What’s the Difference Between AI, ML, Deep Learning, and Active Learning? Posted on : Oct 07 - 2019

Today, the terms artificial intelligence (AI) and machine learning (ML) are often used interchangeably. While the terms are related, they mean different things. We map out how they all relate to one another, so your team can find the best candidates, best approaches and best frameworks as you embark upon your AI journey.

AI refers to the concept of machines mimicking human cognition. To reference artificial intelligence is to allude to machines performing tasks that only seemed plausible with human thinking and logic.

In the real world, one of the most ubiquitous forms of AI might manifest themselves in the form of conversational AI. Conversation AI may include multimodal inputs (e.g. voice, facial recognition) with multimodal outputs (e.g image, synthesized voice). All of these modalities can be considered part of AI, as well as the integration of these modalities.

You may already be familiar with some of these modalities. Starbucks enhanced its mobile app by enabling ordering ahead via voice commands, and Staples’ Easy System allows customers to order with voice commands.

Machine Learning Algorithms Create AI

Machine learning, deep learning, and active learning, on the other hand, are approaches used to implement AI. If AI is when a computer can carry out a set of tasks based on instruction, ML is a machine’s ability to ingest, parse, and learn from that data itself in order to become more accurate or precise about accomplishing that task. View More