Pipeline Conversations
MLOps and LLMOps, from the trenches
Displaying items 1-10 of 19 in total of Pipeline Conversations with the tag "ai".
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Production LLM Security: Real-world Strategies from Industry Leaders 🔐
January 15th, 2025 | Season 3 | 51 mins 35 secs
ai, genai, llmops, llms, mlops, security
Learn how leading companies like Dropbox, NVIDIA, and Slack tackle LLM security in production.
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Optimizing LLM Performance and Cost for LLMs in Production
January 13th, 2025 | Season 3 | 33 mins 49 secs
ai, cost, genai, llmops, llms, mlops, optimization, performance
A deep dive into the world of LLM optimization and cost management - a critical challenge facing AI teams today.
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The Evaluation Playbook: Making LLMs Production-Ready 🧪📈
December 15th, 2024 | Season 3 | 32 mins 43 secs
ai, evaluation, genai, llmops, llms, mlops
A comprehensive exploration of real-world lessons in LLM evaluation and quality assurance, examining how industry leaders tackle the challenges of assessing language models in production.
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Prompt Engineering & Management in Production: Practical Lessons from the LLMOps Database
December 11th, 2024 | Season 3 | 29 mins 34 secs
ai, genai, llmops, llms, mlops, prompt-engineering, prompts
Prompt engineering is the art and science of crafting instructions that unlock the potential of large language models (LLMs). It's a critical skill for anyone working with LLMs, whether you're building cutting-edge applications or conducting fundamental research. But what does effective prompt engineering look like in practice, and how can we systematically improve our prompts over time?
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LLM Agents in Production: Architectures, Challenges, and Best Practices
December 9th, 2024 | Season 3 | 32 mins 37 secs
agents, ai, genai, llmops, llms, mlops
An in-depth exploration of LLM agents in production environments, covering key architectures, practical challenges, and best practices.
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Building Advanced Search, Retrieval, and Recommendation Systems with LLMs
December 6th, 2024 | Season 3 | 13 mins 8 secs
ai, embeddings, genai, llmops, llms, mlops, rag, recommendation, search
Discover how embeddings power modern search and recommendation systems with LLMs.
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Building LLM Applications that Know What They're Talking About 🔓🧠
December 3rd, 2024 | Season 3 | 21 mins 23 secs
ai, genai, llmops, llms, mlops, rag
A conversation about the RAG entries in the ZenML LLMOps database
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ML at the British Library with Daniel van Strien
November 10th, 2022 | Season 2 | 57 mins 28 secs
ai, archives, computer-vision, data-science, libraries, machine-learning
This week I spoke with Daniel van Strien, a digital curator working at the British Library. Daniel has worked on a number of projects at the intersection of archives, libraries and machine learning and I was really happy to have the chance to get to unpack some of the ways he's finding to apply these techniques and tools.
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Questioning MLOps with Lak Lakshmanan
October 27th, 2022 | Season 2 | 53 mins 2 secs
ai, artificial-intelligence, data-science, infrastructure, machine-learning, mlops, scale
This week I spoke with Lak Lakhshmanan, who worked for years at Google on ML and AI projects and products at a senior level and he also brings years of experience working on meteorology and other scientific projects previously.
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The Full Stack with Charles Frye
October 12th, 2022 | Season 2 | 57 mins 5 secs
ai, artificial-intelligence, data-science, deep-learning, education, machine-learning, mlops
This week I spoke with Charles Frye. Not only has Charles volunteered to be a judge on our Month of MLOps competition happening right now, he's part of the core team working on the Full Stack Deep Learning course.