Neural Search Talks — Zeta Alpha
Baking the Future of Information Retrieval Models
Apr 19, 2024
Aamir Shakir, an expert from Mixed Bread AI, shares his journey in revolutionizing AI-driven search technologies. He reveals the whimsical story behind the company’s name, emphasizing a unique baking analogy. Aamir discusses overcoming challenges like GPU shortages and the significance of diverse data in creating robust embedding models. He also highlights the potential of multilingual and multimodal capabilities for future information retrieval. Get ready for innovative insights into the future of AI search!
27:05
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Quick takeaways
- Mixed Bread AI emphasizes the significance of rigorous data collection and innovative loss functions to enhance embedding model performance.
- The company's future focus includes expanding multilingual and multimodal capabilities to address broader challenges in AI and information retrieval.
Deep dives
Challenges in Search and Retrieval
The discussion highlights the intricate challenges faced in the search and retrieval landscape, particularly in creating effective systems within the context of sensitive data, such as that used by consultants and lawyers. The founders of Mixed Bread AI recognized the difficulties involved in embedding model hosting and subsequently developed an API called Mbus to offer open-source models. They discovered a significant knowledge gap among developers who often need to transform into experts in information retrieval, a field rich in over 50 years of research. This realization motivated their efforts to simplify and improve the accessibility of these technologies to empower users in utilizing advanced search capabilities.
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