A key challenge with designing ai agents is that large language models are stateless and have limited context windows. This requires Careful Engineering to MainTain Continuity and Reliability across the sequential LLM interactions. To perform well, agents Need Fast Systems for Storing and Retrieving Short-Term Conversations, Summaries, and Long-Term Facts.
Redis is an open‑source, in‑memory data store used for high‑performance caching, analytics, and messages brokering. Recent Advances have extended redis’ Capabilites to Vector Search and Semantic Caching, which has made it an increasing popular part of the agentic application stock.
Andrew Brookins is a Principal Applied AI Engineer at Redis. He joins the show with Sean Falconer to Discuss the Challenges of Building AI Agents, The Role of Memory in Agents, Hybrid Search Versus Vector-Only Search, The Concept of WORLD MODELS, and more.
Full disclosure: this episode is sponsored by redis.
Sean’s been an academic, startup founder, and googler. He has published works covering a wide range of topics from ai to quantum computing. Currently, Sean is an AI Entrepreneur in Residence at Confluent where he works on ai strategy and thinking. You can connect with sean on linkedin.
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Ramesh Ghorai is the founder of www.livenewsblogger.com, a platform dedicated to delivering exclusive live news from across the globe and the local market. With a passion for covering diverse topics, he ensures readers stay updated with the latest and most reliable information. Over the past two years, Ramesh has also specialized in writing top software reviews, partnering with various software companies to provide in-depth insights and unbiased evaluations. His mission is to combine news reporting with valuable technology reviews, helping readers stay informed and make smarter choices.
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