Anatomy of a Software 3.0 Company - AI in Production Keynote
Explore the design space of AI-native applications and learn Conviction's framework for assessing value, defensibility, and strategy in Software 3.0 companies.
Building the Next Generation of Reliable AI - Lessons and Predictions
Explore insights on developing reliable AI tools, learn from real-world experiences, and gain predictions on future AI tooling trends. Discover effective techniques and emerging breakthroughs in open-source AI development.
Charting LLMOps Odyssey - Navigating Large Language Model Operations
Navigate the iterative development of LLM applications, addressing unique challenges in LLMOps design. Learn strategies for overcoming obstacles and adapting to the evolving landscape of large language model operations.
From Research to Production: Fine-Tuning and Aligning LLMs
Learn essential steps for transitioning LLMs to production, focusing on fine-tuning and alignment strategies. Explore Supervised Fine-Tuning, RLHF, and DPO for effective LLM alignment with production goals.
The State of Production Machine Learning in 2024
Explore the challenges and best practices for deploying robust, scalable ML systems in production. Learn about key focus areas, recommended tools, and ecosystem insights for effective MLOps at scale.
GenAI in Production - Challenges and Trends - Lecture 224
Explore challenges and trends in Generative AI production, including model size, context windows, multimodality, and regulation. Gain insights from Gemini 1.0 vs 1.5 comparisons and industry expert Verena Weber's experiences.
Innovative Gen AI Applications: Beyond Text - MLOps Mini Summit 5
Explore innovative Gen AI applications beyond text, focusing on molecule discovery and call center optimization. Learn about chemical language models, RAG use cases, and efficient pipeline architectures.
The Rise of Modern Data Management - MLOps Podcast #226
Explore modern data management practices, including data contracts and observability, to improve handling and decision-making in the age of AI and cloud computing.
DSPy Assertions: Computational Constraints for Self-Refining Language Model Pipelines
Explore DSPy Assertions for enhancing language model pipelines with computational constraints, enabling more reliable and accurate systems through automatic prompt optimization and self-refinement.
Leading Enterprise Data Teams - Strategies for Success
Gain insights on leading enterprise data teams, prioritizing relationships, and effective communication in MLOps. Learn pragmatic strategies for project prioritization and navigating data-driven initiatives to success.
Handling Multi-Terabyte LLM Checkpoints - MLOps Podcast #228
Explore techniques for handling multi-terabyte LLM checkpoints, including storage options, saving and loading strategies, and infrastructure considerations for large-scale AI model training.
FedML Nexus AI: Generative AI Platform at Scale - MLOps Podcast #230
Explore FedML Nexus AI, a scalable platform for building and commercializing generative AI applications. Learn about enterprise AI, model deployment, federated learning, and secure, privacy-preserving machine learning.
RecSys at Spotify - Building and Evaluating Large-Scale Recommender Systems
Explore Spotify's large-scale recommender systems, foundational embeddings for transfer learning, evaluation methods, and MLOps challenges with Senior ML Engineer Sanket Gupta.
Retrieval Augmented Generation - Techniques and Applications
Explore Retrieval Augmented Generation with Syed Asad. Dive into production issues, embedding models, inference layer experiments, and the evolving landscape of AI engineering in this insightful discussion.
Open Standards Make MLOps Easier and Silos Harder - MLOps Podcast Episode 234
Explore open standards in MLOps for easier data system integration, scalability, and collaboration. Learn about Ibis, Apache Arrow, and their impact on data engineering and machine learning workflows.
Build Reliable Systems with Chaos Engineering - MLOps Podcast #237
Explore chaos engineering to build reliable systems under unpredictable conditions. Learn benefits, trends, and integration with ML systems for improved resilience and observability.
AWS Trainium and Inferentia - Enhancing AI Performance and Cost Efficiency
Explore AWS Trainium and Inferentia's AI accelerators for enhanced performance, cost savings, and seamless integration with popular frameworks. Learn about their benefits and implementation in ML workflows.
Uber's Michelangelo: Strategic AI Overhaul and Impact - MLOps Podcast
Explore Uber's Michelangelo platform evolution, from basic ML predictions to advanced deep learning and generative AI, addressing challenges and introducing innovative features for streamlined AI operations.
From Robotics to Recommender Systems - MLOps Podcast #240
Explore robotics, computer vision, and recommender systems with Miguel Fierro. Gain insights on ML applications, sports analytics, and AI integration in various fields from a Microsoft Principal Data Science Manager.
Building Production-Ready AI Models for Manufacturing - LatticeFlow Roundtable
Explore production-ready AI models for manufacturing with industry experts. Uncover solutions to data challenges, model failures, and integration issues for robust, safe AI systems.
Navigating the AI Frontier: The Power of Synthetic Data and Agent Evaluations in LLM Development
Explore synthetic data and agent evaluations in LLM development. Learn strategies for enhancing model behavior, prototyping, testing, and fine-tuning to build robust AI applications.