AI Energy Efficiency

"If Spotify launched in the 1980s, what would its marketing campaign look like?"
A fun way to stretch creative strategy and contextual thinking.

RAG (Retrieval-Augmented Generation)
An AI setup where the model pulls in fresh/contextual data, like from a database, before answering, so it's not stuck with old training info.

Read: "AI Superpowers" by Kai-Fu Lee
A must-read on how AI is reshaping geopolitics, business, and innovation.

Beyond the Obvious: AI at Work A ramen-cooking robot called Cheffy, developed by Yo-Kai Express in partnership with SoftBank Robotics, is already serving bowls from famed restaurants in Japan in just about 90 seconds, no human chef needed.

What it is:

for RAG/agents. A developer toolkit that converts messy PDFs, slides, emails, and scans into clean, chunked JSON

How you can use it:

Point it at your docs, extract text + layout + tables, and feed structured chunks straight into search or retrieval workflows.

Good for you if:

You're shipping LLM features and your biggest headache is documents that aren't actually machine- readable.

AI models are getting more efficient, Google says a single query now uses as little as 0.24 watt-hours of electricity. But at scale, the picture flips: data centers are projected to consume up to 8% of all U.S. electricity by 2030. That means while per-prompt efficiency is improving, explosive adoption will likely outweigh those gains. AI is quietly becoming part of the same global conversation as aviation and manufacturing industries that must balance progress with sustainability. When evaluating AI tools or building your own, don't just compare features, ask about efficiency and infrastructure. Lighter models, batch processing, and edge AI aren't just cost-savers; they'll also help future-proof your business as sustainability becomes a brand and regulatory expectation.

What Ringg thinks:

This is the hidden cost of scaling AI-latency and accuracy get all the headlines, but energy might be the real bottleneck. For builders, it's a reminder that efficiency isn't just a "green" goal but a competitive one: the teams that figure out how to make AI less power-hungry will hold the edge in cost, speed, and scalability. Illustration by Elena Lacey/The Washington Post Credits: The Washington Post, Tom's Guide