Speaker Details

Luigi Fugaro
Luigi Fugaro's journey into the realm of computer science began in the vibrant world of video games, starting with the Vic 20 and Atari ST1040. This early exposure ignited a fascination with the inner workings of games, particularly the allure of manipulating game code to unlock endless lives and energy. This initial intrigue was the catalyst for Luigi's foray into programming, marking the start of a rich and diverse professional path.Throughout his distinguished career, Luigi has demonstrated a remarkable versatility, mastering an array of programming languages from the structured precision of Fortran to the modern fluency of Java, Go, Delphi, Visual Basic, and Python. His relationship with JavaScript is a bit more nuanced, viewing it as borderline in the programming language spectrum. Though he doesn’t classify HTML as a programming language per se, Luigi holds a deep respect for its capabilities and applications.As his career progressed, Luigi ventured beyond the boundaries of coding, exploring the increasingly critical domains of observability, monitoring, and data management. A pivotal chapter in his career unfolded at Red Hat and Redis, where he realized the critical role of application performance for clients, further enriching his professional expertise.Now, Luigi remains as enthusiastic and driven as ever, constantly seeking new knowledge and challenges. His passion for technology not only leads him to embark on numerous side projects - most of which remain unfinished except for his notable literary contributions - but also keeps him at the forefront of innovation in the ever-evolving field of computer science.
Vector databases are redefining data handling, enabling semantic searches across text, images, and audio encoded as vectors.
Redis OM for Java simplifies this innovative approach, making it accessible even for those new to vector data.
This presentation explores the cutting-edge features of vector search and semantic caching in Java, highlighting the Redis OM library through a demonstration application.
Redis OM has evolved to embrace the transformative world of vector database technology, now supporting Redis vector search and seamless integration with OpenAI, Hugging Face, LangChain, and LlamaIndex. This talk highlights the latest advancements in Redis OM, focusing on how it simplifies the complex process of vector indexing, data modeling, and querying for AI-powered applications. We will explore the new capabilities of Redis OM, including intuitive vector search interfaces and semantic caching, which reduce the overhead of large language model (LLM) calls.