Estimating the Carbon Footprint of BLOOM, a 176B Parameter Language Model · HackerPapers discussions

Estimating the Carbon Footprint of BLOOM, a 176B Parameter Language Model — mentioned by FinnDituri

Fri, 26 Dec 2025 21:56:25 GMT

While I appreciate the irony in the trend of using AI to discredit people making positive claims about AI, it's a pet peeve of mine when it's used as a lazy way to avoid citing the original claim made against AI. It's reminiscent of the 'no you' culture from early 2000s forums. There's some meta-irony here too in that it often has to be debunked by humans, maybe that's the point, but it doesn't diminish my opinion of LLMs, it just makes me think that the Luddites may have had a point. For instance, in the Gemini screenshot, the claim for 100-500x more resource usage for AI queries comes from…

Paper and discussion history. A mention is not an endorsement.

Estimating the Carbon Footprint of BLOOM, a 176B Parameter Language Model — mentioned by ridethelightnin

Thu, 04 Dec 2025 14:35:10 GMT

This has so many unintended consequences for LLM over the next four years I would think. "JavaScript" tokenizes to 2 tokens (BPE). "ECMAScript" tokenizes to 3. No biggie here. But the real cost isn't training—it's inference. Every time an LLM has to reconcile "ES6" with "JavaScript," explain the naming, or reason through "user said JavaScript but docs say ECMAScript"— Hidden chain-of-thought overhead. Clarification tokens. Back of envelope: ~376M JS-related LLM queries/day globally. ~30% trigger some clarification overhead. That's ~5B extra tokens/day, ~1.85T tokens/year. At ~0.000025…

Paper and discussion history. A mention is not an endorsement.

Estimating the Carbon Footprint of BLOOM, a 176B Parameter Language Model — HN submission

Sun, 12 Mar 2023 18:17:42 GMT

Estimating the Carbon Footprint of Bloom, a 176B Parameter Language Model

1 point; 0 discussion replies on HN. Paper and source history. A submission is not an endorsement.