4min chapter

Machine Learning Street Talk (MLST) cover image

#54 Gary Marcus and Luis Lamb - Neurosymbolic models

Machine Learning Street Talk (MLST)

CHAPTER

The Challenge of Building Deep Learning Approaches

The hardness of building deep learning approaches that are very good at relational reasoning in the logical sense is akin to the challenge of building language interpretation. We have better tools coming from the logic world, from the logic in computer science school. So what we do in neuro symbolic AI or neuro symbolic computing is not to throw all the data at the same point and feed a huge neural network with an even larger amount of data. What we do is we do some pre-processing, we provide knowledge representation tools to proper design a learning system where symbolic structure, discrete structures are first learned by this machine learning mechanism. And then you verify then you do your cross validation, then you use your statistical approach to validate

00:00

Get the Snipd
podcast app

Unlock the knowledge in podcasts with the podcast player of the future.
App store bannerPlay store banner

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

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