Data Fabrics and Knowledge Graphs for the AI Enterprise
Explore data fabrics and knowledge graphs as essential tools for integrating enterprise knowledge, enhancing AI capabilities, and democratizing data access across organizations.
Why an Event-Native Mindset Is Essential for Data Architecture
Embrace an Event-Native Mindset to build a responsive data architecture. Learn to model events, create an enterprise nervous system, and enable real-time action and prediction using event-driven knowledge architecture.
Neuro-Symbolic AI and AllegroGraph 8.0: Revolutionizing Enterprise Knowledge Graphs
Explore AllegroGraph 8.0's revolutionary features in Enterprise Knowledge Graphs and Neuro-Symbolic AI. Learn how it integrates LLMs, Machine Learning, Symbolic AI, and Logic to enhance AI accuracy and reliability.
The Art of Building AI Systems - Rapid Training Data Creation
Learn techniques for rapidly creating annotated training data to build accurate and robust AI systems using clinical reports.
Data-Centric Development is Key to Production-Level AI
Explore data-centric AI development approaches for adapting foundation models to complex use cases, focusing on techniques for pre-training, instruction-tuning, and task-specific fine-tuning.
ROBOSHOT: Improving Foundation Model Performance Without Fine-Tuning
Boost zero-shot foundation model performance with ROBOSHOT. Learn to improve robustness, reduce biases, and understand conditions for enhanced results without fine-tuning.
New in Snorkel Flow 2024.R1: Enhanced Security, Image Categorization, and More
Explore Snorkel Flow's latest release: enhanced security, image categorization, LLM integrations, and document intelligence workflows for advanced AI-driven insights and custom solutions.
Fine-Tuning Large Language Models Faster Using Bonito for Task-Specific Training Data Generation
Accelerate LLM fine-tuning with Bonito: Generate task-specific training data for faster instruction tuning and improved zero-shot task adaptation on specialized, private datasets.
Optimizing RAG Implementations for Specialized Enterprise Tasks
Optimize RAG implementations for enterprise tasks. Learn to fine-tune components, apply AI data development techniques, and accelerate production delivery for increased accuracy and precision.
How to Accelerate AI Training With Programmatic Data Labeling - Snorkel Flow Demo
Accelerate AI development with programmatic data labeling. Learn efficient knowledge capture, automated labeling, and iterative improvement techniques for enterprise AI initiatives.
Large Language Models Can Help Make Better Image Classifiers
Explore how follow-up differential descriptions enhance zero-shot image classification by tailoring class descriptions, improving performance and addressing ambiguities in datasets.
How to Fine-Tune LLMs for Specialized Enterprise Tasks - Curating Data and Emerging Methods
Explore fine-tuning methods for LLMs, learn to curate high-quality training data efficiently, and understand evaluation techniques for accurate enterprise deployment of specialized language models.
How to Evaluate LLM Performance for Domain-Specific Use Cases
Explore advanced LLM evaluation techniques for enterprise AI, including data-centric approaches, quality modeling, and fine-grained benchmarking to overcome common challenges and improve performance.
How to Optimize RAG Pipelines for Domain- and Enterprise-Specific Tasks
Master RAG pipeline optimization for accurate, reliable LLM applications. Learn semantic document chunking, embedding techniques, and fine-tuning strategies. Leverage Snorkel Flow to accelerate development and overcome retrieval errors.
Alfred: Building Training Data with Foundation Models and Weak Supervision - Snorkel AI
Streamline data labeling with Alfred, combining foundation models and weak supervision to create high-quality training datasets for academic research and machine learning projects.
Task Me Anything: Revolutionizing Multimodal Model Benchmarking
Explore Task Me Anything platform for efficient multimodal model evaluation. Learn programmatic task generation and active learning techniques to create custom benchmarks for data science projects.
Revolutionizing Data Analysis: Combining LLM, RAG, and Domain Knowledge
Leverage NLP and RAG systems to extract insights from structured and unstructured data, generate actionable insights, and empower data-driven analysis without SQL.
Curate Training Data via Labeling Functions - 10 to 100x Faster
Accelerate data labeling for AI models using programmatic techniques. Learn to capture SME knowledge, improve label accuracy, and explore real-world use cases in banking, pharma, and healthcare.
Inference and Uncertainty Quantification for Noisy Matrix Completion - Lecture 5
Explore inference and uncertainty quantification for noisy matrix completion, focusing on de-biased estimators and their distributional characterizations for optimal confidence interval construction.
Projected Power Method: An Efficient Algorithm for Joint Discrete Assignment - Lecture 3
Explore an efficient algorithm for joint discrete assignment using projected power method. Learn about low-complexity procedures, optimization techniques, and statistical models for solving discrete assignment problems.
Random Initialization and Implicit Regularization in Nonconvex Statistical Estimation - Lecture 2
Explore nonconvex optimization in statistical estimation, focusing on gradient descent's convergence to optimal solutions without explicit regularization or careful initialization.