How One Company Is Using AI To Unlock This Promising Renewable Energy

Zanskar, a startup company, is utilizing AI technology to identify optimal drilling locations for geothermal energy, aiming to make this renewable energy source more cost-effective. By leveraging geological data and machine learning, Zanskar is revolutionizing the geothermal energy sector, with the potential to significantly reduce costs and advance renewable energy production.

A recent Forbes interview discusses a startup called Zanskar that is using AI to tap into geothermal energy, which is a promising form of renewable energy. Geothermal energy involves harnessing heat generated below the Earth’s surface, but the cost of exploration and drilling has hindered its widespread adoption, accounting for less than 1% of total electricity generated in the US. Zanskar aims to solve this problem by using machine learning to identify optimal drilling locations and minimize costs. The company recently raised $30 million from investors, bringing their total funding to $45 million.

Zanskar’s AI technology leverages geological data from various sources, such as satellites and fieldwork, to pinpoint the most suitable spots for geothermal drilling. By accurately identifying these locations, Zanskar aims to streamline the process and make geothermal energy more cost-effective. The accuracy of their AI models varies based on the availability of data, with regions rich in data achieving accuracy rates around 90%. The company’s focus on exploration sets them apart in the geothermal energy space, where competition exists from other startups like Fervo, which have developed cost-effective drilling techniques.

Venture capitalists are increasingly investing in renewable energy startups that leverage AI, recognizing the potential for innovation and efficiency in the sector. The use of AI in renewable energy, such as geothermal power, aligns with the overall trend of AI’s integration across various industries. AI’s ability to process and analyze large amounts of data can enhance decision-making and drive advancements in fields like energy exploration, biotech, healthcare, and engineering. The key to successful AI implementation lies in validating models with real-world data and continuously improving them based on new information.

While concerns exist about AI’s potential impact on job displacement and data accuracy, using AI in renewable energy like geothermal power largely falls in the “pros” column. By making energy production more efficient and cost-effective, AI can help advance the renewable energy industry and create new job opportunities. Zanskar’s AI technology has the potential to significantly reduce costs in geothermal energy projects by optimizing drilling locations and minimizing the number of drilling attempts needed. The company aims to have their first geothermal plant operational within the next three to four years, working with utility companies and tech industry partners to establish reliable energy sources for various operations.

In conclusion, Zanskar’s innovative use of AI in geothermal energy exploration represents a step towards unlocking the potential of renewable energy sources. By combining machine learning with geological data, the company seeks to revolutionize the geothermal energy sector, making it more accessible and cost-effective. The broader trend of AI integration in renewable energy reflects a positive shift towards sustainability and innovation in the energy industry. With continued advancements in AI technology and ongoing validation of models, Zanskar and similar startups are poised to drive significant progress in the renewable energy space.