No. Balk = stop and return on your steps. He was moving towards ”migrating more than 14000 PCs in public administration to Linux”, Gates and Ballmer tried to make him stop, but he continued on his path.
In this case, willing to proceed with what he was planning to do, that is, moving from Windows to Linux against Microsoft's wishes.
edit: And you're right that this implies "balking at Microsoft's proposal". Personally, I did read the sentence as intended ("they wanted him to balk (= stop his plans), but he did not"), but I can see how the phrasing can be misleading...
Merriam-Webster has balk as to stop short and refuse to proceed. To understand the intended meaning, put the emphasis on the first part: If the mayor did not balk, he did not stop, that is, he refused to comply and proceeded with his plan.
> Merriam-Webster has balk as to stop short and refuse to proceed. To understand the intended meaning, put the emphasis on the first part: If the mayor did not balk, he did not stop, that is, he refused to comply and proceeded with his plan.
I feel like one of us is extremely confused.
"Balk" = "stop" = "refuse to proceed", right?
So "<did not> balk" = "<did not> stop" = "<did not> refuse to proceed", right?
"<Did not> refuse to proceed" with Microsoft's proposal therefore means he in fact complied with Microsoft's proposal and did proceed with it, right?
You want to prevent the transition from a GPL codebase with some public domain code to a public domain codebase with some GPL code. One way to do so is to outright ban contributions leveraging tools that are able to generate public domain code at superhuman speeds.
As you pointed out yourself, there's always the option to create a fork that does allow AI contributions, which may eventually force a re-assessment of the policy if the gap in utility grows too large.
> You want to prevent the transition from a GPL codebase with some public domain code to a public domain codebase with some GPL code.
That would take a very long time if contributions are reviewed etc. By then any legal ambiguities would be clear.
> a public domain codebase with some GPL code
which would still be a GPL codebase
> One way to do so is to outright ban contributions leveraging tools that are able to generate public domain code at superhuman speeds.
Can they generate code that would pass the quality standards, and pass the processes, of a project like this at superhuman speed? There is a separate requirement that contributors must be able to understand code and answer questions about it so a human would have to review code before even trying to contribute it.
> As you pointed out yourself, there's always the option to create a fork that does allow AI contributions, which may eventually force a re-assessment of the policy if the gap in utility grows too large.
1. if you are right that LLMs will do well enough to create a huge gap, then that is inevitable.
2. if you are wrong about that then it is unnecessary to try to stop it.
That specifically states “works created solely by machines” so probably doesn't cover AI-aided work? Though where you draw the line there is likely to be something that'll tax legal budgets for years to come…
From the 2025 Report on Copyright and Artificial Intelligence [1]:
> The Office concludes that, given current generally available technology, prompts alone do not provide sufficient human control to make users of an AI system the authors of the output. Prompts essentially function as instructions that convey unprotectible ideas. While
highly detailed prompts could contain the user’s desired expressive elements, at present they do not control how the AI system processes them in generating the output.
Again, that seems to be talking about fully AI generated work, like “works created solely by machines” from the previous document, not AI-aided work. It is only stating that the prompt is not considered sufficient human work because it comes before the generation process, but it says nothing of subsequent editing of combining with other stuff.
The really annoying part is how the copyright lawyers have zero respect for the work of human review and refinement. Reviewing, editing and refining AI code isn't authorship, it's "adoption", they say. Repeated iteration is just rerolling the dice, they say. Not enough to make it copyrightable, they say.
Meanwhile all the actual programmers demand that you spend effort constantly reviewing and iterating on the AI's work so the project doesn't turn into slop.
Damned if you do, and damned if you don't. Maybe the best course of action is to opt out. Copyright is irrelevant if the software isn't published. So much for our precious commons.
The first paragraph talking about reviewing, editing, and refining, is literally the job of a Literary Editor when working with an author on their literature.
Editors do not have any IPRs over the resulting literary work.
Following that simile, the AI is the "author" and the developer is the "editor".
Given that an AI cannot be an "author" under copyright law, there is no copyright in the final product.
Note that humans do come with different types of 'input streams':
Hit my knee in the right spot, and I'll kick my leg, no choice about it. Scream at me to LIFT MY EFFING LEG (in a language I do understand), and I may or may not do so. Write the same thing on a piece of paper, and I generally won't (unless there is some very specific context).
