Agentic Conversations (formally mlops.community)
Demetrios
Episodes
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We Can All Be AI Engineers and We Can Do It with Open Source Models // Luke Marsden // #273
Anyone can become an AI engineer by leveraging open-source models and embracing modern tools.
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Exploring AI Agents: Voice, Visuals, and Versatility // Panel // Agents in Production
AI agents are evolving towards being multi-modal, incorporating voice, text, and visual interfaces to enhance user experiences.
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The Impact of UX Research in the AI Space // Lauren Kaplan // #272
UX research is essential for aligning user needs with product goals, allowing for more user-friendly AI solutions.
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EU AI Act - Navigating New Legislation // Petar Tsankov // MLOps Podcast #271
Understanding the EU AI Regulation Act is essential for companies operating in the AI space within Europe.
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Boosting LLM/RAG Workflows & Scheduling w/ Composable Memory and Checkpointing // Bernie Wu // #270
Limited memory capacity constrains the performance of AI workloads, particularly in LLM and RAG applications.
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How to Systematically Test and Evaluate Your LLMs Apps // Gideon Mendels // #269
Developers must integrate ML and software engineering practices to effectively build and evaluate LLM applications.
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Exploring the Impact of Agentic Workflows // Raj Rikhy // #268
Not summarized yet
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The Only Constant is (Data) Change // Panel // DE4AI
Not summarized yet
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The AI Dream Team: Strategies for ML Recruitment and Growth // Jelmer Borst and Daniela Solis // #267
Not summarized yet
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Making Your Company LLM-native // Francisco Ingham // #266
Being LLM-native requires a strategic approach to leveraging LLMs across all facets of a business, affecting both customer experiences and internal operations.
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Unpacking 3 Types of Feature Stores // Simba Khadder // #265
Not summarized yet
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Reinvent Yourself and Be Curious // Stefano Bosisio // #264
Not summarized yet
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Global Feature Store // Gottam Sai Bharath & Cole Bailey // #263
Not summarized yet
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RAG Quality Starts with Data Quality // Adam Kamor // #262
Data quality is fundamental for successful Retrieval-Augmented Generation systems.
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Who's MLOps for Anyway? // Jonathan Rioux // #261
Not summarized yet
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Alignment is Real // Shiva Bhattacharjee // #260
Not summarized yet
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Ax a New Way to Build Complex Workflows with LLMs // Vikram Rangnekar // #259
Not summarized yet
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Building in Production Human-centred GenAI Solutions // Mohamed Abusaid & Mara Pometti// #177
Not summarized yet
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Visualize - Bringing Structure to Unstructured Data // Markus Stoll // #258
Not summarized yet
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AI Testing Highlights // Special MLOps Podcast Episode
Not summarized yet
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