Unify Project Demo - RAG Playground with LangChain
Explore a LangChain RAG Playground for document analysis, comparing LLM performance across providers for optimal speed, latency, and cost using dynamic routing.
Deep Dive: Exception Handling in the Ivy Framework - Tutorial 18
Explore exception handling implementation and behavior in the Ivy Framework, enhancing your understanding of error management.
Deep Dive: Ivy Framework Testing Implementation and Behavior - Tutorial 15
Explore Ivy Framework's testing implementation and behavior, gaining insights into its functionality and structure.
Integration of Electronic Medical Records and Informatics in Stroke Recovery - SKSI 2022
Explore electronic medical records integration in stroke recovery, focusing on learning health systems and collaborative design for improved patient outcomes.
Artificial Intelligence Primer for Pediatric Cardiac Imaging
Explore AI's impact on pediatric cardiac imaging with Dr. Shelby Kutty. Gain insights into machine learning, neural networks, and their applications in diagnosing cardiac conditions.
Where Does Negative Transfer Come From? On the Implicit Bias of SGD in Multi-Task Learning
Explore negative transfer in multi-task learning, examining task conflict, optimization temperature, and SGD's implicit bias. Gain insights into generalization challenges in neural networks.
How to Go Beyond Research
Explore strategies for translating AI research into real-world impact, focusing on cooperation and conflict resolution among AI systems.
Building a Healthcare and Life Sciences Knowledge Graph with Synthea and ChatGPT
Explore plug-and-play healthcare Knowledge Graphs and ChatGPT's role in answering questions, generating graphs, and creating medical notes. Learn about entity-event models and AI-human collaboration.
Neuro-Symbolic AI with AllegroGraph
Explore Neuro-Symbolic AI's fusion of neural networks and symbolic AI. Learn how AllegroGraph's Knowledge Graph Platform enables complex reasoning and data integration for advanced AI applications.
LIGER: Fusing Model Embeddings and Weak Supervision for Improved NLP and Vision Tasks
Explore LIGER: a novel approach fusing foundation model embeddings with expert-driven labeling functions to enhance NLP and vision tasks.
The Ethical Implications of Building a Real-Life Skynet
Explore the ethical challenges and limitations of generative AI, its potential for improvement, and its broader implications in the evolving landscape of artificial intelligence.
Maximize ML Model Performance with Data-IQ Framework
Discover Data-IQ: a framework to stratify data into subgroups, enabling systematic auditing of ML models across tabular, image, and text data for improved performance and reliable usage.
SQL for Efficient Data Organization in Machine Learning
Explore JoinBoost, a Python library transforming tree training algorithms into SQL queries for efficient ML on normalized databases, offering improved performance and scalability.
Modeling Human Preference to Improve LLM Performance
Explore techniques for aligning language models with human preferences, including reward modeling and scalable tools to improve LLM performance with minimal end-user guidance.
Data Development for Improving GenAI Systems - A Systems-Level Approach
Explore how data development enhances GenAI systems through a case study improving RAG accuracy by 54 points in 3 weeks using scalable tools for embedding and retrieval models.
Mastering LLMs with Skill-it! and Zero-Shot Robustification
Explore innovative techniques for optimizing language models: Skill-it! for efficient training and zero-shot robustification for improved performance. Learn data-driven approaches to enhance AI capabilities.
Why GenAI Needs Careful Training Data Management
Explore the critical role of training data management in GenAI, including harmonization across stages and its impact on model effectiveness and safety in various domains and languages.
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.
Conquer RAG Retrieval Errors: 5-Step Tuning Process in Snorkel Flow
Optimize RAG retrieval with a 5-step tuning process in Snorkel Flow. Learn to identify errors, improve document chunking, and enhance embedding models for better accuracy and performance.
When, Why and How to Fine-Tune LLMs for Enterprise Applications
Explore techniques for customizing large language models in enterprise settings, including when and why to align LLMs and key methods for domain-specific adaptation.
How Numbers Station Combines LLM, RAG, and Domain Knowledge for AI-Driven Data Analysis
Leverage AI for comprehensive data analysis by combining structured and unstructured data, using multi-agent systems, and building AI-powered assistants for actionable insights.