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EP 20 | The Path to Safe AI - Education with Peter Norvig

In this episode of The AI Forecast, host Paul Muller speaks with Peter Norvig, an education fellow at Stanford and the co-author of Artificial Intelligence: A Modern Approach, the leading textbook for AI education. Peter explores the critical role of accessible, up-to-date AI education in building skilled practitioners, guiding policy, and fostering public understanding. Listen in as they explore concepts like "AI literacy" and unpack why continuous learning is essential to keep pace with technological change—and how it can help us build a more informed, ethical, and responsible AI future.

10 Agentic AI Examples (Use Cases) for Enterprises & How To Build Them

AI is no longer just a tool. It is now handling complex tasks with minimal human intervention and oversight. This transformative shift has given rise to agentic AI, where AI-powered systems make decisions, adapt to new information, and automate workflows across departments. From answering customer inquiries to managing financial data, these AI-driven agents are reshaping how businesses operate.

Agentic AI vs Generative AI: Understanding the Key Differences

You’ve probably interacted with AI more times than you can count—whether it’s getting a movie recommendation, using an AI-powered chatbot, or watching AI-generated content. But have you ever stopped to think about how these AI systems actually work? Not all AI is built the same way, and two key paradigms are emerging as game-changers: Agentic AI and Generative AI.

What are Agentic Workflows?

Organizations are moving beyond simple automation towards a future where systems are intelligent enough to tackle complex tasks with minimal human intervention. Agentic workflows are the driving force behind this shift. According to Gartner, a staggering 33% of enterprise software applications are projected to integrate agentic AI by 2028, enabling them to autonomously make decisions for as much as 15% of routine work.

Agencies Win With Data Streaming: Evolving Data Integration to Enable AI

With data streaming, public sector organizations can better leverage real-time data and modernize applications. Ultimately, that means improving the reliability of services that agencies and citizens depend on, enhancing operational efficiency (therefore cutting costs), and delivering critical insights the moment they’re needed.

How to Setup Observability for your MCP Server with Moesif

The Model Context Protocol (MCP) has taken the internet by storm by rapidly becoming the standard for Large Language Models (LLMs) to communicate with external data sources or tools. MCP provides a structured way to fetch data and trigger workflows through APIs and functions. However, with great power comes great responsibility.

What is an AI Voice Agent? A Comprehensive Guide

Voice is the most commonly used form of communication for humans, and it is also the most information-dense. Plus, for the first time in history, generative AI has made it programmable to the extent that an AI voice agent can hold conversations almost indistinguishable from humans. But what exactly are AI voice agents, how do they work, and how can enterprises build AI voice agents for their workflows? Learn all this and more in this blog!