AIAI Toronto, 2025

The development and deployment of advanced AI systems increasingly depend on flexible, robust orchestration layers that bridge diverse models, tools, and resources. IBM’s MCP Gateway addresses this need by providing a FastAPI-based gateway for the Model Context Protocol (MCP), offering a unified interface to scale and manage the modern AI toolchain. This article explores MCP…

As large language models (LLMs) evolve from simple text generators to agentic systems —able to plan, reason, and autonomously act—there is a significant increase in both their capabilities and associated risks. Enterprises are rapidly adopting agentic AI for automation, but this trend exposes organizations to new challenges: goal misalignment, prompt injection, unintended behaviors, data leakage,…

In this tutorial, we discover how exploration methods form clever decision-making via agent-based downside fixing. We construct and prepare three brokers, Q-Learning with epsilon-greedy exploration, Upper Confidence Bound (UCB), and Monte Carlo Tree Search (MCTS), to navigate a grid world and attain a aim effectively whereas avoiding obstacles. Also, we experiment with alternative ways of…

Table of contents Why WER Isn’t Enough ? What to Measure (and How) ? Benchmark Landscape: What Each Covers Filling the Gaps: What You Still Need to Add A Concrete, Reproducible Evaluation Plan References Optimizing just for Automatic Speech Recognition (ASR) and Word Error Rate (WER) is inadequate for contemporary, interactive voice brokers. Robust analysis…