Inspired Outcomes.
Inspired Outcomes.
Inspired Outcomes.
Inspired Outcomes.
This is part 2 of a short series chronicling the design process for an F1 Race Simulation System using AI, with the goal of creating a rapid interactive prototype. In the last post, we explored the following capabilities: In this post, we will extend the model to include: The original ChatGPT session may be found
Designing a F1 Strategy Simulator using AI – Part 2 Read More »
This is part 1 of a short series chronicling the design process for an F1 Race Simulation System using AI, with the goal of creating a rapid interactive prototype. Typically we employ a very interactive design process, with a minimum of these participants: However, for this experiment we don’t have access to an SME –
Designing a F1 Strategy Simulator using AI – Part 1 Read More »
In a previous post, we shared our view that AI may not be helpful with Domain Exploration. Some parts still hold true, but it didn’t stop us from exploring other ways that AI could help. Generative AI is inherently probabilistic, which means it isn’t the best at delivering pinpoint accuracy or consistent results.However, it excels
Rapid Prototypes in under 15 mins using ChatGPT Read More »