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Unlocking value: Top digital transformation trends

IBM Journey to AI blog

As such, organizations are increasingly interested in seeing how they can apply the whole suite of artificial intelligence (AI) and machine learning (ML) technologies to improve their business processes. For example, applied ML will help organizations that depend on the supply chain engage in better decision making, in real time.

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Accenture creates a Knowledge Assist solution using generative AI services on AWS

AWS Machine Learning Blog

As it fields more queries, the system continuously improves its language processing through machine learning (ML) algorithms. Shuyu Yang is Generative AI and Large Language Model Delivery Lead and also leads CoE (Center of Excellence) Accenture AI (AWS DevOps professional) teams.

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How Dialog Axiata used Amazon SageMaker to scale ML models in production with AI Factory and reduced customer churn within 3 months

AWS Machine Learning Blog

They focused on improving customer service using data with artificial intelligence (AI) and ML and saw positive results, with their Group AI Maturity increasing from 50% to 80%, according to the TM Forum’s AI Maturity Index. Amazon SageMaker Pipelines – Amazon SageMaker Pipelines is a CI/CD service for ML.

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Learnings From Building the ML Platform at Mailchimp

The MLOps Blog

This article was originally an episode of the ML Platform Podcast , a show where Piotr Niedźwiedź and Aurimas Griciūnas, together with ML platform professionals, discuss design choices, best practices, example tool stacks, and real-world learnings from some of the best ML platform professionals. How do I develop my body of work?

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Automate chatbot for document and data retrieval using Agents and Knowledge Bases for Amazon Bedrock

AWS Machine Learning Blog

Then the agent will gather information through these three steps and integrate them into a final answer: “The AWS Inferentia and Trainium instances are well-suited for machine learning model inference workloads. Praveen Kumar Jeyarajan is a Principal DevOps Consultant at AWS, supporting Enterprise customers and their journey to the cloud.

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MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

For example, if you use AWS, you may prefer Amazon SageMaker as an MLOps platform that integrates with other AWS services. Knowledge and skills in the organization Evaluate the level of expertise and experience of your ML team and choose a tool that matches their skill set and learning curve. and Pandas or Apache Spark DataFrames.

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Google improves upon NIMA(Neural Image Assessment) through MUSIQ

Bugra Akyildiz

Microsoft introduces a new unit AIOps detailing in the following post : Cloud Intelligence/AIOps (“AIOps” for brevity) aims to innovate AI/ML technologies to help design, build, and operate complex cloud platforms and services at scale—effectively and efficiently.

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