Training Retrieval Augmented Generation With Ola Piktus
Apr 9, 2024
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Join Ola Piktus, a research expert at Cohere, as she discusses retrieval-augmented generation (RAG) in AI models. Dive into topics like model hallucination, RAG applications in real-world scenarios, and the balance between creativity and accuracy. Explore Ola's career journey from software engineering to cutting-edge AI research in a captivating conversation.
RAG enhances language models by integrating external sources for accuracy and reliability.
The evolution of retrieval methods in language models highlights future advancements and responsibilities of organizations.
Transition from sparse to dense retrievers in information retrieval signifies technological advancements and integration with language models.
Deep dives
Retrieval-Augmented Generation Enhancing Language Models with External Information
Retrieval augmented generation integrates large language models with external sources, aiming to improve accuracy and reliability. Cohere's Command R and Command R Plus models optimize advanced RAG use cases by offering citations, multi-step tool use for task automation, and multi-lingual task excellence, available on various cloud platforms. For instance, Command R Plus efficiently retrieves information like top-performing movies in 2022, visually presents the data with citations, showcasing the power of multi-step tool use in RAG.
Evolution of RAG Techniques and Expert Insights
Raga plays a pivotal role in enhancing language models' functionalities, enabling natural language interaction for information retrieval, processing, and customization. Olapictus, an expert in RAG techniques, sheds light on the evolution of retrieval methods in language models. She emphasizes the responsibility of organizations building these systems and offers insights into future advancements and challenges.
Sparse vs. Dense Retriever Models in Information Retrieval
The distinction between sparse and dense retriever models in information retrieval impacts search efficiency and relevance. While sparse retrieval relies on term statistics like BM25, dense retrieval utilizes deep learning models such as BERT to generate compact vector representations for improved accuracy. The transition to dense retrieval signifies advancements in search technology and the potential for deeper integration with language models.
Exploring the Role of Models in Creativity
Models in artificial intelligence are not expected to have the same understanding of concepts as humans do. In many cases, models are encouraged to be creative rather than strictly factual. The development of models like RAG aims to strike a balance between creativity and accuracy in output, providing flexibility for different user intents and scenarios.
Improving Wikipedia Citations with AI
A recent paper co-authored by the speaker focuses on enhancing the verifiability of Wikipedia through AI tools. By leveraging AI, the project aims to assist Wikipedia editors in improving citations by generating better sources for Wikipedia content. The project underscores the importance of bridging research with real-world applications, highlighting the potential impact of AI technology in enhancing information accuracy and reliability.
In today's episode, I chat about retrieval-augmented generation (RAG) with Ola Piktus, Member of Technical Staff at Cohere. With her roots in software engineering and significant contributions to RAG through her research, Ola has an interesting perspective on the evolution of RAG and the language technology landscape.
We cover a range of topics, including the potential of RAG to address model hallucination, the transition from theory to real-world application, and the balance between creativity and accuracy in AI models. Ola’s journey from software engineering to state-of-the-art research in AI is a rare glimpse into the development of language tech.
Watch the episodes on YouTube: https://www.youtube.com/playlist?list=PLhBwB1lBTwJWR19WkJw87EMh1JU9O7Uff I'm a co-author of a manual on GPT-3 and OpenAI API (Packt, 2023): https://www.packtpub.com/product/gpt-3/9781805125228 You can keep in touch with me via socials: IG, TikTok, X, LinkedIn @itsSandraKublik Sign up for my Substack newsletter for the personal scoop on the topics covered today: https://substack.com/@itssandrakublik Website: www.sandrakublik.com For brand collabs, reach out to me at team@sandrakublik.com
