Ok, first off, I’m a big fan of learning new expressions where they come from and what they mean (how they came about, etc). Could you please explain this one?:
well, you dance and jump over the fire in the bank’s vault.
And back to the original topic:
It isn’t resource efficient, simple as that.
It’s not that simple at all and it all depends on your use case for whatever model you’re talking about:
For example I could spend hours working in Photoshop to create some image that I can use as my Avatar on a website. Or I can take a few minutes generating a bunch of images through Stable Diffusion and then pick out one I like. Not only have I saved time in this task, but I have used less electricity.
In another example I could spend time/electricity to watch a Video over and over again trying to translate what someone said from one language to another, or I could use Whisper to quickly translate and transcribe what was said in a matter of seconds.
On the other hand, there are absolutely use cases where using some ML model is incredibly wasteful. Take, for example, a rain sensor on your car. Now, you could setup some AI model with a camera and computer vision to detect when to turn on your windshield wipers. But why do that when you could use this little sensor that shoots out a small laser against the window and when it detects a difference in the energy that’s normally reflected back it can activate the windshield wipers. The dedicated sensor with a low power laser will use far less energy and be way more efficient for this use case.
Cheers on you if you found where to put it to work as I haven’t and grown irritated over seeing this buzzword everywhere.
Makes sense, so many companies are jumping on this as a buzzword when they really need to stop and think if it’s necessary to implement in the first place. Personally, I have found them great as an assistant for programming code as well as brainstorming ideas or at least for helping to point me in a good direction when I am looking into something new. I treat them as if someone was trying to remember something off the top of their head. Anything coming from an LLM should be double checked and verified before committing to it.
And I absolutely agree with your final paragraph, that’s why I typically use my own local models running on my own hardware for coding/image generation/translation/transcription/etc. There are a lot of open source models out there that anyone can retrain for more specific tasks. And we need to be careful because these larger corporations are trying to stifle that kind of competition with their lobbying efforts.