Parth, the digital nerd, dances between the realms of Android and iPhone like a tech-savvy tango. With a keyboard as his compass, he navigates the binary seas, uncovering hidden gems and unraveling ...

In the previous chapter, we learned various strategies to guide AI models 'down the mountain' (optimization algorithms), such as SGD and Adam. The core of these strategies relies on a key piece of ...

Neural networks are computing systems designed to mimic both the structure and function of the human brain. Caltech researchers have been developing a neural network made out of strands of DNA instead ...

An MIT spinoff co-founded by robotics luminary Daniela Rus aims to build general-purpose AI systems powered by a relatively new type of AI model called a liquid neural network. The spinoff, aptly ...

Partnership with MBPJ tackles congestion, safety and urban planning CelcomDigi becomes Malaysia’s first telco to deliver ...

An organoid-based screening platform that allows one-gene-at-a-time knockdown across a whole tissue has been used to identify the genes that regulate closure of the neural tube in humans.

A team of astronomers led by Michael Janssen (Radboud University, The Netherlands) has trained a neural network with millions of synthetic black hole data sets. Based on the network and data from the ...

This one is a bit more symbol heavy, and that's actually the point. The goal here is to represent in somewhat more formal terms the intuition for how backpropagation works in part 3 of the series, ...