Open-Source AI with Vinod Valloppillil and Bob van Luijt - Weaviate Podcast #86!
Jan 23, 2024
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Vinod Valloppillil and Bob van Luijt discuss open-source AI, the business of AI models, the potential of retrieval augmented generation (RAG) in open-source AI, the future of knowledge bases and weight manipulation, advancements in knowledge graphs and vector databases, and the convenience of AI integration in devices.
Transitioning from stateless models to pre-baked models presents new opportunities for building business around software.
Co-training language models with retrieval models and integrating formal representations of knowledge are emerging architectural paths in the field.
Open-source frameworks and communities reduce barriers to building systems using language models with retrieval augmentation.
Deep dives
Transitioning from stateless to pre-baked models
The podcast discusses the transition from stateless models to pre-baked models, highlighting the benefits of using pre-baked models with augmented retrieval. It emphasizes the advantages of having a large language model (LLM) with external memory and retrieval systems to enhance the capabilities and performance of language models.
Exploring different architectural paths
The podcast explores the various architectural paths that are emerging in the field, such as co-training language models with retrieval models, refining the retrieval stack, and integrating formal representations of knowledge into the system. It highlights the ongoing research and development in these areas to improve the performance and efficiency of language models with retrieval augmentation.
Lowering the barrier to build systems
The podcast discusses the excitement around the reduction of barriers to building systems using language models with retrieval augmentation. It emphasizes how open-source frameworks like DSPY and communities contribute to the development and centralized discovery of pipelines and programs, enabling engineers to easily build new products and systems using LLMs and retrieval models.
Enhancing search capabilities and user experiences
The podcast anticipates advancements in search capabilities and user experiences as LLM inference costs decrease and generative feedback loops become more prevalent. It envisions a future where LLMs simulate conversations, create data, explore different ideas, and generate massive vector indexes for new use cases and applications.
Focusing on good enough solutions
The podcast highlights the importance of finding good enough solutions that balance performance, cost, and secondary factors. It acknowledges that achieving good performance with augmented retrieval models may not always necessitate end-to-end training and explores how other architectural decisions can be driven by various factors beyond pure performance.
Hey everyone! We are super excited to publish this podcast with Vinod Valloppillil and Bob van Luijt on Open-Source AI and future directions for RAG! The podcast begins by discussing Vinod's "Halloween Documents", a series of internal strategy writings at Microsoft related to the open-source software movement! The conversation continues to discuss the current state of Open-Source in AI. One of the major points Bob has been making about the business of AI models is that the models themselves are *stateless*, akin to an MP3 file. Vinod pushes back a bit on this definition and jointly it is then settled that these models neither fall into the pure stateful or stateless bucket, rather a "pre-baked" bucket -- presenting completely new opportunities to build business around software. The conversation then continues to discuss the particular details of how people are building RAG systems and many directions for how that may evolve!
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