Technology is evolving at a rapid pace, and the digital revolution has come with all sorts of new and efficient services. One such service is a simulation as a service.
The concept of simulation as a service is still in its infancy, but it seems to have significant potential. It is an innovative approach that takes the engineering process into the virtual world and then delivers it as a technology-enabled service or as an engineering-as-a-service product.
What are the Uses Cases for an AI Simulation?
There are many different use cases for simulation. We can see some of these in the aviation industry. The aviation industry uses simulations to train pilots, test out new airplanes, and study how planes react in certain situations.
Simulations are also used in other areas such as healthcare, automotive design, firefighting, and the military.
Nonetheless, there are still many more uses for simulation that have yet to be explored.
How Simpool Is Innovating The Gaming Industry
Simpool has developed an AI-based sandbox that analyses end users’ journeys, enabling App & Product developers to answer the most essential question for their product success – “What if?”. With an easy server-to-server API-based integration, Simpool will output: in-game insights, user segments, and most profitable predicted configurations. Simpool grants Product, Monetization, and User Acquisition managers, a competitive advantage by enabling them to gain 10x faster time to insight on data, 100x more exploration options, and 20x quicker product iterations, resulting in saved time, effort, and the ability to predict churn, conversion and LTV
Guy Bar Sade, Co-Founder & CEO of Simpool, served as a Director of BI & Analytics at Playtika (Nasdaq: PLTK) from 2013 to 2015, leading its movement toward a real data-driven company. For New York Tech Media, he talked about the value Simpool brings to Product Developers: “Using Simpool, product developers can maximize their work efficiency and innovation aspirations as significant barriers have been removed. Concerns and risks of harming up and running applications with a faulty new variant and bottleneck development can be applied with minimum effort into Simpool artificial ‘sandbox’ and tested. True, results are never 100% match reality, but 80% are good to understand whether a strategy is good or not”.
In the interview, he also addressed how sandbox optimization models are going to affect traditional A/B testing: ” While AB testing is a ‘used’ strategy, I believe that predictive methods and advanced ‘What-if’ engines will be able to provide solid answers. We can see this concept being used in the aviation world while training pilots over edge cases or even in the medical world, where doctors can be trained in simulators before performing complex surgeries. Online space will follow this trend, and it will also empower segmentation applications, MLops space with heavy data preparation processes, which are essential to model user behavior.”
Last Updated: January 3, 2022