They don't say that you should feel bad. The author simply says that the characteristics and unreliability of LLMs make them unfit to be implemented in the Vivaldi browser at this moment. They even close off the article with a positive sentiment about the future of the ML field. They don't burn any bridges there.
> While they do this, they also use vast amounts of energy and are happy using all the GPUs you can throw at them which is a problem we’ve seen before in the field of cryptocurrencies.
But is he wrong?
What does "a lot of energy" even mean? It's meaningless. Do they use too much energy for their usefulness? If they did, people wouldn't be using them.
Like with LLMs, some of us do. But still there are places in the world where one is imprisoned without car. Which is not case with LLMs (yet).
Cars enable long-distance travel, which in many parts of the world is now essential for survival, and often that is, ironically, a result of climate change.
LLMs do nothing to aid human survival. In a post-apocalyptic world, cars would be sought after for both transport and shelter, but nobody would give a care that we lost ChatGPT.
Cars use more energy than LLMs because most of the world is built around requiring a car to get to places.
It's not that we don't mind it; quite the contrary, in fact, as we're always reminded of when the price of gas/petrol shoots upwards.
When the cost of living forces you to live 45 minutes away from your job by car because living within walking distance is astronomical, many folks are conditioned to want a house with a garage "for the kids" because apartments are "for the poor," and EVs, in their current state, are not financially feasible yet (though that is changing!), it's more that we're forced to tolerate it.
I know people don't mind the cost relative to the value they're getting, because if they did, they wouldn't use LLMs.
I think it’s fair to ensure that you create something that isn’t subject to possible quotas in the future
There's plenty of documentation on that directly from the source (openai, etc.) and elsewhere.
> While they do this, they also use vast amounts of energy and are happy using all the GPUs you can throw at them which is a problem we’ve seen before in the field of cryptocurrencies.
> While they do this, they also use vast amounts of energy and are happy using all the GPUs you can throw at them which is a problem we’ve seen before in the field of cryptocurrencies.
"Vast amounts of energy", "happy using all the GPUs you can throw at them", and then the random cryptocurrency reference to evoke all the bad stuff associated with those.
Edit: I do think you're making a fair observation, I just feel there are a few reasons not to draw too strong of a conclusion from it
> Despite all this, we feel that the field on machine learning in general remains an exciting one and may lead to features that are actually useful. In the future, we hope that it will allow us to bring good privacy-respecting features to our users with a focus on improving discoverability and accesibility.
Edit: yes it does make mistakes, but it takes vastly shorter amount of time to find them rather than writing something from scratch.
To me, it feels like there will definitely be features or even entire products out there that wouldn’t exist without something that lowers the barrier of entry far enough for someone to overcome the zone of proximal development: https://en.m.wikipedia.org/wiki/Zone_of_proximal_development
Just the other day I was able to introduce some custom ESLint rules into the project to make the import names match the filename (e.g. when someone renames a Vue component but the import names don’t change or you don’t notice those usages, so you end up with bunches of <OldComponent /> all over the place). I wouldn’t have had the time to do so without ChatGPT/GitHub Copilot nudging me in the right direction and giving me examples to work off of, because frankly my searches for about 15 minutes didn’t turn up anything either.
Clearly that counts for something because nobody in any of my projects had done that previously, now it’s obvious that basically we need a local package added to the project (in package.js) but also that we can store it in the file system and just use the file: syntax. It was much the same story with some .cjs Node prebuild scripts that remind the developers that they should make examples of the new components they make in a development showcase page and so on.
Aside from that, LLMs are useful for boilerplate stuff (hello, ASP.NET and Spring Boot), as well as simple one shots when you don’t want to rack your brain coming up with a particular RegEx, amongst other cases.
If someone wants an LLM in the browser, good for them! If someone doesn’t want to add them to their browser project, that’s their rightful choice.