Docker CTO Explains How Docker Can Support AI Efforts
In this episode of The New Stack Makers, Docker CTO Justin Cormack explains how Docker is making AI models easier to deploy locally.
The New Stack Podcast · Docker, The New Stack, Justin Cormack, Loraine Lawson
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Show Notes
Docker CTO Justin Cormack reveals that Docker has been a go-to tool for data scientists in AI and machine learning for years, primarily in specialized areas like image processing and prediction models. However, the release of OpenAI's ChatGPT last year sparked a significant surge in Docker's popularity within the AI community.
The focus shifted to large language models (LLMs), with a growing interest in the retrieval-augmented generation (RAG) stack. Docker's collaboration with Ollama enables developers to run Llama 2 and Code Llama locally, simplifying the process of starting and experimenting with AI applications. Additionally, partnerships with Neo4j and LangChain allow for enhanced support in storing and retrieving data for LLMs.
Cormack emphasizes the simplicity of getting started locally, addressing challenges related to GPU shortages in the cloud. Docker's efforts also include building an AI solution using its data, aiming to assist users in Dockerizing applications through an interactive notebook in Visual Studio Code. This tool leverages LLMs to analyze applications, suggest improvements, and generate Docker files tailored to specific languages and applications.
Docker's integration with AI technologies demonstrates a commitment to making AI and Docker more accessible and user-friendly.
Learn more from The New Stack about AI and Docker:
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