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.
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 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.
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.
Understanding Human Functioning and Enhancing Human Potential through Computational Methods
Explore computational methods for analyzing human functioning, enhancing potential, and improving efficiency through multimodal approaches in diverse contexts.
Building Trustworthy AI for Environmental Science
Explore trustworthy AI methods for environmental science, focusing on weather, climate, and coastal oceanography predictions, with insights on hail and tornado forecasting.
Tune in and Dropout - How Data Augmentation Can Help Us Build Better Brain Decoders
Explore data augmentation techniques for improving brain decoders, enhancing neural signal interpretation and brain-computer interface performance.
Delivering Intelligent Operations to Industrial Frontline through Visual Guidance and AI
Empower industrial frontline workers with AI and Visual Guidance for enhanced precision, speed, and reliability in critical operations.
SuSLik: Deductive Synthesis of Safe Programs with Pointers - Tutorial 1b
Explore deductive program synthesis for creating provably correct pointer-manipulating programs using SuSLik. Practice specifying programs with formal logic and learn about separation logic.
Moving Beyond the First Portrait of Our Milky Way's Black Hole by Leveraging Underlying Structure
Explore computational imaging techniques used to capture black hole images and leverage data structure to extract evolving details of the Milky Way's supermassive black hole.
AI for Scientists: Accelerating Discovery through Knowledge, Data and Learning
Explore AI-driven scientific discovery, integrating machine learning with expert knowledge to automate data analysis and accelerate research across diverse domains.
Fine-Tuning Vision Transformer Classifier for EyePacs Dataset Quality Model - Part 1
Fine-tune a Vision Transformer for image quality assessment using the EyeQ dataset, a subset of EyePacs, to enhance diabetic retinopathy detection capabilities.
Fine-Tuning Vision Transformer for Diabetic Retinopathy Detection - Part 2
Fine-tune a Vision Transformer for diabetic retinopathy detection using EyeQ dataset. Learn to adapt pretrained models for specialized medical image classification tasks.