What lessons can Legacy Games teach us about Building for CertAInty?

“Gotta catch ‘em all Pokémon?”

Super Mario, Road Rash, Super Contra, Mortal Kombat, Pokémon…

Close your eyes and you're instantly transported back in time to those long after-school afternoons playing arcade games… friends in tow, intense strategies, fervent discussions.

For many, a lot of these legacy arcade games framed the introduction to the exciting world of Tech, IT and AI. But apart from the nostalgia and pixel art aesthetic, these games often paralleled simpler versions of later complex interactions between ‘players’, towards’ strategies’ and ‘payoffs’ at the simplest levels, which would later model open-ended multi-player online role-playing games. While the history of complex strategy games dates far before our computer era to ancient times, we’ve seen how games and game theory have shaped artificial intelligence (and the human intelligence behind it :) in the life and times of Generative Adversarial Networks (GANS), AI agents and more. 

How does this trail back to Tiger? 

If you’ve been following our newsletter (the 200,000+ of you), our anniversary issue touched upon the ‘what’ we do, the ‘why’ we do, and this edition talks about the ‘how’ we do it.  In identifying the right problems to solve, questioning possibilities, and getting to the bottom of our clients’ world – we’re relentlessly seeking, solving, challenging, and growing. This is how we build for certAInty.

In this newest edition of AI of the Tiger, we’re taking the scenic route into exploring beloved retro games and game theory. We examine if and how these elements - when applied not just to computational models and multi-agent systems but to: systems thinking, real-world interactions, and the way we work - can teach us to navigate uncertainty a little bit better. We walk through the nostalgia, the graphics and the gameplay, learning how to play the game better.

Lessons from Super Mario: Level Up Gradually -  Build for Progress, Not Perfection

There’s always a balance between building quickly and building well. How do you navigate these two? Let’s pick up analogy of games like Super Mario for example Their iterative gameplay has simpler early levels and introduces easy mechanics (jump, walk, avoid). As you advance, the levels get harder, but the player has had time to internalize the controls and strategy. We can’t talk about iterative development without Agile - our blogs ‘Choosing the Right Agile Framework’ and ‘Leveraging an Agile Mindset to Help Drive Value’ cover the principles of Agile project management for data and AI engineers. 

Lessons from World of Warcraft: Teamwork makes the dream work

Cooperative game theory involves common interests, necessary information exchange, voluntariness, equality, and mutual benefit among other things… where all elements work together. From games like World of Warcraft to The Legend of Zelda, we learn that a coalition of combined strengths creates the most optimal outcomes. Modern DataOps and data engineering does exactly this -  blending tech stacks with accelerators, open-source tools, and partner networks to achieve faster, smarter outcomes, governance, and scale. Here’s our story with OSM Thome.  

Lessons from Pokémon: Learn, Train, Grow. 

If knowledge is power, then context is the thunder stone in the Pokémon universe. To evolve our models, we train them with context, continuously teaching our tools and processes how to work for us with the code, comments, and patterns from specific projects. We explore this adaptive learning in our blogs on knowledge graphs and harnessing copilots. The lesson here? The more context, the better our models can learn. 

Lessons from Pac-Man: Responsible Play in a Fast Game

The core objectives of Pac-Man are clear: Eat all the dots: Avoid the ghosts, Use power pellets, and score Bonus points. If we were to turn this analogy to AI and Data governance, the lessons seem obvious - building for and with Responsible AI and with explainable AI principles in place, anticipating implementation hurdles and proactive risk management across all levels - HEal & INtERAcT to untie the AI knot. Read more.

What are some of your favorite legacy arcade games and a few principles you can pick up from them? Let us know in the comments.