u/BoringContribution7

If AI's water and energy problem bothers you, you've probably seen "EcoGPT" pop up as the green alternative.

it's not just a ChatGPT with a green logo. There's a lot more to it. Here's my simple breakdown based on my understanding of the app.

EcoGPT is built to be the leanest model that gets the job done. I use it on a daily basis for all my content, emails & reach-outs.

How is it efficient:

→ EcoGPT runs lean open-source models instead of frontier ones

→ It routes queries through Groq's LPU chips, claimed to be up to 10x more energy-efficient than GPUs

→ Smart caching means repeat questions don't re-run the full

→ It claims \~90% less energy than traditional AI, on renewable-heavy infrastructure

ChatGPT does none of this by design. It's optimised for capability, not for the footprint of each query.

The offset:

EcoGPT plants 1 tree per 100 messages and says it has planted 163k\+ trees. It also shows you a running environmental-impact tracker as you chat.

ChatGPT gives you no per-query offset and, notably, still disowns water and carbon footprint.

EcoGPT is NOT a 1:1 ChatGPT replacement.

Match the tool to the task. Use a lean, green model for the 80% of prompts that don't need a supercomputer. Save the frontier model for the 20% that actually do.

Per query, Claude Opus uses about 4 Wh. ChatGPT (gpt-4o) uses about 0.3 Wh. That makes Opus roughly 13x more energy-intensive for the same question. (https://aitechmodel.com/ai-energy-consumption-per-query-in-2026-claude-averages-0-012-kwh-per-response-vs-0-0003-kwh-for-a-google-search/)

It's a model-size comparison.

.Both Anthropic and OpenAI run models spanning the same range, from under a watt-hour to several watt-hours.

Which Company uses more water & electricity? Nobody knows, because neither company publishes it. No official per-query energy numbers from either. No emissions disclosures from either ahead of their IPOs, while Microsoft and Google both put out full sustainability reports every year.

if you're picking a "greener" AI company based on public data, you can't. there isn't any to pick from.

Should companies be required to disclose per-model energy use the same way they disclose pricing?

Sam Altman stated in a blog post that the average chatgpt query uses about 0.34 watt-hours and about 0.000085 gallons of water, comparing it to what a high-efficiency lightbulb uses in a couple of minutes, that figure hasn't been peer reviewed and openai hasn't clarified what counts as an "average" query.

Data Center Dynamics. (ALSO this is not verified he just said it NO Proof)

anthropic hasn't published anything comparable, as of march 2026 anthropic has not reported scope 1, 2, or 3 emissions in any public filing, and states only that it works with cloud providers that prioritize renewable energy, so any claude water or energy number you see online is a third-party estimate, not a company figure.

so which matters more here, openai's own unverified number, or anthropic's total silence, and does either one actually tell how much energy they're consuming?

Here are the top Canada class action settlements currently open, deadlines + payout

Canadian Armed Forces racial discrimination

deadline: Oct 15, 2026

who: current/former CAF members who faced racial discrimination or harassment during service (1985–2025)

payout: $5,000–$35,000, assessed individually by severity

Ontario training schools

deadline: Sept 22, 2027 (longest runway on this list)

who: anyone alive as of Dec 8, 2015 who lived at one of 13 listed Ontario training schools, 1953–1984

payout: $5,000 flat if you just confirm harm + school, up to $100,000 for serious cases like sexual assault

silk / great value listeria outbreak

deadline: Oct 16, 2026

who: anyone in Canada who bought or drank the recalled Silk or Great Value plant-based beverages from the July 2024 recall

payout: $400–$300,000 depending on how sick you got, refunds also available if you just bought the product with no illness

cibc/renaissance mutual funds, discount broker

deadline: Oct 21, 2026

who: held CIBC or Renaissance fund units through a discount broker (td direct, bmo investorline, etc) between 2003–2024

payout: pro-rata split of $26M, amount only known after deadline passes

cibc/renaissance mutual funds, non-discount

deadline: Nov 18, 2026

who: former holders (not through a discount broker) need to file. current holders don't do anything, money gets deposited straight into their funds

payout: pro-rata split of $11M

cra privacy breach (sweet v hmk)

deadline: Feb 3, 2027

who: NOT everyone affected in 2020, only two narrow windows: accounts hit in the credential-stuffing attacks (jun 26–aug 18, 2020) or accessed through a represent-a-client account (oct 8–nov 25, 2020)

Payout: $80 flat for loss of time, $200 flat for fraudulent CERB access, up to $5,000 for documented losses.

what will be the state of sustainable ai in 2030? to achieve it I think these should be the bare minimum:

Make MoE and sparse architectures the default; models activate a fraction of themselves per query; "watts per useful answer" on the spec sheet next to benchmarks.

data centres stop drinking. closed-loop cooling standard in new builds, waste heat feeds district heating and greenhouses, "water-positive" is audited, not false marketing.

the grid caught up. new capacity comes with dedicated clean power, not old coal plants on life support. workloads run when the grid is cleanest.

