4 Apr
2018

McKinsey - An executive’s guide to AI

McKinsey publised an online executive's guide to AI to cover the highlights of artificial intelligence: machine learning and deep learning.

Artificial Intelligence
McKinsey - An executive’s guide to AI

McKinsey publised an online executive's guide to AI to cover the highlights of artificial intelligence.

The article starts with a brief definition of AI:

"AI is typically defined as the ability of a machine to perform cognitive functions we associate with human minds, such as perceiving, reasoning, learning, interacting with the environment, problem solving, and even exercising creativity. "

The guide continues with Why AI now?, a interactive timeline which presents the first technologies and innovations that led to AI.

The guide goes on with machine learning and the various type and some business use cases:

Supervised learning

 

Supervised_learning

 

Unsupervised learning

Unsupervised_Leanring

 

Reinforcement learning

 

Reinforcement_Learning

The guide ends on the subject of Deep Learning, defining it as:

"Deep learning is a type of machine learning that can process a wider range of data resources, requires less data preprocessing by humans, and can often produce more accurate results than traditional machine-learning approaches (although it requires a larger amount of data to do so.)"

They present 2 majors models of deep learning and some business use cases:

Convolutional neural network

 

Convolutional neural network

 

Recurrent neural network.

 

Recurrent_Neural_Network

SOURCE AND TO READ THE FULL ARTICLE : https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/an-executives-guide-to-ai

Want to learn more?
Download the ebook
Related blog articles

Related articles

Back to the blog
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
20
Feb 2018

Worximity fera partie de la super grappe Scale AI

French
20
Feb 2018

Worximity will be part of the Supercluster Scale AI

English
5
Feb 2019

Un Montréal à saveur d'intelligence artificielle

French

Related articles

Back to the blog
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
30
May 2018

4 Main Challenges of IIoT Adoption and What Can Be Done About Them

According to Statista the global manufacturing industry is set to spend over $890 billion for IoT technologies by 2020. However, despite this huge growth in the applications of said technologies, there are still challenges that prevent their adoption on a mass scale.

English
22
Nov 2019

How CFOs Can Increase EBITDA using IIoT

Are you a CFO interested in understanding how you can extract the most economic value from your investments in machinery assets?

English
12
Jul 2018

Why you should monitor giveaway in real time your factory

Giveaway and overproduction are one of the major processing wastes and can be very costly if left unaccounted for. Have you considered monitoring giveaway in your factory?

English