i doubt that's the goal for them. i bet they just really don't have capacity for people using it a ton, yet they wanted people to be able to try it out while it's new. so they compromised and made it temporarily available. and then hope they can get costs down or capacity up so they can make it more available again
I think the goal is "private citizens: subscriptions; corporations: per-token billing." It's getting people addicted to LLMs on cheap subscriptions so that they can then force companies to pay for expensive inference.
sounds like the link with AI is tenuous at best given the other comments, but I'll take it as an opportunity to say a few things I believe anyway:
1. AI is really helpful for a lot of things
2. to the extent that AI can do something perfectly for us, we probably shouldn't try to force people to "learn" it the hard way
3. people who don't want to learn won't, and will suffer naturally later
4. if the material didn't need to be learned anyway, then using AI to do it for them is a win. that's how the real world works anyway.
5. if AI makes some knowledge obsolete, we should stop trying to teach it.
i think the only thing for the teachers to do is to properly warn students of the consequences of using AI to skip learning ahead of time (because by the time the natural consequences hit, it's too late), and to do their best to devise tests that incentivize the right knowledge, while also showing how to use AI properly.
the problem is that the education system isn't set up to change this quickly so I don't really know how they are going to properly adjust every semester
i guess i don't blame a writer who's job is threatened by this technology to write a piece like this. but the perspective is ultimately one where they are complaining about how it affects them, without regard to the end user.
it's the same as toll booth operators complaining about fastpass
As a user I hate google's approach as well, not because of job related reasons, but the functionality keeps changing to no increased value to me. I don't see how you the end user would have a different opinion unless you did not use google before say 2016.
As a user I actually appreciate it. But most of the stuff I google is coding questions.
Before if I asked a question, the top 3 results would be StackOverflow. I'd click into the first one and find out that the question was subtly different than mine making its answer useless, but it included a lot of similar words. Go back and click into the second one. It's exactly my problem, asked three years ago, no answer. Go back and click into the third one. Same question, but it's been answered. Great. But the accepted answer has a score of -3 and another answer has a score of 5. So which one do I follow? Whoops, it's actually neither of them, because the library has broken both of those workflows.
Now I get my answer right away 90% of the time. And if I don't then I scroll down and I'm not worse off than I was 2 years ago.
Yes, the churn they bring to products that were complete over a decade ago is ridiculous. So much change for change’s sake (or more likely in pursuit of promotions internally) and so little thought to quality, what makes a product good, and what would make users happy.
They try to offer some other perspectives as well:
> This isn’t just a me problem. You don’t have to be a writer to have your livelihood be dependent upon Google search results. Small-business owners need Google to reach potential new customers. Students, many of them working on school-issued Chromebooks made by Google, need it to research term papers and study for final exams. In its earliest form, Google dot-com was the perfect utility for all of these people and millions more.
But I agree with you (despite being predisposed to agreeing with the author) that the invective doesn't quite land because they don't do quite enough work to ensure we're on their side in understanding how we might be affected.
I'll just take this space to note that folks that feel similarly to the author should try Kagi, as they let you choose how much AI you want rather than forcing a chat interface onto you or directing you away from links.
> i guess i don't blame a writer who's job is threatened by this technology to write a piece like this
> it's the same as toll booth operators complaining about fastpass
I think your analogy would work better if toll booth operators built the roads, the cars, the toll booths themselves, and then were all replaced by fastpass.
sure, there is some bitching about how the ad funded web-site-news business model is getting distrupted. I'm not completely heartbroken about that.
but much of the article describes how Google is trying to deploy their final solution for intermediation. their attempts to 'googlify' things like grocery shopping and job searching pretty much failed. but now, they are promoting a model where, finally, all information they present has been googlified. they are not a phone book or card catalog, but now the entire library. there aren't original sources any more, just what Google has decided to tell you about something.
It's more like a company unaffiliated with the toll booth offering a better deal that lets you avoid the toll booth, pocketing all the money, and the road becoming unusable from lack of maintenance.
this was definitely me in high school. i still fondly remember the day when we could use our Ti-83+ for our exam but we had to show the teacher that we cleared memory for notes and formulas.
So i wrote a program that just made it look like I cleared memory and it worked like a charm.
I don't remember if I even stored anything that could be constituted cheating but it was more about the satisfaction of knowing I outsmarted them, heh.
I think it's the least hostile thing they can say, and I respect their decision for their own project.
That said, it still feels like they are unnecessarily hobbling their project. LLMs are tools and they can help you think, research, and code. You can overuse them, yes, but you should embrace them where they help.
not accepting bun's PR for other reasons is totally fine (sounds like it's a core change where more thinking needs to be done), but simply banning all LLM authored PRs is unnecessarily restrictive. Just focus on the quality of the work.
Why review thousands of lines of LLM generated code from some random person you don’t know when you could use an LLM yourself to do the same thing, except with probably a better design and more thoughtful approach?
Maintainers should get to spend their time developing stuff, not just reviewing low effort PRs. The flood of LLM code is changing the balance for the worse for maintainers, and I can totally see why they’d just want to ban it.
But at least you know how the sausage was made by the end. You have no idea how high or low quality any PR from a random person online is, and taking any amount of time to review a PR could be a total waste.
if someone made the same gigantic mess of a PR without LLMs, it would still be rejected, because it is a gigantic mess of a PR.
the low effort part is the problem. what if i made a great, focused, readable PR but had claude write it out? what if i carefully checked and deliberated each line, just as if i had written it myself?
granted, in the real world, 99.9% of slop PRs are written by LLMs. so i thought "okay, reasonable, ban the thing that is most likely to cause problems."
but then how does the "no LLM translators!" rule fit into that view?
It’s the lack of friction that LLMs bring. It’s easy to put in a couple of lines and generate 1000’s of lines of code. Whereas the person would never have done that without LLMs.
I think LLM dev needs to take a better spec driven approach. The vibing is getting to be annoying.
I think the only thing that will save us is smarter models. Slop coders are not going to stop making slop.
They’ll still use even smarter LLMs badly no doubt, but I’m thinking that maintainers of open source projects will be able to more effectively use LLMs to review potential PRs to weed out the truly bad ones quickly.
I guess they could setup a competent openclaw pr review agent. The problem is again - cost. Who is paying for the token usage by open source projects? How many tokens before they exhaust their quota with junk PRs?
Well previously lazy contributors simply would never have made a PR because it was too much work. Now they can have an LLM make a PR with virtually no effort at all.
It’s obviously an imperfect rule, and maybe it’ll change over time. But I am just saying that I understand why open source maintainers are doing this.
There is just no possibility for them to review all the low effort AI slop being thrown their way. Yes, some of it is going to actually be very high quality, but you don’t know that until you review it, which is the whole issue.
Agree, but "no LLMs" locks out good PRs and contributors too.
I hypothesize it may have roughly the same effect as denying all contributions where the author used intellisense 10y ago.
A substantial portion of people who write good code will be using some sort of LLM assistance, even if it is just something like Cursor Tab (autocomplete).
Yes, you'll also hit all of the spammy PR "contributors", but you'd also do so by prohibiting all contributions by people who have a belly button
As per OpenAI themselves, xhigh is only necessary if the agent gets stuck on a long running task. Otherwise it’s thinking trades use so many tokens of context that it’s less effective than high for a great majority of tasks. This has also been my experience.
reply