🤔 Looking to improve your Text2SQL performance?
In this episode, join Angelina and Mehdi, for a discussion about a real world industry use case of RAG with Text2SQL systems.
Who's Angelina: VP of AI and data, Co-founder of Transform AI Studio, two-time fast.ai fellows under Jeremy Howard, published author. https://www.linkedin.com/in/MeetAngelina/
Who's Mehdi: Professor of Computer Science, Co-founder and Chief AI Engineer at Transform AI Studio, NSF fellow, published author. https://www.linkedin.com/in/mehdiallahyari/
What You'll Learn:
🔎 Explain what QueryGPT is and why Uber developed it
🚀 Highlight the challenges Uber faced with data queries
🛠 Walk through of the evolution of QueryGPT's architecture (20 iterations!)
🎯Walk away with key learnings and implications for other companies (build vs. buy)
✏️ In This Episode:
00:00 Intro
03:08 Why QueryGPT?
03:58 Initial design and architecture
06:48 Key challenges
07:36 Latest architecture
08:26 AI Agents used in the system
13:23 Continuous evaluation
14:25 Key learnings from QueryGPT
15:35 Fine-tuning
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🧰 Our video editing tool is this one!: https://get.descript.com/nf5cum9nj1m8
🖼️ Blogpost for today: https://www.uber.com/en-IN/blog/query-gpt/?uclick_id=6cfc9a34-aa3e-4140-9e8e-34e867b80b2b
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📚 If you'd like to learn more about RAG systems, check out our book on the RAG system: https://angelinamagr.gumroad.com/
🕴️ Our consulting firm: We help companies that don't want to miss the boat of the current wave of AI advancement by integrating these solutions into their business operations and products. https://www.transformaistudio.com/
Stay tuned for more content! 🎥 Thanks you for watching! 🙌