Transparency is law, not pr. Every major model reports energy and water use. AI tools carry an environmental nutrition label, like cars show emissions.

We use it more deliberately. "throw AI at everything" becomes "is a model even the right tool here" small local models handle routine stuff, big models saved for what actually needs them.

Efficiency gains get eaten if usage outgrows the savings, and voluntary pledges don't survive a compute arms race.

Which of these actually arrives before 2030? What do you hope for, and what is actually achievable?

Always assumed English just threw silent letters in to torture learners, but the actual history is more interesting.

The "k" in "knight" wasn't always silent. Earlier people really did pronounce it — k-nicht, closer to how German still says related words like "Knie" for knee with the k intact. The sound quietly dropped over time but the spelling froze in place, so we're stuck writing a letter nobody says.

Then there's the flip side: some silent letters were added on purpose, after the fact, to make a word look like it belonged to a certain trend or root. The "e" in "house" is that kind of thing — decoration more than pronunciation. And the classic "silent e" at the end of a word often exists to reach back and change the vowel: it's the reason "hop" becomes "hope."

Someone shared a mnemonic they'd kept for 40 years: vowels are being hunted by naughty letters, and the silent e stands guard at the end of the word to protect the vowel. Cheesy, but it stuck with them since childhood, which is kind of the point of a good mnemonic.

I am interested in this & want to know moreof such whose backstory behind silent words.

people have shared multiple ways to make AI more ecofriendly, like using better prompts or choosing models based on the complexity of the problem. surely it could be helpful, but I see it as an architecture issue.

AI-focused data centres grew electricity use 50% in 2025, and the IEA projects the total nearly doubling to 950 TWh by 2030 (source: iea.org/reports/key-questions-on-energy-and-ai/executive-summary). On water, about two-thirds of what a data center uses isn't the cooling towers on-site, it's the electricity plant generating its power.

MoE models fix the bottleneck by only querying the parts of the model it needs instead of firing the whole thing every time.

What do you think companies should be doing from here on to make AI sustainable?

I was reading an old edition of Cheaper by the Dozen, hit the phrase "ruptured deleted," and it stopped me because it means nothing on its own. The publisher didn't want to print the original swear word, so instead of a blank or a dash, they swapped in a nonsense placeholder. Another spot in the same book just says "unprintable" instead of the word.

the character is clearly cursing, everyone reading knows it, and the page just says something absurd with a straight face. Still censorship, but it's winking at you.

I liked it, better than modern bleep or a row of asterisks any day. it treats the reader like an adult who can do the math.

Has anyone encountered anything similar? At first it doesn't make sense, but then it does

This clicked for me recently and now I notice it everywhere. There's a set of words where the exact same spelling gets said two different ways depending on what you mean.

"Learned" is the cleanest example. Say it "lernd" and it's the verb - you learned something. Say it "lern-ed," two syllables, and it's an adjective meaning scholarly, as in "a learned professor." Same with "blessed": "blest" is usually the verb (he blessed me), while "bless-ed" is the adjective. And "beloved" splits too - "belov'd" leans adjective, "belov-ed" the noun/direct address.

The pattern seems to be that the extra-syllable versions survive in more formal, dramatic, older-feeling words, And the clipped versions are the everyday verbs.

"Primer" does a related trick but with vowels: rhyme it with "timer" and it's the paint/undercoat, say "primmer" with a short i and it's the little instructional book. Same word, and honestly both meanings are about "preparing" something.

What other words flip meaning based purely on how you say them? I feel like once you start listing them there are more than you'd expect.

Microsoft's emissions, 2025 vs 2024:

* Emissions: 20.29M metric tons CO₂e, up from 16.21M a 25% jump

* Gross (before offsets/interventions): over 34M metric tons, nearly double what it was in 2022

* Electricity used: 37M MWh, up 24%, enough to power 3.4 million U.S. homes for a year

* S****cope 2 (from power contracts): jumped from 258,000 tons to nearly 2.7M tons an 10x increase, since Microsoft dropped renewable energy certificates that were masking the real number

* Biggest single site: its Boydton, Virginia data centre over 3M MWh alone

They still claim to hit carbon-negative by 2030. It's not just Microsoft, Google emissions up 18%, Amazon up 16% this same reporting cycle

We source from suppliers in China who aren't tech-savvy, no paypal, trade assurance. They only have bank accounts. Right now, every payment goes through our bank as an international wire, and the FX markup plus wire fees add up fast. This is something we dont like paying every time.

