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Retrieval Reimagined: LLM & Embedding Mastery using OSS locally.

Engineering Trust: Practical AI Governance for Real-World Deployments

Reshaping the Business using AI

Bridging Worlds with Words: Innovations at the Lee Language Lab

LLMOps Infrastructure for Production-Grade Agentic RAG Applications with Union.ai

Scaling Down, Powering Up: Can Efficient Training Beat Scaling Laws?

Optimized RAG: Strategies for Cost and Scale

CPU Inferencing of Language Models in Teradata

Agentic AI Workshop: Where Innovation Meets Implementation

Stop RESTing — Wake up your AI with MCP

RAG: The 2025 Best-Practice Stack, Prototype to Production

Fuel iX: Powering Enterprise-Wide Productivity with Generative AI

Case Study: How Does DeepSeek’s FlashMLA Speed Up Inference

Scaling Large Language Models: Getting Started with Large-Scale Parallel Training of LLMs

Tackling challenges in scaling test-time compute

Training on AMD Instinct GPUs: From Pre-training to Fine-tuning and Post-training Strategies

Explainable Forecasting through Causal Inference

From Executives’ Delusions to Making AI Enablement a Reality: Bridging Data Readiness Gap

Machine Learning for Machine Uptime: AI-Powered Fault Detection & Predictive Maintenance

Optimizing NLP Workflows by Combining GenAI and Traditional LLMs

Building with GenAI: What It Really Takes to Get Bots into the Wild

Generative AI for Retail: Personalization with Diffusion Models

Scaling Ultra Low Latency LLM Inference

GARAGe: How ADA Uses LLMs to Make Retrieval Smarter

Ensuring Data Security in the AI Revolution

Scaling of Quantized Large Language Models for Efficient Inference

Towards World Models and General Agents

Uncovering Financial Fraud with Graph Machine Learning at Scale

Automating Workflows with a Deterministic Network of Modular Agents

The Celestial Mechanics of Attention Mechanisms