving computers the ability to understand text and spoken words in the same way as human beings can. SageMaker JumpStart solution templates are one-click, end-to-end solutions for many common ML use cases.

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Top 6 Kubernetes use cases

IBM Journey to AI blog

Kubernetes’s declarative, API -driven infrastructure has helped free up DevOps and other teams from manually driven processes so they can work more independently and efficiently to achieve their goals. And Kubernetes can scale ML workloads up or down to meet user demands, adjust resource usage and control costs.