Curbing AI's Energy Use with Innovation

How much environmental damage does AI cause? According to a report, the impact is largely unknown and often ignored. The driving force behind AI's energy consumption faces resistance. The pursuit of AI superiority continues, with big tech companies focused on user capture and data acquisition.

Without a way to assess AI quality, the focus remains on faster processing, larger models, and bolder claims. Environmental implications receive minimal attention. The solution to AI's energy dependence lies in economics. Smartphones demonstrate power management through engineering, balancing performance with battery constraints.

Datacenters face a similar challenge with cooling and power. The AI industry's financial investment in this race is significant. There is little consumer pressure to change this. The alternative is to shift conditions, making the race irrelevant.

Microsoft's Shift Online

In the 1990s, Microsoft recognized the internet's potential and aimed to dominate it. However, open standards and code made Microsoft's approach obsolete.

An Open Source Solution

An open-source approach is crucial for AI. Efforts should focus on areas where big tech's AI model is not viable. Prioritize efficiency, promote open ecosystems, and ensure data control for users. By removing the incentives for the arms race, transparency and power control can be achieved.

This shift can be framed as a competition between control and autonomy. Concerns about data sovereignty could drive AI development that avoids corporate dominance, especially in Europe. China could also play a role in preventing an American AI monopoly, even without gaining one itself. There are questions of morality with working with China.

Open source, which drove innovation, came from China. Open standards and code cannot be easily regulated.