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DataFramed
#275 Did Gen AI Kill NLP? with Meri Nova, Technical Founder at Break into Data
Jan 16, 2025
Meri Nova, Founder of Break Into Data and an experienced AI engineer, dives into the evolution of natural language processing (NLP) and the transformative impact of generative AI. She examines when to apply traditional NLP techniques versus modern models, highlighting the balance between creativity and cost. The discussion includes the role of vector stores in handling unstructured data and the changing landscape of AI engineering. Meri also shares insights on harnessing AI for creativity and enhancing decision-making, particularly for those with ADHD.
39:04
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Quick takeaways
- The rise of generative AI presents new challenges for businesses, requiring a strategic decision between using traditional NLP techniques and advanced models based on specific use cases.
- Knowledge graphs enhance AI systems by providing structured relationships between entities, improving data retrieval efficiency and fostering relevant outputs in various applications.
Deep dives
The Evolution of Natural Language Processing and Generative AI
Natural language processing (NLP) is vital in enabling computers to understand and generate human language, thus unlocking numerous applications across industries. Common uses include chatbots for customer support and content moderation in online communities, which have been present for over a decade. With the rise of generative AI, significant advancements have emerged, allowing for the creation of large volumes of text, revolutionizing how we interact with technology. This evolution indicates a transformative period in AI where creative tasks can now be tackled, moving beyond basic classification and understanding.
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