Well even law enforcement and politicians (corrupt or not) don’t want this.

https://www.passbolt.com/

A brilliant researcher will even dig up this ancient comment and will be even more frustrated knowing there’s an answer we all knew, but no one ever posted it.

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How exactly are his eyebrows in the exact middle of his face? Very difficult to process this.

I think he genuinely believed it was the best thing for society. He, like so many, was (and likely still is) convinced that everyone thinks like he does. So he believes the only thing that drives people is money.

Now if that were the case, the only way to advance society and facilitate growth in software would be to offer smart people a lot of money.

In that flawed logic, he really thought it was for the best.

You’re absolutely right! According to the research you cited, the energy use is actually much LOWER than I stated in my comment.

Your source shows that an efficient AI model (Qwen 7B) used only 0.058 watt-hours (Wh) per query.

Based on that, my entire 3-prompt chat only used about 0.17 Wh. That’s actually less energy than a single Google search (~0.3 Wh). Thanks for sharing the source and correcting me.

If It makes you feel better (or at least more educated)……the entire three-prompt interaction to calculate dogpower consumed roughly the same amount of energy as making three Google searches.

A single Google search uses about 0.3 watt-hours (Wh) of energy. A typical AI chat query with a modern model uses a similar amount, roughly 0.2 to 0.34 Wh. Therefore, my dogpower curiosity discussion used approximately 0.9 Wh in total.

For context, this is less energy than an LED lightbulb consumes in a few minutes. While older AI models were significantly more energy-intensive (sometimes using 10 times more power than a search) the latest versions have become nearly as efficient for common tasks.

For even more context, It would take approximately 9 Lemmy comments to equal the energy consumed by my 3-prompt dogpower calculation discussion.

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Username checks out

If I’m not mistaken, you specifically showed an interest in better understanding this.

A dog’s power output comes from its muscle mass, which for a healthy dog is about 45% of its total body weight. This gives our 28-pound dog roughly 12.57 lbs (or 5.7 kg) of muscle.

Studies of animal muscle show that the peak power output of vertebrate muscle tissue during a short, explosive burst (like a jump or the start of a sprint) is around 100 to 200 watts per kilogram of muscle.

Now we can estimate the dog’s peak power:

• Low estimate: 5.7 kg of muscle x 100 W/kg = 570 watts
• High estimate: 5.7 kg of muscle x 200 W/kg = 1140 watts

Converting these figures to horsepower (1 horsepower = 746 watts):

• Low estimate: 570 W / 746 ≈ 0.76 horsepower
• High estimate: 1140 W / 746 ≈ 1.5 horsepower

So, a small 28-pound dog might be able to generate a peak power of around 0.75 to 1.5 horsepower for a very brief moment.

So this YASA motor is somewhere between 670 and 1,340 times more powerful than the dog it’s being compared to in weight. That’s some jaw-dropping power output.

Looks like you need a blog. You could post your own articles.

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This is the closest you’ll get to proof I would imagine.

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“The magic you are looking for is in the work you are avoiding” Dipen Parmar

This is dumb. Sorry.

Instead of doing the work to integrate this, do the work to publish your agent’s data source in a format like anthropic’s model context protocol.

That would be 1000 times more efficient and the same amount (or less) of effort.