AIAI New York, 2025
Catch up on every session from the AIAI New York with sessions across 3 co-located summit featuring the likes of Meta, Bank of America, Google DeepMind and many more.
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The rise of agentic artificial intelligence
The rise of agentic AI fuels AI in ways traditional AI can’t. The scope of AI is plentiful, but there’s a small subsection of tasks Agentic AI is just better at, thanks to its increased levels of autonomy. With the improvement in capability comes a fresh look at how to manage such a tool within…
Explainability and transparency in autonomous agents
As AI agents achieve autonomy, the necessity for explainability and transparency has by no means been extra pressing. In a current panel dialogue, 4 AI consultants (Keshavan Seshadri, Senior Machine Learning Engineer at Prudential Financial; Pankaj Agrawal, Staff Software Engineer at LinkedIn; Dan Chernoff, Data Scientist at Parallaxis; and Saradha Nagarajan, Senior Data Engineer at…
How to Build an Intelligent AI Desktop Automation Agent with Natural Language Commands and Interactive Simulation?
In this tutorial, we stroll by the method of constructing an superior AI desktop automation agent that runs seamlessly in Google Colab. We design it to interpret pure language instructions, simulate desktop duties similar to file operations, browser actions, and workflows, and present interactive suggestions by a digital setting. By combining NLP, job execution, and…
Google AI Ships a Model Context Protocol (MCP) Server for Data Commons, Giving AI Agents First-Class Access to Public Stats
Google launched a Model Context Protocol (MCP) server for Data Commons, exposing the undertaking’s interconnected public datasets—census, well being, local weather, economics—via a standards-based interface that agentic methods can question in pure language. The Data Commons MCP Server is out there now with quickstarts for Gemini CLI and Google’s Agent Development Kit (ADK). What was…
