Natural Gas Fuels AI – And AI Means More Affordable Natural Gas
Artificial intelligence (AI) has the potential to revolutionize the American economy. The energy implications of the rollout of advanced AI are enormous both in driving increased demand for energy and in helping to meet this new demand.
The type of AI becoming increasingly prevalent today is generative AI, which is capable of producing text, images, videos, or other media from existing data. One common subset of generative AI is known as Large Language Models (LLM). This type of AI is inspired by one of the most impressive computers on earth – the human brain. LLM uses a neural network to train a model system such as ChatGPT with massive amounts of data. Huge quantities of writing, photographs, videos, and other data sources train a model, which then creates a map of the connections between individual nodes (neurons), allowing the AI to recognize patterns in the data and extrapolate new outcomes accordingly. Chat GPT-4 uses approximately 100 billion such neurons with 100 trillion connections. The energy requirements to train and operate such a network are correspondingly enormous due to the amount of server capacity needed.
Finding enough affordable, immediately deployable and extremely reliable energy to meet the demands of the current AI rollout while keeping greenhouse gas emissions low is proving to be one of the largest challenges in this next technology boom. Fortunately, America’s vast reserves of natural gas provide a reliable solution that can help to lower energy costs and emissions from the massive new data centers that AI depends on.
The even better news is that AI itself is helping to fill the fuel demand created by AI data centers. The days of drilling an exploratory well in hopes there might be natural gas at the bottom of it are far behind us. Seismic surveys allow producers to search for detectable deposits of natural gas by generating, recording and analyzing sound waves in a process similar to how bats use echolocation to navigate or ships use sonar to search for potential obstacles. While this process previously required highly trained human analysts to examine the seismic survey returns, AI trained on the results of previous seismic surveys is being deployed to find deposits that human operators would have previously missed. According to MCF Energy analyst Deborah Sacrey, quoted by Oilprice.com, some of the programs in use for this purpose today have a success rate of over 80% when drilling in areas that were invisible to human analysts.
The beneficial feedback loop here is obvious. The more energy AI data centers can access, the more effectively AI can be trained in searching for natural gas and in techniques to help us use energy more efficiently in other sectors of the economy. With the potential for a dramatic acceleration in economic growth through AI-enhanced productivity, the partnership of natural gas and AI stands to raise all boats, increasing the standard of living in a way unseen since the industrial revolution and making all Americans happier, healthier, and wealthier in the long term.