The focus upon AI continues to be the predominant technology subject of the day; it’s the must-have feature of any new product or service; it’s at the forefront of many discussions about ethics, attribution and indeed our own future employment prospects.

But increasingly, the term “AI” has become synonymous with only one flavour of artificial intelligence - that being “machine learning” (ML) - e.g. generative AI, applied AI, large language models (LLMs) and the such.

However, there are many other types of AI, which until recently, were the mainstay algorithms found behind automated decision making solutions.

Many of these concepts can be found in the video games we know and love.

Are these other types of AI still relevant? Do they risk being drowned out, or forgotten, in the rush to embrace machine learning solutions?

In this session, intended for the enterprise/business application developer, we’ll open a window into the world of the video game development.

We’ll explore the type of algorithms that are a staple of game development: pathfinding, state machines, decision trees, and goal-oriented action planning.

We’ll delve into some of the performance considerations necessary to keep these algorithms running efficiently.

We’ll circle back to how the business application developer can use this type of AI in applications, and how the lessons learnt making video games can help us write better software.