Evaluating LLMs and RAG Pipelines at Scale
Explore techniques for evaluating Large Language Models and RAG pipelines in production, focusing on Valor, an open-source evaluation service for rigorous real-world testing.
Better Chatbots with Advanced RAG Techniques
Explore advanced RAG techniques for building superior chatbots. Learn hybrid search, query generation, result filtering, re-ranking, and chunking to enhance information retrieval and user interactions.
The Best Component for Your RAG System - Optimizing with AutoRAG
Optimize RAG systems automatically with AutoRAG. Boost performance by finding the ideal pipeline for your data and use-case through efficient evaluation of various modules.
Why AI Apps Don't Work in Production: AI Reliability Survey
Explore AI reliability challenges in production, survey techniques for improvement, and gain insights from 18 months of solving AI engineering reliability issues.
Deploying GenAI Applications to Enterprises: Custom Evaluation Models and LLMOps Workflow - MLOps World
Explore challenges and solutions in deploying conversational AI to enterprises, focusing on accuracy optimization, LLMOps workflows, and infrastructure requirements for scalable implementation.
From Idea to Production: AI Infrastructure for Scaling LLM Applications
Explore strategies for scaling LLM applications from beta to production, addressing challenges and building adaptable AI infrastructure for evolving models and workflows.
Data Versioning in Generative AI - A Pathway to Cost-effective Machine Learning
Explore data versioning strategies for generative AI, focusing on cost-effective techniques to minimize processing time and API calls while enhancing collaboration and efficient versioning of annotations and embeddings.
Making Enterprise GenAI Safe and Effective - Tools and Approaches
Explore tools and approaches for safe, effective enterprise GenAI deployment, including finetuning, moderation guardrails, and sidecar systems for automated compliance.
Running Prompts at CI: Why It Doesn't Make Your GenAI App Enterprise-Ready
Explore challenges and best practices for deploying GenAI applications in enterprise environments beyond basic CI prompt testing.
Innovating Responsibly with AI: Minimizing Risks and Maximizing Opportunities
Explore Adobe's blueprint for responsible AI innovation, gaining insights to develop your organization's strategy for maximizing opportunities while minimizing risks.
Unleashing AI-Powered Threat Detection and Response in the SOC
Explore AI-powered threat detection in SOCs, focusing on cloud and hybrid environments. Learn real-world applications and future implications for cybersecurity operations.
Leveraging AI in Cybersecurity - Fighting Fire with Fire
Explore AI-driven strategies to fortify cloud workloads against evolving cyber threats, from development to runtime, ensuring comprehensive protection throughout the lifecycle.
Secure AI Transformation: What We Can Do Now and in the Future
Explore new threats, strategies, and best practices for securely transforming AI initiatives, focusing on safeguarding AI applications, development, data, and runtime environments.
Apache Airflow: Where Data Engineers and ML Engineers Meet
Explore production-quality Generative AI pipelines using Apache Airflow. Learn to orchestrate workflows, integrate data engineering, and implement MLOps best practices for robust AI applications.
Beyond the Model Zoo - Optimizing Foundation Models for Your Application
Optimize foundation models for specific applications, exploring techniques beyond pre-trained models to enhance performance and efficiency in machine learning projects.
Defining Open-Source AI: Challenges and Opportunities in the Evolving Landscape
Explore the complexities of defining Open-Source AI, balancing innovation with core open-source principles in the evolving AI landscape. Engage in shaping a definition that reflects technological progress.
Reproducibility and Data Version Control for LangChain and LLM/OpenAI Models
Explore reproducibility and data version control for LangChain and LLM/OpenAI models using lakeFS. Learn to manage large datasets efficiently and achieve reproducibility in LLM applications.
Deploying Generative AI Models - Best Practices and Interactive Example
Explore best practices for deploying generative AI models at scale, with an interactive example using UbiOps for serverless and cloud-agnostic implementation.
Dynatrace for AI Observability: Monitoring OpenAI, TensorFlow, and Other AI APIs
Gain insights into AI model behavior, performance, and costs using Dynatrace. Monitor OpenAI and TensorFlow APIs, optimize performance, and understand AI observability through practical demonstrations.
Bringing AI to Existing Databases Without Complex MLOps
Integrate AI seamlessly with existing databases, bypassing complex MLOps processes. Learn efficient techniques for enhancing data infrastructure with artificial intelligence.
What Does it Mean to be an AI Engineer in the World of Generative AI
Explore the evolving role of AI Engineers in the era of Generative AI, covering technical aspects and business strategies for both engineers and decision-makers.