With AI systems, we have the benefit that the distinction between such pathways is in principle under our control.
> Not after the pathways are tokenized and enter the model. There's no internal separation. There's no internal separation. It's not possible, either.
That's not accurate in the slightest. Steering vectors, SAEs, circuit breaking, activation patching, ablation, etc. are all old hat. Of course that's all irrelevant, because that's not what he's talking about. You control tokenization. You control what data is available to a model. You control how it enters the model. An LLM isn't some daemon outside of space and time, it's a normal program that works with byte streams.
Which is true as a tautology, but not in the way you mean. The problem isn't the hijacking of classifiers, that's incoherent. You bypass a stochastic classifier to hijack the reasoning model, and potentially bypass the stochastic classifier sitting on the other end.
I think the argument you may be trying to make is that it's not something where we can easily build a general, one-size-fits-all solution in a first-order system. My response to that is that it's already solved, inductive logic programming has already proven its generality. The problem is the non-elementary search space, so it's really dependent on whether or not we discover semantic models for SOL with better heuristics than what we currently have. Of course at that point, this branch of ML is effectively dead anyways.
Until then, you can still do it if you actually control your inference pipeline, it's just something you have to engineer for a specific environment.
Demonstrations of failure: every cult, all propaganda, indoctrination (both military and dictatorial), authority bias, Asch conformity experiments, and the fraction of the population more susceptible to hypnosis.
I'd argue there's a qualitative difference between using machine learning for specific data analysis tasks, and using a generic agentic AI system controlled by some corporate entity. The association of the term 'AI' with the latter is increasing.
Yes, but nozzlegear claims that even technically "intertwined" (presumably they mean "inclined") people don't know the connection between LLMs and the broader ML work that encompasses it. That's a pretty big claim, and would be rather shocking if true. ML and deep learning were heavily invested in and discussed through the 2010s (and earlier, but the hardware developments at the end of the 2000s enabled the ML boom of the 2010s), is our industry really so memory constrained (I know there's a shortage now, but still) that people don't know the connection between machine learning and LLMs?
> but nozzlegear claims that even technically "intertwined" (presumably they mean "inclined") people
Sorry, I meant the subjects (LLMs, ML, AI) are intertwined, not the people. But what I was getting at with my comment is that (IMO) most people see them as distinct things, even on HN where most know that LLMs use ML. As an analogy, it's like physics versus mathematics: separate subjects in most everyone's mind, and even separate academic departments, but physics is still math.
It's a matter of definitions, but I can at least understand someone wanting to make a distinction between reactive and non-reactive 'AI' (such as data filters).
There's overlap and edge cases, though: Maybe you have a program that summarizes texts. One could argue that's no different from a passive filter. But can you then ask questions about the text? That's unquestionably AI.
Depends on what you mean by the term: Some companies are in the business of supporting game studios without being game studios themselves (eg animation companies you outsource your out-of-engine cinematics to). If all your customers are game studios, you could be argued to be a 'game (support) company'.
Are the majority of Adobe's and Autodesk's customers game studios? Because that was the basis of the argument that was being made.
And just to clarify, personally, I would not describe JangaFX as a game company myself (as you pointed out, they aren't in the game business per se, but the visual effects business) - I'm just trying to clarify why the claim isn't completely outlandish.
Dunno it's just weird to say you're in the business of who you sell to instead of what you sell.
A caterer that only caters to oil camps isn't suddenly in the oil business, for example. To take an easier to understand example.
Or my brother in law runs a company that does CNC machining and sells to Airbus. He's not suddenly an aircraft manufacturer, even though his parts make it onto planes.
Shrugs. I have no issue with someone claiming that a company making drills used exclusively for oil drilling is in the 'oil business'. However, I would not call such a company an 'oil company', so I take your point...
Phrased differently, they claimed that the entropy of the distribution of some quality metric tends to be higher on the domain of projects with vibecoded sites compared to the domain of projects with handcrafted sites.
1: to refuse abruptly
2: to stop short and refuse to proceed
Per Cambridge Dictionary, it means:
to be unwilling to do something or to allow something to happen
So "He did not balk" can be read as "He did not stop" / "He was willing to let things proceed"