Three AI Use Cases for Analyzing Sales Data
Explore three practical AI applications for analyzing sales data, demonstrated with real-world examples from a warm outreach campaign. Learn data augmentation, structuring unstructured data, and lead scoring techniques.
Compressing Large Language Models (LLMs) with Python Code - 3 Techniques
Explore three LLM compression techniques: quantization, pruning, and knowledge distillation. Learn to implement these methods with Python code examples for efficient model optimization.
Total Synthesis Guidance for Chemists Using LLM and LMM Prompts
Enhance total synthesis efficiency using LLM and LMM prompts to analyze recent papers, extracting key insights for improved yield, purity, and cost-effectiveness in complex organic molecule production.
ChemRxiv: Large Multimodal Models for Chemical Research with Document Retrieval
Explore AI's impact on chemical research through spectra and reaction analysis, leveraging Large Multimodal Models for rapid processing and enhanced image-related tasks.
Paclitaxel Biosynthesis AI Breakthrough: Accelerating Drug Synthesis Research
Explore AI-driven breakthroughs in paclitaxel biosynthesis, covering retrobiosynthesis, microorganism engineering, research areas, and challenges. Gain insights into AI's potential to accelerate drug synthesis advancements.
The Fragmented ML Stack and How to Fix It
Explore the fragmented ML stack, understand Ivy's role in unification, and see demonstrations of function, library, and model transpilation.
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.
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.
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.
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.
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.
AI Copilots for Businesses - Driving Innovation with Generative AI
Explore AI copilots' impact on enterprise productivity and data management, from RAG pipelines to generative AI solutions transforming business operations and customer experiences.
How Top Healthcare Companies Boost AI Development with Data-Centric Approaches
Discover how leading healthcare companies accelerate NLP application development using data-centric AI workflows, reducing development time from months to days.