| Honestly the conversation of AI researchers on climate science seems so superficial and removed from reality of climate change. It's like they are trying to solve a drought by capturing condensation on a glass of cold beer. https://ourworldindata.org/emissions-by-sector The major emissions sectors are agriculture, transportation, cement and metal, energy usage in primary sector for thermal processes. For someone who seems to have dedicated their lives to climate and AI solving energy intensity of deep learning isn't even relevant let alone a factor in emissions, also better climate models aren't the solution for reducing emissions. We need not only new tech but a new socio-technical system for reduction of emissions. Rice cultivation, cement, waste, heating of houses in northern latitudes all generate sizeable quantum of emissions what's AI going to do there to solve these? Optimization can squeeze some gains but we need revolution in fundamental science and engineering capabilities to quickly discover, synthesize and scale the manufacturing of new materials whilst rewiring the every elememt of the the supply chain to support such transition. This is a problem for AI- yes, but is this where bulk of climate AI research is focused on? Sadly not! What is more motivating and upbeat though is the fact scientists from traditional engineering domains are increasingly discovering AI. SciML work by Chris rackauckas PiNN by karniadikis, neural operators by anima Nvidia are some of the best forays into this space. I have not mentioned the frentic research happening in AI and microbiology which can be a game changer in invention of biotechnology solutions for climate change. Yet sadly none of this is ever mentioned or covered in climate AI related conversations. |
This can at least be partially solved by having all homes in these regions training machine learning models on racks of GPUs at night.