Deep Learning

Digital advertising continues to evolve at a rapid pace, driven by technological advances, changing consumer behaviors, and shifting privacy regulations. We recently sat down with Jaysen Gillespie, Vice President of Global Product Commercialization at RTB House, to discuss IntentGPT, one of our most significant recent innovations. Gillespie has been instrumental in leading the development and commercial rollout of this technology, which represents a fundamental shift in how advertisers can understand and act on user intent across the web.

Artificial intelligence (AI) tools are productivity game changers, but not every AI is suited for every type of task. Some excel at writing copy, others can generate incredible images, and some can help researchers predict the weather. Understanding different types of AI is the key to successfully implementing AI into your workflow. This article will dive into the differences between two of the most commonly used types of AI: Generative AI vs. Predictive AI.

Generative AI applications are reshaping how organizations tackle marketing, product innovation, and user engagement. From generating new content to analyzing complex datasets, these advanced systems reduce repetitive tasks and unlock fresh perspectives. In this article, we explore key Generative AI examples and outline practical steps to deploy GenAI applications in different sectors, including marketing, healthcare, and finance.

At present, the narrative surrounding AI is a strange cocktail of both dark prophecies and unbridled optimism. However, between these extremes is a growing number of people taking advantage of new Generative AI tools to eliminate dull repetitive tasks, improve their productivity, and ultimately focus more on strategic and creative work.

When used correctly, this growing toolkit of AI-powered products makes it possible for marketers to concentrate on what they do best and outsource repetitive or time-consuming tasks to AI.

Let’s take a look at some of the top Generative AI tools for marketers and how you can implement them in your own workflow.

Generative artificial intelligence has sparked emotions of hope, fear, and a little skepticism. The technology is able to take over a wide range of tasks previously seen as the domain of skilled professionals, and many feel that they need to adopt generative AI tools or be left behind. However, no technology is a silver bullet, and in order to properly utilize its potential, we need to understand what generative AI is and how it should be implemented into your workflow.

The food and beverage industry has always been incredibly competitive. After all, food is important to all of us. It’s not just a necessary source of nutrients, protein, and fiber; it’s inextricably linked with culture, community, family, and friends. It brings comfort, togetherness, even bliss. It’s the way to our hearts.

But in recent years, the competition in food & beverage has reached a boiling point. There’s been a feeding frenzy as a horde of new players has entered the fray. Between any brand and a customer’s table lies a crowded, fiercely competitive marketplace. The advent of food apps and a growing consumer expectation of convenience has further heightened the competition. The latest digital technology provides unprecedented convenience for the consumer and a widening plethora of choices.