ChatGPT is the brand new artificial intelligence based language model developed by OpenAI. Essentially, ChatGPT is an AI-powered chatbot that can answer any question. It includes complex subjects, such as physics, mathematics and computer development.
One of the trickiest obstacles in machine learning is overfitting. A Machine Learning model must be able to generalize, that is, it must be able to take new observations and predict with some accuracy the associated target variable.
Voice assistants Alexa, Google Home and Siri are all based on automatic language processing technologies. Objective: to have the ability to understand, process and generate voice messages.
The random forest is a machine learning algorithm designed to obtain a reliable prediction thanks to a system of random subspaces.
Inference is a logical operation based on induction. Inference in machine learning and deep learning aims to make efficient predictions from a trained learning model.
TensorFlow is an open source deep learning platform created by Google. Equipped with a Python API, it offers a multitude of tools to train and optimize artificial neural networks.
Written in Python, Keras is an artificial neural network rapid prototyping interface. It is based on the deep learning libraries Tensorflow, Microsoft Cognitive Toolkit, PlaidML and Theano.
Machine learning, or automatic learning, is the main technique of AI. It consists of training algorithms from a learning base to enable them to make predictions or automate tasks.
Transformer type, the large language model has no less than 175 billion parameters. Which makes it an AI capable of covering questions and answers, translation, generation of text or application code.
The open source project orchestrated by INRIA has become a reference machine learning infrastructure alongside deep learning frameworks such as Keras, Pytorch or Tensorflow.