Learn to setup a robust observability solution for RAG in production
Learn about different types of LLM evaluation metrics needed for generative applications
See how easy it is to leverage Galileo's platform alongside the IBM watsonx SDK to measure RAG performance, detect hallucinations, and quickly iterate through numerous prompts and LLMs.
The LLM Hallucination Index ranks 22 of the leading models based on their performance in real-world scenarios. We hope this index helps AI builders make informed decisions about which LLM is best suited for their particular use case and need.
Evaluations are critical for enterprise GenAI development and deployment. Despite this, many teams still rely on 'vibe checks' and manual human evaluation. To productionize trustworthy AI, teams need to rethink how they evaluate their solutions.
Low latency, low cost, high accuracy GenAI evaluation is finally here. No more ask-GPT and painstaking vibe checks.
ChainPoll: A High Efficacy Method for LLM Hallucination Detection. ChainPoll leverages Chaining and Polling or Ensembling to help teams better detect LLM hallucinations. Read more at rungalileo.io/blog/chainpoll.
LLM Studio helps you develop and evaluate LLM apps in hours instead of days.
Webinar - Announcing Galileo LLM Studio: A Smarter Way to Build LLM Applications
Learn the intricacies of evaluating LLMs for RAG - Datasets, Metrics & Benchmarks
Unlock the potential of LLM Judges with fundamental techniques
Master the art of building your AI evaluators using LLMs
Learn to create and filter synthetic data with ChainPoll for building evaluation and training dataset
Top Open And Closed Source LLMs For Short, Medium and Long Context RAG
Llama 3 insights from the leaderboards and experts
Research backed evaluation foundation models for enterprise scale
At GenAI Productionize 2024, expert practitioners shared their own experiences and mistakes to offer tools and techniques for deploying GenAI at enterprise scale. Read key takeaways from the session on how to productionize generative AI.
Unsure of which embedding model to choose for your Retrieval-Augmented Generation (RAG) system? This blog post dives into the various options available, helping you select the best fit for your specific needs and maximize RAG performance.
Unlock the potential of RAG analysis with 4 essential metrics to enhance performance and decision-making. Learn how to master RAG methodology for greater effectiveness in project management and strategic planning.
It’s time to put the science back in data science! Craig Wiley, Sr Dir of AI at Databricks, joined us at GenAI Productionize 2024 to share practical tips and frameworks for evaluating and improving generative AI. Read key takeaways from his session.
An exploration of type of hallucinations in multimodal models and ways to mitigate them.
Learn to do robust evaluation and beat the current SoTA approaches
Understand the tradeoffs between LLMs and humans for generative AI evaluation