Applied NLP in the Age of Generative AI

2024-09-20 · Source: Explosion · Developer tools and consulting for AI, Machine Learning and NLP - Explosion.ai · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering · Depth: Intermediate, quick

Summary

The talk by Ines focuses on critical lessons derived from practical experience in solving real-world information extraction challenges within industry settings. It introduces a novel approach and mindset specifically tailored for developing robust and modular Natural Language Processing (NLP) pipelines. This new methodology is presented within the context of the evolving landscape of Generative AI, aiming to equip professionals with strategies for effective NLP system design.

Key takeaway

For NLP Engineers or AI Architects designing systems in the Generative AI era, you should prioritize adopting a new approach that emphasizes robust and modular pipeline design. This talk offers valuable industry lessons from information extraction, providing a critical mindset shift to build more resilient and adaptable NLP solutions. Consider how these insights can refine your current development practices.

Key insights

Ines shares lessons and a new approach for robust, modular NLP pipelines in the Generative AI era.

Principles

• Lessons from real-world information extraction
• Design robust, modular NLP pipelines

In practice

• Solve real-world information extraction problems
• Apply Generative AI in NLP pipelines

Topics

• Applied NLP
• Generative AI
• Information Extraction
• NLP Pipelines
• Modular Design

Best for: NLP Engineer, AI Engineer, AI Architect

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Editorial summary, takeaway, and curation by AIssential. Original article published by Explosion · Developer tools and consulting for AI, Machine Learning and NLP - Explosion.ai.