MLA 017 AWS Local Development

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The deployment of machine learning models for real-world use involves a sequence of cloud services and architectural choices, where machine learning expertise must be complemented by DevOps and architecture skills, often requiring collaboration with professionals. Key co ...

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Machine learning pipeline orchestration tools, such as SageMaker and Kubeflow, streamline the end-to-end process of data ingestion, model training, deployment, and monitoring, with Kubeflow providing an open-source, cross-cloud platform built atop Kubernetes. Organizatio ...

SummaryIn this episode of the Data Engineering Podcast Prashanth Rao, an AI engineer at KuzuDB, talks about their embeddable graph database. Prashanth explains how KuzuDB addresses performance shortcomings in existing solutions through columnar storage and novel join algorithms. ...  Afficher plus

Episode 13: What impact will AI-generated content have on the entertainment industry? Matt Wolfe ( https://x.com/mreflow) and Nathan Lands ( https://x.com/NathanLands) dive into this topic, envisioning a future where AI generates interactive movies and complex gaming worlds with in ...  Afficher plus

SummaryIn this episode of the AI Engineering Podcast Mark Brooker, VP and Distinguished Engineer at AWS, talks about how agentic workflows are transforming database usage and infrastructure design. He discusses the evolving role of data in AI systems, from traditional models to m ...  Afficher plus

Our guest today is Loubna Ben Allal, Machine Learning Engineer at Hugging Face 🤗 . In our conversation, Loubna first explains how she built two impressive code generation models: StarCoder and StarCoder2. We dig into the importance of data when training large models and what can ...  Afficher plus