Explore the potential of random forest models in traffic forecasting and insights for future research aimed at improving urban traffic management systems.
Explore noisy channel language model prompting: few-shot text classification, enhancing stability, handling imbalanced data, and generalizing to unseen labels.
Cyberattacks are becoming increasingly sophisticated. Learn how an identity-first security strategy can tackle the evolving cyber threats in an AI-first-world.
Explore how to harness local language models with Semantic Kernel. Discover the power of running AI on your terms — secure, private, and under your control.
Learn how to navigate technical debt in AI projects, balance rapid adoption with long-term sustainability, and implement best practices for successful AI initiatives.
Explore concepts of AI-driven query processing, key algorithms that enhance search performance, and best practices for optimizing AI-powered retrieval systems.
Explore key strategies for effective data management in AI projects, including real-time access, federated queries, and data literacy for developers and engineers.
Learn about context-specific real-time Generative AI (GenAI) with Retrieval Augmentation Generation (RAG) using Kafka and Flink to prevent hallucinations.
Develop a custom Sketch-to-Image API for converting hand-drawn/digital sketches into photorealistic images using stable diffusion models powered by ControlNet.
Experts at Black Hat 2024 reveal how developers and security pros can collaborate better: from shifting left to embracing AI and prioritizing user experience.
The Confusion Matrix and the ROC Curve evaluate model performance in machine learning and data science. Compare and learn when to use each in model evaluation.