Preeti
The AI Engineer World’s Fair in San Francisco brought together AI startups, industry leaders, and engineers to discuss the current state and future of AI Engineering. The term “AI Engineer” emerged to describe engineers focused on creating AI-powered applications. The journey for AI Engineers started with OpenAI’s APIs and has evolved to more complex projects incorporating agentic workflows and RAG pipelines.
Challenges in deploying AI applications to production were discussed at the fair, highlighting the need for reliable outcomes. The scarcity of transformative AI products in production led to a critique that AI is more hype than substance. The shift towards quality and reliability in AI applications was emphasized, with a growing focus on observability, testing, and evaluation of AI systems.
The prediction is for a dramatic increase in the quality and reliability of AI applications in the coming year, with a focus on LLM ops and evals. The AI engineering community is shifting towards more rigorous evaluations and testing methods to improve outcomes. Startups are showcasing tools to facilitate evaluations and visualize AI chains and flows, empowering engineers to experiment more effectively.
Looking ahead, the emphasis on quality and reliability is expected to lead to truly innovative AI solutions that excel in performance. The shift from functionality to robust performance will bring about the first wave of useful production-grade agentic products. The future of AI engineering looks promising as the focus shifts towards delivering on the promises of AI with substance over hype.
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Source link: https://medium.com/@joe_30979/the-evolution-of-ai-engineering-insights-from-the-worlds-fair-0f1d9b2de204?source=rss——large_language_models-5
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