or just tax wealth and profit instead of income and tools. these are neither new ideas nor are they specific to the proposed llm-based worker replacement
I am not scientist enough to judge this, so please someone enlighten me: most categories i've read through that find a shift do so with an increase of about 0.1-0.2 standard deviations. that does not sound significant to me. is that enough to make the claims this study makes?
Statistically significant does not necessarily mean practically significant. If you just increase your sample size sufficiently, you can measure a significant effect, despite having a small magnitude of the measured effect:
https://en.wikipedia.org/wiki/Power_(statistics)#:~:text=Sta...
considering this is a review aggregating a bunch of small n studies from before we acknowledged the replication crisis in psychology, I'm going with "no"
the article mentions three types of stakeholders: contributors, debuggers and incident responders. it entirely fails to mentions consumers, who mostly care about backwards compatibility of changes, and thus about the type of a change. once the type is established, e.g. a change is breakimg, the consumer next cares about the scope to make downstream adjustments.
the part about broken promises regarding breaking changes is _kind of_ fair, but only assuming tooling isn't able to track reverts. accidental breakages occure with every approach and better to have an approximation than no information at all.
I've always wanted to do this, but can't get over the linux tty only supporting 256 colors. If I could get that higher and maybe add unicode support, I'd love to go tty only.
I agree that a `gh stack` command is not needed, but this feels to me like just a better UI feature for a good git workflow. It literally is about making multiple smaller PRs that build on top of each other.
The question is, why are you not just merging them into main as you go? It's a bit of a smell when you "need" to merge branches into branches. It shows a lack of safety and ease in deployments, which is the real problem to solve IMO.
Stacked PR’s… don’t do that though? They’re just PR’s. You can merge just the first one in the stack, and now it’s not “all or nothing”. Reading the docs, I don’t see a way to signal that the PR’s must all merge together.
Because the most natural way of saying “these changes need to land atomically” is called a branch, and landing it atomically is called a “merge”. But I guess GH’s UI sucks for reviewing large changes, so we’re stuck having to make each change independently mergeable and pass tests (likely disabling dead-code lints, etc) just to work around this limitation. Sigh.
At least when I actually do want changes to be mergeable in a stack, I now have a better UX for having folks review them.
it is difficult to comprehend for me that soneone spends all this time thinking through and calculating how to harness as much energy as possible and then wants to use it for large language models instead of something useful, like food production, communication, transport or any other way of satisfying actual human material needs. what weird priorities.
Whether you like it or not, we are burning a lot of electricity on datacenters. That is a fact. And energy consumption is likely going to significantly increase in the near future. If we can reduce that energy usage, that is a good thing and a big improvement.
I do not think I even understand your complaint. Different people can work on different problems. We do not have to pick only one.
LLMs and other IT applications have the distinct advantage that they require no other raw materials as input, aside from initial setup, extension, and maintenance. Under these conditions the requirements essentially boil down to real estate and high bandwidth internet connections. Also, demand for AI is currently so high that the solution can be scaled up far enough to be viable.
All the other concerns require more subtle approaches because human requirements are much more messy.
demand for AI is not high, which is the current problem of the industry and the reason that AI companies are trying to shoehorn their technology into products everywhere.
these companies and the author of the article are trying to increase capacity for something that barely anyone wants in the software they use, which makes it all the more wasteful.
I agree, the author seems wildly optimistic that all that capacity will indeed be needed in the long run. But I personally hope that it will lead to a breakthrough of solar and battery storage even if demand for AI tanks. If that happens, one could still shunt all that solar energy to other places, either with alternators and overland lines, or by shipping charged grid scale batteries via train.
Tell that to the 1000-watt space heater in the corner that i tasked with upscaling some old home movies! Four GPUs worked very hard all night to get footage of my first dog up to 1080p. My living room is a little warm this morning.
Well, I've never seen anything written by AI evangelists that doesn't sound like it was written in day three of an adderall binge. This essay is no different.
Sometimes (often) solving the problem is the most fun part, regardless of how it’s used.
The scale of AI energy consumption is quite unique from what I heard, and there’s a lot of money flowing into that direction. So that seems to me a decent reason to think about that.
I haven’t heard yet that food production is constrained by these kind of things.
It appears to make that you’re just taking a cheap jab at AI.
I don’t think that’s a great description of what’s going on here. I think there are two things:
1. The actual thing the authors spend a lot of time thinking about seems to be more generally how to make good use of solar power for things that people find valuable – synthetic fuels desalination, etc – and the implications of the sun only shining some of the time – maybe you don’t want to pay more for more efficient systems as then you want steady power which is more expensive.
2. I think the blog post is a bit of a response to lots of public discussion about AI data centres. IMO seems better to see what someone who thinks a lot about energy has to say than eg, a government suggestion that you delete old pictures to reduce water consumption.
I share the reaction but I'm also aware how easy is it to inventivize (aka subsidize) ineffective old processes in the name of "productive" priorities. The problem is not LLM/DC, the problem is food production, transport and communications are not sexy in a "post-scarcity" (entitled/distracted) societies. People take too many things for granted
>instead of something useful, like food production, communication, transport or any other way of satisfying actual human material needs. what weird priorities.
You realize that even pre-AI, that this complaint would still hold for most of tech? Adtech, enterprise SaaS, and B2C apps are hardly "actual human material needs". Even excluding tech, the next lucrative sector would be banking, and same complaint would be applicable. In other words, this is a decades (centuries?) old complaint, repackaged for the current thing.
Food distribution is still a problem in vast part of the world.
Handling food waste is another issue.
Climate related shortage are coming soon for us (at the moment they only manifest as punctual price hikes - mustard a few years ago, coffee and chocolate more recently, etc...
I don't know if the electricity going into compute centers could be put to better use, to help alleviate climate change impacts, or to create more resilient and distributed supply chains, etc...
But I would not say that this is "not a problem", or that it's completely obvious that allocating those resources instead to improving chatbots is smart.
I understand why we allocate resource to improving chatbots - first world consumers are using them, and the stock markets assume this usage is soon going to be monetized. So it's not that different from "using electricity to build radios / movie theater / TVs / 3D gaming cards, etc... instead of desalinating water / pulling CO2 out of the air / transporting beans, etc...
But at least Nvidia did not have the "toupet" to claim that using electricity to play Quake in higher res would solve world hunger, as some people claim:
It feels like you didn’t read your own link as he somewhat addressed your concern directly. The idea is simply that AI investment is an “up front cost” to future improvements. To debate against it you would have to provably explain why you think AI will not advance other technologies whatsoever.
I usually don't try to prove things won't happen. I leave the burden of proof to the salesmen. In this case, they have extraordinary claims, so as the saying goes, I wait for extraordinary proofs.
