Digital Twins and Simulation in IoT | Cosmo Tech's Sam George | Internet of Things Podcast

DesignCosmotechincreased profitability by 5% and reduced carbon emissions by 60%

AI guided simulation analyzed millions of potential factory locations against KPIs like carbon and profitability to determine the optimal site for new production.

“What goal AI guided goal seeking simulation really does is, it gives those experts superpowers, right? It's really there to help them in a system, in taking that complex environment that's really difficult for a human being to consider all possibilities. And effectively generating all the different possibilities and coming back with, here's the optimal one.”

DesignCosmotech

AI refined and guided the simulation engine toward specific KPIs, allowing it to simulate fewer scenarios to achieve the desired outcome rather than using brute force.

“What it would do is it would just do some brute force permutation of every possible location, a source of factory on the planet. You could maybe take a 1000000000 different possible locations and prune them down. 99% of those are going to be irrelevant. What AI does is AI helps guide the simulation engine or cosmotech simulation engine, towards KPI fulfillment, so that you simulate as few as things as possible to achieve those KPIs.”

DesignCosmotech

The system used deterministic generative AI to create new future possibilities for simulation, avoiding the hallucinations common in models like GPT-3.5 or GPT-4.

“What's interesting is that when Cosmotech is taking advantage of AI guided simulation, there is a component of generative AI to it, like it is generating these new future possibilities. The thing that's different about it is it's deterministic. Whereas things like GPT 35 and GPT 4 are prone to hallucinations, you ask it something it doesn't understand and now it's hallucinated.”