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AI for climate: a real world test

We challenged a non-coder to use ChatGPT to write battery software. The results were surprising.

An episode of the Catalyst with Shayle Kann podcast, hosted by Latitude Media, titled "AI for climate: a real world test" was published on June 15, 2023 and runs 79 minutes.

June 15, 2023 ·79m · Catalyst with Shayle Kann

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The list of potential uses for AI in climatetech is growing fast: developing better materials, optimizing solar farms, integrating renewables and microgrids. But many of these are still theoretical. We wanted to find a real-world application that changed the way we make climatetech. So we decided to come up with our own test run. Back in March Duncan Campbell, vice president at Scale Microgrids, used ChatGPT to code some battery dispatch software and tweeted about his experience. Duncan isn’t a professional software developer, but he still came up with some promising results.  Could a non-coder like Duncan use AI to do the work of several climatetech coders? We invited Duncan to do it again and ramped up the challenge. We recruited Seyed Madaeni, CEO and co-founder of Verse to create a challenge for Duncan. Seyed is an expert in AI and the software used in electricity markets. He routinely sends “problem statements” to his team of software developers to create new software. This time, he sent a problem statement to Duncan that reflects real world conditions, one that we might actually assign to real engineers to solve. The challenge? Develop battery dispatch software using ChatGPT.  In this episode, Duncan presents his results to Shayle and Seyed. They talk about things like: The different methods of optimizing battery dispatch, from old-school Excel sheets to more sophisticated software written by coders Seyed’s process of assigning a problem statement to his engineering team and the simplified version he sent to Duncan Duncan’s process of iteratively working with ChatGPT-4 to develop and debug the code  Why working with ChatGPT is like working with a bunch of really fast, but really inexperienced junior coders If you want to see the code that Duncan wrote with ChatGPT, click here.  Watch the conversation on YouTube. Recommended Resources: Carbon Copy Live: How AI could supercharge climatetech The Wall Street Journal: Why AI Is the Next Big Bet for Climate Tech Catalyst is a co-production of Post Script Media and Canary Media. Support for Catalyst comes from Climate Positive, a podcast by HASI, that features candid conversations with the leaders, innovators, and changemakers who are at the forefront of the transition to a sustainable economy. Listen and subscribe wherever you get your podcasts. Catalyst is supported by Scale Microgrids, the distributed energy company dedicated to transforming the way modern energy infrastructure is designed, constructed, and financed. Distributed generation can be complex. Scale makes it easy. Learn more: scalemicrogrids.com.

The list of potential uses for AI in climatetech is growing fast: developing better materials, optimizing solar farms, integrating renewables and microgrids. But many of these are still theoretical. We wanted to find a real-world application that changed the way we make climatetech. So we decided to come up with our own test run. Back in March Duncan Campbell, vice president at Scale Microgrids, used ChatGPT to code some battery dispatch software and tweeted about his experience. Duncan isn’t a professional software developer, but he still came up with some promising results.  Could a non-coder like Duncan use AI to do the work of several climatetech coders? We invited Duncan to do it again and ramped up the challenge. We recruited Seyed Madaeni, CEO and co-founder of Verse to create a challenge for Duncan. Seyed is an expert in AI and the software used in electricity markets. He routinely sends “problem statements” to his team of software developers to create new software. This time, he sent a problem statement to Duncan that reflects real world conditions, one that we might actually assign to real engineers to solve. The challenge? Develop battery dispatch software using ChatGPT.  In this episode, Duncan presents his results to Shayle and Seyed. They talk about things like: The different methods of optimizing battery dispatch, from old-school Excel sheets to more sophisticated software written by coders Seyed’s process of assigning a problem statement to his engineering team and the simplified version he sent to Duncan Duncan’s process of iteratively working with ChatGPT-4 to develop and debug the code  Why working with ChatGPT is like working with a bunch of really fast, but really inexperienced junior coders If you want to see the code that Duncan wrote with ChatGPT, click here.  Watch the conversation on YouTube. Recommended Resources: Carbon Copy Live: How AI could supercharge climatetech The Wall Street Journal: Why AI Is the Next Big Bet for Climate Tech Catalyst is a co-production of Post Script Media and Canary Media. Support for Catalyst comes from Climate Positive, a podcast by HASI, that features candid conversations with the leaders, innovators, and changemakers who are at the forefront of the transition to a sustainable economy. Listen and subscribe wherever you get your podcasts. Catalyst is supported by Scale Microgrids, the distributed energy company dedicated to transforming the way modern energy infrastructure is designed, constructed, and financed. Distributed generation can be complex. Scale makes it easy. Learn more: scalemicrogrids.com.
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