Enhancing LLMs with Retrieval Augmented Generation by Andrei Bondarev of Langchain.rb скачать в хорошем качестве

Enhancing LLMs with Retrieval Augmented Generation by Andrei Bondarev of Langchain.rb

The 2023 breakthroughs in Generative AI have been taking the software development world by storm. We'll take a look at a few components of what is quickly becoming the modern stack for building LLM-powered applications. Andrei will build a case for Ruby in the emerging AI trend, and show how some of the AI capabilities can be leveraged today! Bio: Andrei has been a software engineering professional for 13 years. Among many others he’s been fortunate to make his impact at Spree Commerce (Acquired by First Data), WeddingWire (merged with The Knot), FiscalNote (IPO), National Public Radio, and USA Today. He currently runs a software dev firm, and serves as an Architect/Engineering Manager/Fractional CTO on the client projects. Consumed by the AI wave this year, Andrei pondered what the future holds for Ruby in the world of ever-growing AI/ML needs. Having just completed a massive client project building a keyword search with Elasticsearch, Andrei dove into the current landscape of semantic search capabilities and the vector search databases. This led him to building Langchain.rb, an “original Langchain”-inspired open source library for building LLM-powered applications. In his free time he enjoys playing tennis and going on long runs while listening to podcasts.