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submitted 1 week ago by [email protected] to c/[email protected]
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[-] [email protected] 3 points 1 week ago* (last edited 1 week ago)

Good engineers are figuring out more energy/compute efficient ways to train models all the time. Part of the original deepseek hype was that they not only cooked a competitive model but did it with the fraction of energy/compute needed by their competion. On the local hosting side computer hardware isalso getting more energy efficient over time not only do graphics cards improve in speed but also they slowly reduce the amount of power needed for the compute.

AI is a waste of energy

It depends on where that energy is coming from, how that energy is used, and the bias of the person judging its usage. When the energy comes from renewable resources without burning more emmisions into the air, and computation used actually results in useful work being done to improve peoples daily lives I argue its worth the watt hours. Espcially in local context with devices that take less power than a kitchen appliance for inferencing.

Greedy programmer type tech bros without a shred of respect for human creativity bragging about models taking away artist jobs couldn't create something with the purpose of helping anyone but themselves if their life depended on it. But society does run on software stacks and databases they create, so it can be argued llms spitting out functioning code and acting as local stack exchange is useful enough but that also gives birth to vibe coders who overly rely without being able to think for themselves.

Besides the loudmouth silicon valley inhabitors though, Theres real work being done in private sectors you and I probably dont know about.

My local college is researching the use of vision/image based models to examine billions of cancer cells to potentially identify new subtle patterns for screening. Is cancer research a waste of energy?

I would one day like to prototype a way to make smart glasses useful for blind people by having a multimodal model look through the camera for them and transmit a description of what it sees through braille vibration pulses. Is prototyping accessibility tools for the disabled a waste of energy?

trying to downplay this cancer on society is dangerous

"Cancer on society" is hyperbole that reveals youre coming at us from a place of emotional antagonism. Its a tool, one with great potential if its used right. That responsibility is on us to make sure it gets used right. Right now its an expensive tool to create which is the biggest problem but

  1. Once its trained/ created it can be copied and shared indefinitely potentially for many thousands of years on the right mediums or with tradition.

  2. Trsining methods will improve efficiency wise through improvements to computational strategy or better materials used.

  3. As far as using and hosting the tool on the local level the same power draw as whatever device you use from a phone to a gaming desktop.

In a slightly better timeline where people cared more about helping eachother than growing their own wealth and american mega corporations were held at least a little accountable by real government oversight then companies like meta/openAI would have gotten a real handslap for stealing copyright infringed data to train the original models and the tech bros would be interested in making real tools to help people in an energy efficient way.

ai hit a wall

Yes and no. Increasing parameter size past the current biggest models seems to not have big benchmark omprovements though there may be more subtle improvements in abilities not caputured with the test.

The only really guilty of throwing energy and parameters at the wall hoping something would stick is meta with the latest llama4 release. Everyone else has sidestepped this by improving models with better fine tuning datasets, baking in chain of thought reasoning, multi modality (vision, hearing, text all in one). Theres still so many improvements being made in other ways even if just throwing parameters eventual peters out like a Moore's law.

The world burned long before AI and even computers, and it will continue to burn long after. Most people are excessive, selfish, and wasteful by nature. Islands of trash in the ocean, the ozone layer being nearly destroyed for refigerantd and hair sprays, the icecaps melting, god knows how many tons of oil burned on cars or spilled in the oceans.

Political environmentalist have done the math on just how much carbon, water, and materials were spent on every process born since the industrial revolutions. Spoilers, none of the numbers are good. Model training is just the latest thing to grasp onto for these kinds of people to play blame games with.

[-] [email protected] -4 points 1 week ago

This responce shows a lack of understanding of how this tech works.

Fundamentally we are still on the same ML algos from the 90s

There isn't any more gains to be had until we totally scrap our current approach and invent a new kind of ML that nobody has even started working on.

Please stop treating a robot like a god. It's cringe.

this post was submitted on 26 May 2025
20 points (88.5% liked)

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