Syed Asad, an Innovator and AI Engineer, discusses Retrieval Augmented Generation (RAG), Semantic Vector Searches, and Vector Databases reshaping data landscapes. Topics include AI model deployment complexities, AI evaluation frameworks, challenges in client approval, and struggles with data ingestion in AI environments.
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question_answer ANECDOTE
CSV Data Challenge
Syed Asad faced a production issue with a large CSV file (133MB) for a RAG.
Various embedding models and vector databases failed to process the data efficiently.
volunteer_activism ADVICE
Alternative to Embeddings
Consider data complexity and topic repetition when choosing embedding models.
For simpler data, alternative approaches like Parquet format and Llama Index may be more efficient.
volunteer_activism ADVICE
Inference Layer Exploration
Explore and test different inference solutions for production.
Consider factors like cost, performance, and logging capabilities when choosing a solution.
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Syed Asad is an Innovator, Generative AI & Machine Learning Engineer, and a Champion for Ethical AI
MLOps podcast #233 with Syed Asad, Lead AI/ML Engineer at KiwiTech // Retrieval Augmented Generation.
A big thank you to @ for sponsoring this episode! AWS -
// Abstract
Everything and anything around RAG.
// Bio
Currently Exploring New Horizons:
Syed is diving deep into the exciting world of Semantic Vector Searches and Vector Databases. These innovative technologies are reshaping how we interact with and interpret vast data landscapes, opening new avenues for discovery and innovation.
Specializing in Retrieval Augmented Generation (RAG):
Syed's current focus also includes mastering Retrieval Augmented Generation Techniques (RAGs). This cutting-edge approach combines the power of information retrieval with generative models, setting new benchmarks in AI's capability and application.
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// Related Links
Website: https://sanketgupta.substack.com/
Our paper on this topic "Generalized User Representations for Transfer Learning": https://arxiv.org/abs/2403.00584
Sanket's blogs on Medium in the past: https://medium.com/@sanket107
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Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/
Connect with Syed on LinkedIn: https://www.linkedin.com/in/syed-asad-76815246/
Timestamps:
[00:00] Syed's preferred coffee
[00:31] Takeaways
[03:17] Please like, share, leave a review, and subscribe to our MLOps channels!
[03:37] A production issue
[07:37] CSV file handling risks
[09:42] Embedding models not suitable
[11:22] Inference layer experiments and use cases
[14:00] AWS service handling the issue
[17:35] Salad testing and insights
[22:12] OpenAI vs Customization
[24:30] Difference between Olama and VLLM
[27:16] Fine-tuning of small LLMs
[29:51] Evaluation framework
[32:04] MLOps for efficient ML
[37:12] Determining the pricing of tools
[39:35] Manage Dependency Risk
[40:27] Get in touch with Syed on LinkedIn
[41:46] ML Engineers are now all AI Engineers
[43:01] The hard framework
[43:53] Wrap up
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