an AI that is able to do multiple things (FIXME-anthropic defs)
algorithm
a set of instructions to complete a task; a recipe
anonymous function
a function that’s defined on the fly, typically to lighten syntax or return a function within a function. In python, they’re defined with the lambda keyword.
a group of samples that is similar by some definition
clustering
a type of unsupervised learning that finds groups or clusters among the samples
compute
apply a series of mathematical operations to an input
deep learning
a type of machine learning that consists of creating large numbers of hidden layers of artificial neurons
discriminative model
a type of statistical model that describes the decision boundary to make a prediction
feature
in machine learning, one input to the prediction algorithm, typically of many, stored together in a feature vector
generative model
a type of statistical model that describes the way that the underlying data is distributed with sufficient detail to be able to sample new data that is in the same distribution as the original data; often in
generative pretrained transformer
It is a transformer model that takes in tokens and can be sampled from to to produce novel token sequences that are similar to its training data
a vocabulary and a grammar for how to combine the words in order to convey meaning
large language model
a probability distribution that describes the structure of sequences of tokens and enables next token prediction as well as serves as a mathematical description of tokens using many parameters
learning algorithm
an algorithm for finding patterns in data
a paramter optimization or parameter fitting algorithm
machine learning
a sub field of AI; emphasizes the use of data to learn relationships, studies the algorithms that find patterns in data
model
a simplification of some part of the world
model class
a generic mathematical model that can be fit to a specific part of the world by setting parameter values
neural network
a set of artificial neurons where the outputs of some are the inputs to the others, serving to “connect” them as a set, or network; often described as layers where connections are from one layer to the next.
neural network architecture
the general structure of how a neural network is set up, not the specific weights, but the size of the layers, number of layers, types of layers for example
number
a mathematical object used to count, measure and label
number system
a cultural artifact that describes the symbols used to represent quantities and how to interpret them as numbers
parameter
(general programming) all inputs to a function
(in ML) the values that transform a generic function into a specific function
place based
a type of number system where the position or place of the symbol changes its meaning. So in 1, 10, and 100, the symbol 1 represents different values because of its position.
predictive model
a mathemtical model, typically implemented in computer code, that predicts a label for an input or an outcome based on past
probability distribution
a function that takes an event (or value) as input and returns the likelihood of that even occuring
production
a state of a system where it is in use by users unaffiliated with the developers and generally unrestricted (except for possibly payment)
a human readable language that can be processed by computers and translated (either live through an interpreter or in batch through a compiler) to machine instructions that the physical computer can execute
machine representation
a description of an object that can be stored in a computer
a state of a system where is has been built and evaluated, but not deployed to general users, instead is only available to the team that built it and (potentially) other authorized users
a process to produce text that is grounded in content from specific resources in order to improve the factual correctness of the text or augment with specific data that was not available to a base model at the time of traning
commonly used to “chat with” a document or to prevent false statements
sandbox
a state of a system where is is available to test, but is not officially deployed, may have simulated data instead of real data or be isolated from external systems
statistical model
a type of mathematical model that describes its object of inquiry using probability distributions
supervised learning
a type of machine learning that requires both features and target variables at time of training
machine learning with labeled examples
target
the variable to be predicted in a machine learning problem setup, the dependent variable
the output of a prediction algorithm
also called the dependent variable or label
test accuracy
percentage of predictions that the model predict correctly, based on held-out (previously unseen) test data
test data
data that was not used in training that is instead used to evaluate the perforance of a model
token
the basic units used in computational processing of texts from human spoken (not programming) languages
a part of a word or a word, approximately like prefix, base, suffix parts, in general 1000 tokens is about 750 words