⏩ The Forward-Forward Algorithm

🧠 A revolutionary new idea for training neural networks

Hello,

In this issue, I want to try something slightly different. There are so many scientific developments going on out there and they are the oxygen for technological innovation.

So I thought, why not bring them into the hi, tech. fold?

🥳️ And nothing screams “Friday!!” like a deep-dive into a dense scientific paper, eh?

Today, we will be discussing a new breakthrough in the field of artificial intelligence: the Forward-Forward (FF) algorithm.

It arrived in a paper last month (read it here), released by none other than Geoffrey Hinton. At 75 years old, Hinton is still a central figure in AI and when he announces a potential “breakthrough”, we take notice.

I took a read to see what all the fuss is about and I will now (wish me luck) provide YOU with all the juicy details.

The quick summary:

• Geoffrey Hinton, a leading researcher in artificial intelligence, has released a new paper detailing a potential breakthrough in the field: the Forward-Forward (FF) algorithm.

• The FF algorithm is an alternative to backpropagation, which is widely used but has limitations.

• FF uses less energy and can learn in real time without stopping to perform backpropagation.

• It is suitable for use with unknown non-linearities.

• While it is not as fast as backpropagation, it may be useful in situations where the forward computation is unknown or power is an issue.

Allow me to explain.