#### Auto-regression & diffusion: concepts, differences

Resources: Why Does Diffusion Work Better than Auto-Regression?

#### Tensors

arrays of scalars

#### Chain rule (calculus)

$dy/dx=dy/du∗du/dx$

Intuitively, the chain rule states that knowing the instantaneous rate of change of z relative to y and that of y relative to x allows one to calculate the instantaneous rate of change of z relative to x as the product of the two rates of change.

As put by George F. Simmons: “If a car travels twice as fast as a bicycle and the bicycle is four times as fast as a walking man, then the car travels 2 × 4 = 8 times as fast as the man.”

#### Neuron

#### Multi-Layer Perceptron (MLP)

#### Underscores in Python (`_`

and `__`

): Instance

In Python, `__self__`

is used to refer to the current instance of the class within instance methods. It is explicitly passed as the first parameter to instance methods.

Resources:

#### Weights of a Neural Network

Weights are not inputted data. Leaf nodes that will affect the loss function. Get iterated using the gradient information.

Need more.

#### Biases in the context of a Neural Network

So, weights and biases are...

Here will be the content.

#### Cost Function

#### Computation Graph

(mentioned in autograd)

Resources:

Sample computation graph

#### Semantic Search

#### Vector Embeddings

A bunch of numbers capturing the essence of our texts. Numerical representations (basically vector representations!) of our texts to map different data types to points in a multidimensional space, with similar data points positioned near each other. These representations assist machines to understand and process our data more effectively.