i'm no expert, and i actually asked google gemini a similar question yesterday - "how much more energy is consumed by running every query through Gemini AI versus traditional search?" turns out that the AI result is actually on par, if not more efficient (power wise) than traditional search. I think it said its the equivalent power of watching 5 seconds of TV per search.

I also asked perplexity to give a report of the most notable ARXIV papers. This one was at the top of the list -

"The most consequential intellectual development on arXiv is Sara Hooker's "On the Slow Death of Scaling," which systematically dismantles the decade-long consensus that computational scale drives progress. Hooker demonstrates that smaller models—Llama-3 8B and Aya 23 8B—now routinely outperform models with orders of magnitude more parameters, such as Falcon 180B and BLOOM 176B. This inversion suggests that the future of AI development will be determined not by raw compute, but by algorithmic innovations: instruction finetuning, model distillation, chain-of-thought reasoning, preference training, and retrieval-augmented generation. The implications are profound—progress is no longer the exclusive domain of well-capitalized labs, and academia can meaningfully compete again."