#Martin Keen

CAG vs. Long Context: AI's Memory Explained

IBM's Martin Keen explains how AI models use Long Context and Cache Augmented Generation (CAG) to process information, highlighting the trade-offs and efficiency gains of each approach.

The 4 Types of AI Agent Memory Explained

IBM Master Inventor Martin Keen details the four essential memory types AI agents need: working, semantic, procedural, and episodic.

Predictive vs. Generative AI: Key Differences Explained

IBM's Martin Keen clarifies the distinction between predictive AI (forecasting outcomes) and generative AI (creating new content), outlining their core mechanics and use cases.

IBM Master Inventor on AI's Contextual Bottleneck

IBM Master Inventor Martin Keen discusses how context is the key bottleneck for AI models, outlining four pillars of context engineering: connected access, knowledge layer, precision retrieval, and runtime governance.

Open Source AI: Boon or Bane for Security?

IBM's Martin Keen and Gabe Goodhart discuss the security implications of open-source AI, balancing innovation with risk.

AI Agents Need Skills: Martin Keen on LLM Tooling

Martin Keen of IBM explains how AI agent skills, defined in structured files, are essential for LLMs to perform tasks, detailing the "skill file" format and different knowledge types.

IBM's Martin Keen on Physical AI Training

IBM Master Inventor Martin Keen discusses the advancement of Physical AI, focusing on how robotic agents learn through simulation and real-world data, and the role of compute efficiency.

IBM Master Inventor Explains Multimodal AI

IBM Master Inventor Martin Keen explains the evolution of multimodal AI, contrasting feature-level fusion with native multimodality and the importance of temporal reasoning for video.

IBM's Martin Keen on AI Human-in-the-Loop Spectrum

IBM's Martin Keen explains the human-in-the-loop spectrum for AI, detailing how human involvement is crucial in training, tuning, and inference stages.

IBM's Martin Keen on Hierarchical AI Agents

IBM's Martin Keen explains why hierarchical AI agents are superior to monolithic ones for complex tasks, detailing the benefits and challenges.

IBM's Martin Keen on LLM Context Windows

IBM's Martin Keen explains how larger context windows in LLMs simplify deployments and improve reasoning by reducing reliance on complex RAG systems.

IBM Master Inventor Martin Keen on Agentic Storage

IBM Master Inventor Martin Keen explains 'Agentic Storage,' detailing how AI agents interact with diverse storage systems and the critical safety layers needed for responsible operation.

IBM Experts Unpack AI's Evolution and Cybersecurity's Enduring Challenges

IBM Master Inventor Demystifies Key AI Concepts Shaping the Future

AI Agents: Precision, Not Hallucination, in Anomaly Resolution

AI Agents and Mixture of Experts: Distinct Architectures for Frontier AI

Beyond Prompts: The Rise of Context Engineering in Smarter AI Systems

AI Agents Transform Cybersecurity: A New Era of Defense

Multi-Agent Pipelines Elevate AI Narrative Design Beyond LLM Limits

AI Agents: Autonomous Intelligence Reshaping Enterprise Operations

The Unseen Tide: Decoding and Defeating AI Slop

Grounding AI: IBM Experts on Mitigating Hallucinations

Learn how RAG, Chain of Thought, and model selection can create more reliable and trustworthy AI.