DeepMind wants to reconcile Deep Learning and classical computer science algorithms with Neural Algorithmic Reasoning. Featuring DeepMind's Petar Veličković and Charles Blundell, MILA's Andreea Deac artwork
Orchestrate all the Things podcast: Connecting the Dots with George Anadiotis

DeepMind wants to reconcile Deep Learning and classical computer science algorithms with Neural Algorithmic Reasoning. Featuring DeepMind's Petar Veličković and Charles Blundell, MILA's Andreea Deac

  • S2E28
  • 58:14
  • September 10th 2021

Will Deep Learning really be able to do everything? We don't really know. 

But if it's going to, it will have to assimilate how classical computer science algorithms work. This is what DeepMind is working on, and its success is important to the eventual uptake of neural networks in wider commercial applications.

This work goes by the name of Neural Algorithmic Reasoning. Join us as we discuss roots and first principles, the defining characteristics, similarities and differences of algorithms and Deep Learning models with the people who came up with this. 

We also cover the details of how Neural Algorithmic Reasoning works, as well as future directions and applications in areas such as path finding for Google Maps

Could this be the one algorithm to rule them all?

Article published on VentureBeat.

Image: Getty

Orchestrate all the Things podcast: Connecting the Dots with George Anadiotis

I've got tech, data, and media, and i'm not afraid to use them.

My name is George Anadiotis, and i am a writer, a planner and a doer. I am an Onalytica Top 100 Influencer in Big Data and Cloud, a Knowledge Graph expert, and a P2P Foundation and ZDNet contributor, among other things.

Linked Data Orchestration is my brand. This podcast is where i share my work, as well as conversations with people who bring interesting news and views to the table.

Some might call this futurism; let's just say it's connecting the dots.

Coming from a technology background, i've had the chance to learn to play many instruments on the way to becoming a one man band and an orchestrator.

Before starting a career as an analyst and journalist, i served Fortune 500, startups and NGOs as a consultant, built and managed projects, products and teams of all sizes and shapes, and got involved in award-winning research. I still try to do that stuff as much as possible.