Building a Document Intelligence AI Application: Live Demo in Snorkel Flow
Extract interest rate dividends from 10K documents using Snorkel Flow's foundation model-first workflow for document intelligence tasks.
Improving Data and Modeling for Computer Vision Applications
Explore advancements in computer vision for data-centric image classification. Learn about visual prompts, parameter-efficient models, and adapting representations for improved performance and efficiency.
How Wayfair Uses AI to Build Better E-Commerce Experiences
Explore Wayfair's ML strategies for enhancing e-commerce, from customer understanding to catalog enrichment. Learn about data-centric approaches and SME-DS collaboration for improved product discovery.
Tackling Advanced Classification Using Snorkel Flow
Explore advanced classification techniques using Snorkel Flow, addressing challenges in label schema, high cardinality, and multi-label problems while leveraging foundation models for production-ready solutions.
The Making of RedPajama and the Future of Open-Source AI
Explore the creation of RedPajama, an open-source AI project, and its impact on the future of AI. Learn about data collection and training processes for building leading open-source models.
Getting Started with Gemini on Vertex AI
Explore Gemini on Vertex AI: Learn tools, techniques, and evaluation methods for building with foundation models in this introductory workshop.
Jumpstart Your AI/ML Program with Vertex AI Model Garden
Explore Vertex AI Model Garden to easily deploy and manage state-of-the-art AI models, transforming your startup with minimal coding and effort.
Foundation Models in the Modern Data Stack - Part 2
Explore foundation models' applications in data analytics, cleaning, and linkage. Learn solutions for production deployment challenges in the modern data stack.
LLMOps and GenAI at Enterprise Scale - Challenges and Opportunities
Explore challenges and opportunities in deploying GenAI solutions at enterprise scale. Learn about LLMOps, model selection, emerging stacks, and best practices for robust implementation.
GENIE: Generative Foundation Models for Automated Climate Science
Explore generative foundation models for automated climate science with Rose Yu's GENIE project, advancing AI applications in environmental research.
Foundation Models for Materials Synthesis
Explore foundation models for materials synthesis, focusing on AI-driven approaches to accelerate discovery and innovation in materials science.
Simplified Training, Tuning and Deployment of Foundational Models as a Service with Red Hat OpenShift
Simplify end-to-end lifecycle of foundation models using Red Hat OpenShift Data Science. Learn about cloud-native, scalable stack for training, tuning, and inferencing with integrated open-source components.
Tabular Learning: Skrub and Foundation Models - Automating Data Wrangling
Explore tabular learning with skrub library, automating data wrangling and simplifying complex pipelines for efficient machine learning on organizational data.
Advanced Computer Vision Workflows with Foundation and Custom Models
Build computer vision applications by combining foundation models like Segment Anything 2 with custom trained models like YOLOv8, using Roboflow Workflows for efficient and powerful image processing pipelines.
AI, Machine Learning, Deep Learning and Generative AI Explained
Explore AI, ML, DL, and Generative AI concepts, their evolution, and impact. Learn about large language models, chatbots, and deepfakes while clarifying misconceptions in this concise overview.
Generative AI for Multimodal Biomedicine
Explore groundbreaking developments in multimodal biomedical AI, covering advanced foundation models for pathology imaging, retinal analysis, and integrated biomedical imaging across multiple modalities.
The Dual Nature of Consistency in Foundation Models - Challenges and Opportunities
Explore the complexities of consistency in Large Language Models, including measurement methods, mitigation strategies, and leveraging opportunities for improved model reliability.
Improving Security Outcomes with Generative AI
Discover how to leverage foundation models and generative AI to enhance security operations, reduce risks, and implement practical AI solutions for your security team.
Mastering Generative AI: Harnessing AWS GenAI for Your Solutions
Explore AWS GenAI solutions, from foundation models to Amazon Bedrock and Claude 3. Learn about customization, knowledge bases, agents, and CodeWhisperer for innovative AI implementation.
Build and Orchestrate Serverless Generative AI Applications
Learn to build and orchestrate serverless generative AI applications using AWS services like Amazon Bedrock and Step Functions. Explore integration techniques, error handling, and human feedback loops in AI workflows.
Operational Excellence for LLMs Using Amazon Bedrock - Conf42 LLMs 2024
Explore operational excellence for LLMs using Amazon Bedrock. Learn design principles, LLMOps, model lifecycle, customization, and architectural patterns for effective implementation and evaluation.