Enhanced geothermal systems (EGS) are not just new but a real game changer.

See Enhanced Geothermal Systems | Department of Energy [1]

Think of EGS as the perfect high-impact technology transfer from the best of Shale Revolution - drilling horizontal and hydraulic fracturing, to open up new areas for geothermal resources development.

With Google-Fervo and Meta-Sage leading the way for a geothermal renaissance in America, we shall take a closer look at the implication for GenAI development in subsurface energy (from the perspective of DeepLearning TIG).

Analog of Super Computing

GenAI as large language models LLMs are the monoliths (model with billions and more parameters and burning GPUs and energy in unprecedented scale). If the end game is artificial general intelligence AGI, monolith may become Gigantopithecus just as IBM Mainframe was at the zenith of enterprise computing (including seismic data processing), until a “seismic” shift to distributed parallel processing and server farms became the norm.

Switching to Microservices

Next week I'd be presenting "AI Application to Geothermal Development" [2] and highlight a different approach to de-risking geothermal development. It is serverless implementation (the opposite of monolith). We're transforming actionable insights by connecting data, leveraging serverless architecture, and unlocking collective intelligence: Real intelligence / human + AI.

Stay tuned, or better yet, register and be there to share your perspective on using AI and delivering a managed and predictable energy transition.

[1] Department of Energy https://www.energy.gov/ee...d-geothermal-systems

[2] program: https://broken.aapg.donfick.com/care...OtGE3uKYgbGPNhsSfVFV