Is there a better way to pay bank-only suppliers in China without losing so much to conversion and fees each time?

stripe's invite-only in india, so building around it isn't possible. lemonsqueezy was one of the options back then but it's part of stripe too.

what should you go with while building saas from india? There's one popular one we all know of, but i've heard a lot of bad reviews about their service and their fees.

what should we go with, one that supports payments from us/eu countries, not just indian payments (upi payment is optional)?

my kids love toys & have collected like 100s of them, but now we're trying to be mindful about what we buy the kids, we've been trying to stick to toys that actually help in the growth & development of our kids.

The main thing we're working on is books. picture-heavy chapter books at bedtime, and he picks off the shelf himself, and the hope is that stories become what he reaches for when he's bored. Some nights he asks for two, some nights it's a fight to get through four pages.

we has a collection of magnetic tiles that he's still building with two years in, a rush hour puzzle set, snap circuits, which he needed help with at first and now runs on his own, and a beginner chess set that we both play badly. Rubik's cube was way too early.

for parents with kids in the 5-10 range: what are your kids' go-to toys & are you mindful about what they play with? and do board games work at this age?

There was a boy in my son's year at a party last year who turned up in a princess dress, full moana, loving life, and not one of the kids batted an eyelid, it was the adults doing the double takes. that stuck with me. my little one's favourite colour is pink, he's got a unicorn bike helmet, he went as ghost spider to a party once, and for a while i quietly worried about him standing out now he's started school. then i remembered those kids at that party and realised they're miles more accepting than we give them credit for, the prejudice gets trained into us as we grow up, it isn't there at 5.

same with the messy play guilt honestly. i used to feel bad we don't do the sensory trays and kinetic sand at home, then i clocked that mine gets properly filthy climbing trees, walking barefoot in the park, eating an ice lolly with half of it down his front, and that is the sensory play. the frog-spawn chia pudding trays can stay at nursery, where they mop the floor after, not me.

anyway, i've stopped performing for a crowd of parents who mostly aren't even watching, and he's happier for it, and weirdly so am i.

I almost quit my sport after my second kid, I had guilt every time I left for a weeknight match instead of staying home with the kids. I shared it with my partner, and he was like, "The kids are excited for your match. So I looked into whether it was actually hurting them, and found the opposite of what I had guilt about. They were mostly happy to see me going and would walk me to the main gate. I realised that a mother's own activity level predicts her kids' activity level, which links to better outcomes in their children, as long as the kid still gets real time with you.

I noticed that kids learn from what they watch you do. My daughter imitates and coaches me from the sideline and wants to try everything herself. She's picked up talking to strangers, having conversations, just from watching me talk to neighbours.

There are multiple AI/non-AI tools I use on a daily basis that plant trees based on the usage.

* IdleForest Chrome/Edge extension plants trees off revenue from your unused (idle) bandwidth rather than usage or queries directly. Funds go through Trees for the Future, Tree-Nation, and 1ClickImpact.

* OceanHero search engine, does not plant trees, cleans the ocean instead. Roughly 1 plastic bottle removed per 5 searches or 17 tabs opened, funded through Plastic Bank and Waste Free Oceans.

* Wave Browser browser, also ocean cleanup not trees, partnered with 4ocean, funds removal by session/browsing rather than per-search

* EcoGPT plants one tree per 100 queries/messages, Funds go through One Tree Planted, American Forests, and Trees for the Future.

Which are the other AI tools that plant trees based on our usage?

AI datacenters use a lot of water (billions of gallons) and energy. Apart from that, people in nearby areas are directly impacted by it, potable water, constant noise, heat, and more.

Cochise County almost banned data centers outright, the board pulled back at the last minute and settled for regulations, water plans, noise studies. San Marcos, Texas didn't pull back, their council voted 4-3 in June to ban data centers citywide, first in the state to do it, now facing a legal challenge over whether cities even have that authority.

Meanwhile there are multiple models and companies claiming to have less carbon footprint, using less energy and emissions, like **mistral, cohere, ecogpt**, all claiming to be efficient, so why hasn't the market moved toward them, and why aren't companies moving in that direction as a priority?