AI Foundations
Explore foundational concepts, tools, and evaluation methods that support the effective development and deployment of AI in business settings. This section helps organizations understand how to build reliable AI systems, measure their performance, address ethical and operational risks, and select appropriate infrastructure. It also provides practical benchmarks and comparisons to guide technology choices and improve AI outcomes across use cases.
AI Explained: Trends and Applications by Industry in 2026
Artificial Intelligence (AI) allows computers to learn from experience, adapt to new inputs and perform human-like tasks. Most of the AI examples you’ve heard about –from chess-playing machines to self-driving cars–rely heavily on deep learning, a subfield of AI.
Lazarus AI: Extractive & On-Prem AI for Regulated Industries
Generating insights from unstructured data has long been a strategic aim among organizations that Lazarus AI builds foundation models (e.g. RikAI) to solve complex and urgent problems involving large amounts of unstructured private data. Lazarus is active in these industries: Government (e.g. defense), insurance (e.g. damage assessment of catastrophic events), healthcare, and banking.
Image Recognition vs Classification: Applications with Examples
Businesses increasingly leverage AI-powered visual data solutions, but confusion between image recognition and classification leads to inefficiencies. Understanding the key differences helps businesses optimize AI deployment in the security, healthcare, and retail fields. Explore image recognition vs classification, their key differences, and applications with real-life examples.