Intro to Machine Learning (ML Zero to Hero, part 1)

Machine Learning represents a new paradigm in programming, where instead of programming explicit rules in a language such as Java or C++, you build a system which is trained on data to infer the rules itself. But what does ML actually look like? In part one of Machine Learning Zero to Hero, AI Advocate Laurence Moroney walks through a basic “Hello World” example of building an ML model, introducing ideas which we’ll apply in later episodes to a more interesting problem: computer vision.

Artificial Intelligence in Marketing

Artificial intelligence (AI) has proven to be useful in many applications from automating cars to providing customer service responses. However, though many firms want to take advantage of AI to improve marketing, they lack a process by which to execute a Marketing AI project. This article discusses the use of AI to provide support for marketing decisions. Based on the established Cross-Industry Standard Process for Data Mining (CRISP-DM) framework, it creates a process for managers to use when executing a Marketing AI project and discusses issues that might arise. It explores how this framework was used to develop three cutting-edge Marketing AI applications.

Supervised Learning: Crash Course AI #2

This presentation teaches John Green Bot how to tell the difference between donuts and bagels using supervised learning.

Supervised learning is the process of learning with training labels, and is the most widely used kind of learning when it comes to AI. It helps with tagging photos on Facebook and filtering spam from your email. We’re going to start small today and show how just a single neuron (or perceptron) is constructed, and explain the differences between precision and recall. Next week, we’ll build our first neural network.

Deepfakes: Is This Video Even Real? | NYT Opinion

“Deepfakes” are seemingly realistic videos generated by artificial intelligence. First seen on Reddit with pornographic videos doctored to feature the faces of female celebrities, deepfakes were made popular in 2018 by a fake public service announcement featuring former President Barack Obama. Words and faces can now be almost seamlessly superimposed.

The result: We can no longer trust our eyes.

In June, the House Intelligence Committee convened a hearing on the threat deepfakes pose to national security. And platforms like Facebook, YouTube and Twitter are contemplating whether, and how, to address this new disinformation format.

It’s a conversation gaining urgency in the lead-up to the 2020 election.

Yet deepfakes are no more scary than their predecessors, “shallowfakes,” which use far more accessible editing tools to slow down, speed up, omit or otherwise manipulate context.

The real danger of fakes — deep or shallow — is that their very existence creates a world in which almost everything can be dismissed as false.

Adobe Advertising Cloud: Where programmatic meets media. All media.

Adobe Advertising Cloud is the only independent ad platform that unifies and automates all media, screens, data and creativity at scale. Create meaningful ad experiences that resonate with your audience, deliver data-driven TV advertising, manage all your media strategies across digital and TV and utilize AI and data to turn search marketing from a best guess, to a winning strategy.