AI-powered
podcast player
Listen to all your favourite podcasts with AI-powered features
2min snip
Ben Goertzel: AGI is 5 Years Away!
Theories of Everything with Curt Jaimungal
Unifying AI Algorithms with Distributed Knowledge Metagraphs
The integration of neural, symbolic, and evolutionary methods involves creating a large, distributed knowledge metagraph, which goes beyond a traditional graph by allowing links that span multiple nodes and pulling the general subgraphs. This distributed knowledge metagraph represents neural nets, logic engines, evolutionary learning, and static knowledge. It is a self-modifying, self-rewriting, and self-evolving graph, with the initial state representing various types of knowledge that can be fed in from databases, language models, or pattern recognition. This unification is achieved through a common representation using Galois connections, which allows AI algorithms to be represented as fold and unfold operations over the metagraph.
00:00
Transcript
Episode notes
Get the Snipd
podcast app
Unlock the knowledge in podcasts with the podcast player of the future.
AI-powered
Discover
highlights
Listen to the best highlights from the podcasts you love and dive into the full episode
Save any
moment
Hear something you like? Tap your headphones to save it with AI-generated key takeaways
Share
& Export
Send highlights to Twitter, WhatsApp or export them to Notion, Readwise & more
AI-powered
podcast player
Listen to all your favourite podcasts with AI-powered features
Discover
highlights
Listen to the best highlights from the podcasts you love and dive into the full episode