AI is evolving from models to systems to agents—autonomous entities that act, adapt, and collaborate. As intelligence emerges from interactions, the future of AI depends on context, trust, and workflow integration. How we design social AI today will shape its role in amplifying human intelligence.
A lecture by Michael Levin, distinguished professor of biology at Tufts University and associate at Harvard's Wyss Institute
Preparatory material for our workshop on using generative AI for decision-making, generated by NotebookLM.
ChatGPT Will Never Work Like the Demo, AGI is a Red Herring, The Brittleness of Agentic Reasoning and Planning Using LLMs, Can LLMs Reason and Plan, How to Use Generative AI to Create, and more!
The current obsession with AGI, fueled by the hype from companies like OpenAI, is a dangerous distraction we must firmly reject. Don't fall for the red herring argument that we need superintelligent AI to save us from ourselves. It's an insult to human intelligence and agency.
Research suggests that LLMs are not demonstrating genuine reasoning abilities but are instead relying on pattern matching and retrieval based on the provided examples. We're still a ways off reliable performance of LLMs in reasoning and decision-making tasks.
LLMs are great at coming up with approximate knowledge and ideas for potential plans. But to actually use those ideas, you need to pair the LLM with external programs that can rigorously check the plans for errors. The key is to use them as part of a bigger system.
Create by mixing modes, varying both inputs and outputs, and perspectives. Part 6 in our How to Use Generative AI series.
The Agentic AI Reoport, Graph RAG, Inside Anthropic's Claude, The Agentic Web, Karaitiana Taiuru and Indigenous AI, Weaving with Generative AI, and more!
Recent developments in AI have given rise to a new class of systems known as agentic AI. These systems are characterized by their ability to perceive, reason, and act with varying levels of complexity, extending human capabilities in unprecedented ways.
Artificial intelligence will never understand why I found it important to write this piece today. Why and how I hope I can connect with readers through it. Because only you, my fellow humans, can have similar experiences.
Graph RAG doesn't necessarily replace knowledge graphs but can serve as a complementary tool, especially in scenarios where rapid, scalable, and dynamic summarization of large unstructured datasets is required.
This research from Anthropic on the inner workings of Claude constitutes a major milestone in AI interpretability. It's a first glimpse into the mind of an alien intelligence, one that we've created but are only beginning to understand.
An interview with Māori Data Sovereignty expert, Karaitiana Taiuru about indigenous peoples and AI.
Weave by Levering the Technology's Combinatorial Power. Part 5 in our How to Use Generative AI series.
Writing and Conversations About AI (Not Written by AI)
