Topic

AI

A collection of 7 issues

Accumulating Thoughts

On average we have about 6000 thoughts everyday. What if we could record, track and classify all those thoughts. And feed it into a giant neural network to make a virtual version of yourself. Writing, speaking, drawing, tweets, vlogs and all other forms of “content” we create are

Dunning-Kruger Effect

The Dunning-Kruger Effect is a bias where people think that they are smarter than they actually are. A person with low ability is more likely to overestimate themselves. This is due to their lack of perception of the task at hand and lack of previous experience. Both leading them to

Sparsely Activated Network

A deep learning network contains multiple learning nodes separated as layers and interconnected both within and across different layers to create a network. Typically deep learning models are trained by activating all nodes for each training input. Another way to train the network is to sparsely activate the network for

Freudian Slip

A Freudian slip is an error that occurs due to an internal train of thought. It is said that this happens due to the interference of the unconscious. It is characterized as a slip because it is an indication of what you are thinking behind the scenes. Sometimes these slips

Context and AI

AI and ML techniques have made big leaps this year. With AlphaFold solving the protein folding problem to the GPT3 engine that can solve most text related problems using its language model. Computer vision techniques have improved as well. All these research has some drivers behind it. And usually these

Protein Folding

Protein exists as a polypeptide chain consisting of amino acids linked by a peptide bond. These chains can be in random shapes. But what makes them biologically functional is the shape it takes up when they are acted upon by a ribosome. Ribosomes are found in all living cells and

Federated Learning

Federated Learning is a machine learning technique that trains algorithms with separate local samples and without exchanging them. This enables training of an algorithm using multiple devices. This is a huge plus from a data privacy and data security point of view. The basic principle is that the algorithm is