🌨️ Can AI Solve the Climate Crisis?

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If you’re trying to get funding for an AI startup - or have an idea, there’s a tool called ExitFund (link in Tools section - not sponsored) that might be something to look into.

It would be interesting to go through the process and document it along the way, so I might do that. Let me know if I should add it as a new section.

Also…

Reddit devs, admins, and mods rug pulled the community last night, wiping out millions - when they sold before the announcement to end the crypto karma project was announced - which means I got rugged twice this week, and it’s only Wednesday.

Uptober is a lie.

Let's get it.

- Kevin

In a recent conversation with WIRED, Sims Witherspoon, the climate action lead at Google-owned DeepMind, delved into how AI can be an ally in combating climate change.

Citing the increasing unpredictability of weather patterns due to global warming, DeepMind is employing its AI prowess to address this existential challenge.

According to Witherspoon, AI assists in three distinct ways:

1. Understanding the Problem: AI equips us with enhanced models for predicting and monitoring climate change. An instance Witherspoon highlighted was DeepMind's 'precipitation nowcasting,' which forecasts rainfall a few hours in advance. This tool outperformed other methods and was deemed superior by Met Office forecasters.
   

2. Optimizing Existing Systems: Rather than entirely discarding current infrastructures and systems, AI can be harnessed to fine-tune them. For instance, in data centers, AI-driven initiatives managed to enhance energy efficiency, slashing energy consumption by an impressive 30%.
   

3. Advancing Breakthrough Technologies: AI, as depicted in popular media, is often seen as a futuristic, breakthrough tool. Validating this perception, Witherspoon mentioned DeepMind's foray into nuclear fusion. By deploying neural networks, the team developed a reinforcement learning model to control plasma shapes in fusion reactors, potentially paving the way for a limitless source of carbon-free energy.

Witherspoon acknowledged the significant carbon footprint of AI models and emphasized the importance of transparency regarding their energy consumption. Efforts are being made to minimize the computational power required for these models.

Lastly, two crucial roadblocks in harnessing AI for climate change are: (1) the access to comprehensive climate-critical data and (2) collaboration with domain experts.

These experts not only deepen the understanding of the challenges faced but also ensure that AI solutions are practical and actionable.

Optimistically looking to the future AI should be seen as a transformative tool capable of solving multifaceted climate-related challenges at an unparalleled scale.

For a deeper dive check out the full story below.

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