I think the idea is that it's completely declarative, and the range of what you can do, being constrained to a set list of operations and targets, becomes clearer and easier to understand?
I had that exact problem, but I've been working on a fork of another tool to try to improve the situation. It isn't a clone of magit, but it has a basic form of the same type of command interface, with a lot of the same benefits (easily seeing the tree of nested available commands and activating them with single letters, seeing what's going on with your repo live, WYSIWYG, and editing it with those commands). It's single-handedly allowed me to switch from git to jj without feeling lost
This kind of logic only works if the percentages for each industry are all equally that small, so you can treat them as all equally bad, but they are absolutely not.
The single biggest non divisible sector you can realistically come up with is "personal transportation", but even that is only 10% of global co2. You can look at other sectors like "industry" and "energy" and I can guarantee you will be able to easily split things down into sub categories which have <5% impact on global co2 emissions.
But they didn't split it up like that. They said all data center emissions irrespective of what those data centers are used for — which can be an extremely wide variety of things since data centers basically run our entire network information internet economy. That's much more like saying all transportation emissions instead of splitting it up by type of transportation. Yes, that doesn't include the full life cycle emissions of creating the data centers. But I'm pretty sure that transportation, as a proportion of emissions, doesn't also include the full life cycle emissions of producing the cars, trucks, boats, and airplanes in the first place.
Also, I think it's worth pointing out that the sectors you list are like 1.5 to 2x larger than the one he gave and the largest nondivisble sector, you listed is literally 10x, which I think does more to prove his point than yours.
Also, by your logic, literally any new sector of the economy that uses any amount of energy, basically at all, should be banned, because it "all contributes." that's a consistent position to take and there are certainly people that hold that position, but that at that point seems like a fundamental axiological difference that I and probably OP are simply not going to agree with you on.
Also from that exact same study (why not cite the actual study? It's quite readable) the LLMs couldn't recite more than a small fraction of many other books, often ones just as well known[0] — in fact, from the bar charts shown in the exact news article you cited, it's pretty clear that Sonnet 3.7 was a massive outlier, and so was Harry Potter and the Sorcerer's Stone, so it really seems to me like that's an extremely unrepresentative example, and if all the other LLMs couldn't recite even a small fraction of all the other books except that one outlier pairing, despite them being widely reproduced classics, why would we expect LLMs to actually regurgitate regularly, especially a relatively unknown open source project that probably hasn't been separately reproduced that many times?
Not to mention the fact that, as the other commenters mention, that appears to just... not have happened at all in this case, so it's a moot point.
I am going to be adding opinions (OpEds) from myself and guest writers around cultural decay, the decline of the internet, tech news etc. I do not want to make another reddit. I do not want to make another infinite scroll. I do not plan on making money from this. I'll take the hit. The internet is dying, at least I can try and help us before it's completely gone.
Perhaps killing the corporate internet would be. The ability to connect to people from all over the world was improving society at an astronomical rate before virtually everyone was brainwashed by money-making addictive algorithms
I think the problem is that because it talks and understands English and more or less does whatever you ask, the affordences aren't particularly clear. That's actually one of the biggest problems with the chatbot model of AI — it has the same problems as the CLI, in that it's extremely flexible and powerful and you can do a lot with it and add a lot to it, but it's really not clear what way of interacting with it is more or less effective than any other, or what it can or can't do well.
I think attempts to document the most effective things to ask it to do in order to get to your overall goal, as well as what it is and is not good for, is probably worth doing. It would be bad if it turned into a whole consultant marketing OOP coaching clusterfuck. Yeah, but building some kind of community knowledge that these things aren't like, demigods, they have limitations and during things one way or the other with them can be better is probably a good thing. At the very least in theory would cut down some of the hype?
I think it's nonsensical to insist that it would only be a subjective improvement. The tests either exist and ensure that there aren't bugs in certain areas, or they don't. The agent is either in a feedback loop with those tests and continues to work until it has satisfied them or it doesn't.
Red-Green TDD is one of the main "agent patterns" Simon proposes, so it seemed relevant.
Also, the same thing applies to feedback loops with compilers and linters as well: they provide objective feedback that then the AI goes and fixes, verifiably resolving the feedback.
Even with less verifiable things like using specifications, the fact that it relies on less objective grounding metrics doesn't mean there's no change in the model's behavior. I'm sure if you looked at the code that a model produced and the amount of intervention necessary to get there for a model that was asked to produce something without a specification versus with one, you would definitely see an objective difference on average. We're already getting objective studies regarding AGENTS.MD
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