One of the hardest parts of applied NLP has always been breaking down complex business problems into machine learning components. It's so hard because it requires domain expertise and reasoning about the specific use case, and it's the one thing technology couldn't fix. But what if we could take some of the learnings from AI-powered coding assistants and apply them to solving real-world NLP problems? In this talk, I'll show you these new agentic development workflows, what they mean for developer tools and why code and the open-source ecosystem are more important than ever.
Read about and join the waitlist for Ellf, our new platform and virtual assistant for applied NLP and agentic NLP development.
https://explosion.ai/blog/against-llm-maximalism
A lot of people are building truly new things with LLMs, like wild interactive fiction experiences that weren’t possible before. But if you’re working on the same sort of NLP problems that businesses have been trying to solve for a long time, what’s the best way to use them?
https://explosion.ai/blog/atomic-nlp
An applied NLP methodology inspired by Atomic Design: building reliable language understanding systems out of small, composable components instead of one big model and a prompt.
https://explosion.ai/blog/human-in-the-loop-distillation
This blog post presents practical solutions for using the latest state-of-the-art models in real-world applications and distilling their knowledge into smaller and faster components that you can run and maintain in-house.
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codingconduct
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kneath
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