RinggCity Newsletter Ringg AI This week's 3 big questions. Will AI's energy efficiency gains be overshadowed by surging demand? AI's efficiency is improving, but data centers powered by AI are projected to consume up to 8% of electricity by 2030, small gains. (Read more ahead). The Washington Post Are legal teams becoming leaders in AI strategy? Legal teams are increasingly stepping up as strategic partners in AI adoption, guiding not just compliance but also how businesses responsibility deploy and scale AI. TechRadar Could multimodal search tools really unseat Google’s dominance? Possibly, multimodal search could challenge google if it delivers faster, richer, and more intuitive answers than traditional keyword search. Fortune India | PPC Land QuickBytes Prompt “If spotify launched in the 1980s, what would its marketing campaign look like?” A fun way to stretch creative strategy and contextual thinking. AI Jargon 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 the old training method. Reccos Read: “AI Superpowers” by Kai-Fu Lee A must read on how AI is reshaping geopolitics, business, and innovation Meme Matrix (ChatGPT) Bonus Byte! 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 ToolBench Unstructured What it is: A developer toolkit that converts messy PDFs slides emails and scans into being Chunked JSON and RAG/agents How can you use it: Point it at your docs, extract text plus layout plus tables and feed structured chunks straight into search or retrieval workflows Good for you if: You are shipping LLM features and your biggest headache is documents that aren’t actually machine readable RinggLens AI’s Energy Dilemma 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 US electricity by 2030 That means why per prompt efficiency is improving explosive adoption will likely outweigh those gains AIR is quietly becoming part of the same global conversation as aviation and manufacturing industries that must balance progress with such sustainability When evaluating AI tools for 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 Credits: The Washington Post, Tom’s Guide Should continue theaters follow Netflix’s new ethical AI Playbook? How much could the RMG bank cost in the country in rupees jobs and growth? Can we make AI powerful yet energy-light?