Deep learning

And he's also the director of knowledge exchange for the Bath Institute for Mathematical Innovation.

And we have worked closely with Chris over the last few years as he is the principal investigator of the Maths for Deep Learning research project, Maths for DL.

And excitingly, Chris has just been awarded a prestigious gold medal from the Institute of Mathematics and its applications.

Congratulations, Chris.

When the computer itself came out, people were saying, oh, that's the end of mathematicians, you know, back in the 1960s.

but now come on computers are opening up the whole new world for us so uh i i don't see that at all i think i think um what ai is doing is it's bringing maths more and more and more into people's lives and we need mathematicians more and more to be able to address the problems that ai itself poses i mean let me give you an example if i train an ai system How do I know that the training data hasn't led to a completely wrong solution? And that's a mathematical question.

And that's the kind of stuff that your group, Maths for Deep Learning, works on, isn't it? That's precisely what we work

on, these mathematical questions that are thrown up by AI.

We really do.

We're using this incredibly expansive, just meticulous text, Deep Learning for Finance.

It's a 2024 book by Sofian Kabar.

It's extremely comprehensive.

Like one guy includes the wick of a candlestick and the other just uses the body.

True.

So why in the world does a meticulous book about math-driven deep learning dedicate space to subjective human charting?

It's a fair question.

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And with that, the modern AI boom had officially started.

But the question has to be asked, how are neural nets being used in music generation? Well, in 2016, Google's Project Magenta turned a few heads when they released an AI-generated piano piece made by Deep Learning Algorithms.

Ultimately, the next big step was to generate music just based on a simple text query in natural human language.

Google's Music LM did just that, and honestly, it was impressive for the time, but far from perfect.

You may not have heard his name before, but you almost certainly encountered his ideas.

He works extensively with certain areas of machine learning and co-wrote a seminal book on the concept of deep learning, a subfield of machine learning focused on algorithms inspired by the structure and function of the brain called artificial neural networks.

In his book, which of course is called Deep Learning, Goodfellow explains it this way.

Hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones.

If we draw a graph showing how these concepts are built on top of each other, the graph is deep with many layers.

And for this reason, we call this approach to AI deep learning.

In plain English, this means we can have programs that work more and more like an old-school organic brain.

Goodfellow's most well-known invention is something called a generative adversarial network, or the GAN.

University of California, Santa Barbara is the source.

Headline, "Deep Learning," of course, this is AI related, "Refines How Bionic Eyes Communicate With The Brain." Very geeky, but very interesting.

Check that one out.

Our next honorable mention is from fastcompany.com.

So we've been having this s-s-sort of, to some degree, conceptual conversation about, about the nature of intelligence and whether concepts like wholly general intelligence really make sense.

Um, there's also a conversation here which I suppose is connected in some ways, but also feels a little bit different, which concerns the specific kind of paradigm in AI at the moment, which is deep learning.

For a long time, you expressed skepticism about what was sometimes called connectionism as an approach to understanding both the mind and as an approach to artificial intelligence.

Do you think that the progress that's been made in deep learning over the past several years, do you think of that as putting pressure on that early skepticism that you expressed concerning connectionism, or do you think it's potentially consistent with the kinds of views and arguments that you outlined in books like How the Mind Works and The Blank Slate?

You know, it absolutely does put pressure on it.

It has forced me to update.