focusing on how computational techniques can be leveraged to advance sustainability goals.
Encouraging this communication is neither easy nor without its difficulties, however, something that David Rolnick, one of the paper’s authors and co-founder and biodiversity lead of CCAI readily acknowledges. “Whether I’m optimistic or pessimistic, fundamentally, I’m action oriented, and I think it’s important to do what we can,” she underscores.Ultimately, doing what we can to address climate change through AI is going to be approached via two basic principles: limiting greenhouse gas emissions going into the future and responding to the effects of what levels of climate change we have, unfortunately, already locked in.
“[AI] is not the most powerful tool,” he emphasizes. “It’s not the best tool. It’s one tool, and it’s a tool that I had at my disposal. I’m not optimistic because of AI specifically, I’m optimistic because climate change isn’t an on-off switch. We get to decide just how bad it is. Any difference that we can make is a meaningful difference that will save lives.
“We’re seeing huge advancements in batteries in terms of cost and energy density,” Donti says. “Batteries are going “In transportation, there are many more and smaller companies [...] often there is much less means, much less data to exploit. Where one can take the system perspective, trying to optimize routing, charging station placement, machine learning has interesting things to add, but it’s not always straightforward.”
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