Posts tagged LLMs
Webinar - Deeplearning.ai + Galileo - Mitigating LLM Hallucinations
Join in on this workshop where we will showcase some powerful metrics to evaluate the quality of the inputs (data quality, RAG context quality, etc) and outputs (hallucinations) with a focus on both RAG and fine-tuning use cases.
Galileo + Google Cloud: Evaluate and Observe Generative AI Applications Faster
Galileo on Google Cloud accelerates evaluating and observing generative AI applications.
Mastering RAG: LLM Prompting Techniques For Reducing Hallucinations
Dive into our blog for advanced strategies like ThoT, CoN, and CoVe to minimize hallucinations in RAG applications. Explore emotional prompts and ExpertPrompting to enhance LLM performance. Stay ahead in the dynamic RAG landscape with reliable insights for precise language models. Read now for a deep dive into refining LLMs.
Mastering RAG: 8 Scenarios To Evaluate Before Going To Production
Learn how to Master RAG. Delve deep into 8 scenarios that are essential for testing before going to production.
A Metrics-First Approach to LLM Evaluation
Learn about different types of LLM evaluation metrics needed for generative applications
5 Key Takeaways From President Biden’s Executive Order For Trustworthy AI
Explore the transformative impact of President Biden's Executive Order on AI, focusing on safety, privacy, and innovation. Discover key takeaways, including the need for robust Red-teaming processes, transparent safety test sharing, and privacy-preserving techniques.
Pinecone + Galileo = get the right context for your prompts
Galileo LLM Studio enables Pineonce users to identify and visualize the right context to add powered by evaluation metrics such as the hallucination score, so you can power your LLM apps with the right context while engineering your prompts, or for your LLMs in production
RAG Vs Fine-Tuning Vs Both: A Guide For Optimizing LLM Performance
A comprehensive guide to retrieval-augmented generation (RAG), fine-tuning, and their combined strategies in Large Language Models (LLMs).
Generative AI and LLM Insights: February 2024
February's AI roundup: Pinterest's ML evolution, NeurIPS 2023 insights, understanding LLM self-attention, cost-effective multi-model alternatives, essential LLM courses, and a safety-focused open dataset catalog. Stay informed in the world of Gen AI!
Mastering RAG: How To Evaluate LLMs For RAG
Learn the intricacies of evaluating LLMs for RAG - Datasets, Metrics & Benchmarks
Tricks to Improve LLM-as-a-Judge
Unlock the potential of LLM Judges with fundamental techniques
State of AI 2024: Business, Investment & Regulation Insights
Industry report on how generative AI is transforming the world.
Introducing the Hallucination Index
The Hallucination Index provides a comprehensive evaluation of 11 leading LLMs' propensity to hallucinate during common generative AI tasks.
Paper - Galileo ChainPoll: A High Efficacy Method for LLM Hallucination Detection
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.
Generative AI and LLM Insights: April 2024
Smaller LLMs can be better (if they have a good education), but if you’re trying to build AGI you better go big on infrastructure! Check out our roundup of the top generative AI and LLM articles for April 2024.
Mastering RAG: How To Architect An Enterprise RAG System
Explore the nuances of crafting an Enterprise RAG System in our blog, "Mastering RAG: Architecting Success." We break down key components to provide users with a solid starting point, fostering clarity and understanding among RAG builders.
Understanding LLM Hallucinations Across Generative Tasks
The creation of human-like text with Natural Language Generation (NLG) has improved recently because of advancements in Transformer-based language models. This has made the text produced by NLG helpful for creating summaries, generating dialogue, or transforming data into text. However, there is a problem: these deep learning systems sometimes make up or "hallucinate" text that was not intended, which can lead to worse performance and disappoint users in real-world situations.
Generative AI and LLM Insights: March 2024
Stay ahead of the AI curve! Our February roundup covers: Air Canada's AI woes, RAG failures, climate tech & AI, fine-tuning LLMs, and synthetic data generation. Don't miss out!
Mastering RAG: How To Observe Your RAG Post-Deployment
Learn to setup a robust observability solution for RAG in production
Mastering Data: Generate Synthetic Data for RAG in Just $10
Learn to create and filter synthetic data with ChainPoll for building evaluation and training dataset
Best LLMs for RAG: Top Open And Closed Source Models
Top Open And Closed Source LLMs For Short, Medium and Long Context RAG
Is Llama 3 better than GPT4?
Llama 3 insights from the leaderboards and experts
15 Key Takeaways From OpenAI Dev Day
Galileo's key takeaway's from the 2023 Open AI Dev Day, covering new product releases, upgrades, pricing changes and many more!
Galileo Luna: Breakthrough in LLM Evaluation, Beating GPT-3.5 and RAGAS
Research backed evaluation foundation models for enterprise scale
A Framework to Detect & Reduce LLM Hallucinations
Learn about how to identify and detect LLM hallucinations
Generative AI and LLM Insights: August 2024
While many teams have been building LLM applications for over a year now, there is still much to learn about RAG and all types of hallucinations. Check out our roundup of the top generative AI and LLM articles for August 2024.
5 Techniques for Detecting LLM Hallucinations
A survey of hallucination detection techniques
Generative AI and LLM Insights: May 2024
The AI landscape is exploding in size, with some early winners emerging, but RAG reigns supreme for enterprise LLM systems. Check out our roundup of the top generative AI and LLM articles for May 2024.
Survey of Hallucinations in Multimodal Models
An exploration of type of hallucinations in multimodal models and ways to mitigate them.
Mastering RAG: Adaptive & Corrective Self RAFT
A technique to reduce hallucinations drastically in RAG with self reflection and finetuning
Solving Challenges in GenAI Evaluation – Cost, Latency, and Accuracy
Learn to do robust evaluation and beat the current SoTA approaches