GenAI Productionize 2.0: The premier conference for GenAI application development
Research backed evaluation foundation models for enterprise scale
Learn to setup a robust observability solution for RAG in production
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.
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.
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.
Llama 3 insights from the leaderboards and experts
Low latency, low cost, high accuracy GenAI evaluation is finally here. No more ask-GPT and painstaking vibe checks.
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.
An exploration of type of hallucinations in multimodal models and ways to mitigate them.
Top Open And Closed Source LLMs For Short, Medium and Long Context RAG
Learn to do robust evaluation and beat the current SoTA approaches
Learn the intricacies of evaluating LLMs for RAG - Datasets, Metrics & Benchmarks
Learn to create and filter synthetic data with ChainPoll for building evaluation and training dataset
Working with Natural Language Processing?
Read about Galileo’s NLP Studio