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Super Data Science: ML & AI Podcast with Jon Krohn
847: AI Engineering 101, with Ed Donner
Dec 24, 2024
Ed Donner, Co-founder and CTO of Nebula.io, shares his insights from a career that spanned JPMorgan Chase to AI entrepreneurship. He delves into the role of an AI engineer and the exciting job opportunities in the field. Ed explains how to choose a large language model effectively, introduces key AI terms like RAG and agentic AI, and discusses the value of blends of real and synthetic data for testing. They even engage in a competitive game to pit LLMs against each other, showcasing innovative methods in AI evaluation.
01:12:14
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Quick takeaways
- AI engineers are in high demand as their role combines data science, software engineering, and machine learning to implement AI solutions.
- Choosing a large language model often starts with closed-source options for prototyping before transitioning to open-source models based on specific needs.
Deep dives
The Role of AI Engineer in Today's Workforce
AI engineers, sometimes referred to as LLM engineers, are in high demand, rivaling the number of job openings for data scientists. This new role is a hybrid between data science, software engineering, and machine learning engineering, requiring professionals to understand various aspects of AI. With approximately 4,000 job openings available in the U.S., the growth in this area reflects the increasing reliance on machine learning and AI technologies across industries. Organizations seek individuals who possess the ability to design and implement AI solutions effectively.
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Listen to the best highlights from the podcasts you love and dive into the full episode