“Embeddings” emphasizes the notion of representing data in a meaningful and structured way, while “[[Vectors]]” refers to the numerical representation itself. ‘Vector embeddings’ is a way to represent...

Conceptually, for two vectors x and y, x.y is defined as magnitude of a multiplied by projection of y onto x (think of it as shadow cast by...

Vectors have two properties 1. Magnitude (length), 2. Direction. From a computer science perspective, it’s just an ordered list of numbers Vectors can be added, multiplied (=scaled) A...

Layers = groups of perceptrons (See [[Perceptron]]) stacked so that each layer’s outputs become the next layer’s inputs, letting the network learn increasingly abstract features. Stacked/layered perceptrons create...

Perceptron = the simplest artificial neuron that takes multiple inputs, multiplies them by weights, adds a bias, and turns the result into a yes/no (or score) output. Inputs:...

Alright, OpenAI o1 is out. If you are anything like me, you first chuckled at the description that it was “designed to spend more time thinking before they...

Large Language Models (LLMs) like ChatGPT can handle two aspects of communication very well: plausibility and fluency. Given an input context they determine what are the most probable...

A few months ago my curiosity around how-are-LLMs-‘learning’ took me down the rabbit hole of AI and Psychology history and I ended up finding a string of very...

The first 10 minutes of this Stanford CS224N lecture explained NLU, NLG and the tasks within and it was helpful. Natural Language Understanding (NLU) is a subset of NLP...

This seemed like the core ideas so I wanted to clarify them conceptually. “Embeddings” emphasizes the notion of representing data in a meaningful and structured way, while “vectors”...

I recently heard Jeff Bezos briefly talk about his views on LLMs here. Less than a minute into the conversation, he said something that struck a chord with...