The AI Energy Crisis & A Newfound Push for Efficiency

The energy demands of major mainstream AI models are becoming unsustainable, with training a single model producing as much carbon as five cars over their lifetimes. Industry giants like Microsoft and Google are investing in energy alternatives like nuclear and geothermal to tackle the issue. Meanwhile, startups like Rhymes are rethinking AI’s future with smarter, more efficient models, such as the Aria model, which only activates the necessary parameters for each task. These innovations could lead to a more sustainable AI future without massive infrastructure investments.

It’s no secret we've stumbled upon a formidable obstacle to our AI-powered future: the staggering energy consumption of our current models.

Industry leaders are scrambling to come up with short-term answers to ensure they don’t miss the wave, with ambitious efforts like Microsoft’s reopening of nuclear reactors on Three Mile Island and Google working on “first-of-its-kind” geothermal projects.

And while that plays out at the big kid’s table, a flock of new startups are building on the progress made in recent years, re-thinking the fundamentals to see if there are solutions that could serve as the long-term solution.

One that doesn’t require hundreds of millions of dollars in infrastructure investment.

AI’s Power Demands Are a Ticking Time Bomb

Operating large language models in their current iteration is an energy-intensive process that's rapidly approaching unsustainable levels. Training a single AI model can emit as much carbon as five cars over their entire lifetimes. It's not just an environmental concern; it's a scalability nightmare threatening to derail the AI revolution before it fully takes flight.

Consider these sobering facts:

• GPT-3, with its 175 billion parameters, reportedly required 1,287 MWh for a single training run.
• The carbon footprint of training a large NLP model is estimated to be around 626,000 pounds of CO2 equivalent.
• As models grow, so does their energy consumption – often at a superlinear rate.

And as the industry pushes for more advanced AI capabilities, this energy consumption is set to skyrocket. This is not only a problem on an operational level but also in the greater picture, as industry leaders like Google have pledged to achieve net-zero carbon emissions. As part of that effort, tech giants are already buying billions in carbon credits from firms doing things like plugging orphaned oil and gas wells - a market where demand is already ...