Models can (and should) be shrunk whenever possible to use less computing power. And knowledge can be recycled and reused instead of starting the deep learning training process from scratch. Ultimately, finding ways to reduce model size and related computing power (without sacrificing performance or accuracy) will be the next great unlock for deep learning. That way, anyone will be able to run these applications in production at lower cost, without having to make a massive environmental tradeoff. Anything is possible when we think small about big AI – even the next application to help stop the devastating effects of climate change.