Majromax

> The rocket launch was only achieved through significant ‘manual’ effort on Sol’s part as it papered over its late-game failures to connect certain production systems by repeatedly ferrying supplies between areas of the factory.

Looking through the video, around 12m one can see the Sol trace report the cancellation of a conflicting 'courier' (hand-feeding) script.

Rather than implement 'manual' effort, it seems like Sol considered the Engineer to be just another unit of automation!

That's not exactly within the intent of the challenge, but it's not too far out of bounds either. It's also a hard loophole to close if the agent interacts with the game through a scripting layer.

> Luna < Terra < Sol < Astra, fine. But does Terra 6.1 beat Sol 6? Does Fable 5.1 beat Opus 5.5? If I build something around this Terra 6.1 release, then when Luna 6.2 is released in a month, should I swap?

I understand how it can be confusing, but I don't think that this is exactly a problem.

Luna through Astra offer qualitative descriptions of the model's size. Presumably OpenAI trains its biggest model (Astra-ish, maybe even larger) first, then distills it to smaller sizes.

Verison numbers reflect something about the architecture or training dataset. Again, they keep these details close to their chest, but we should expect that weight-for-weight higher versions should beat lower versions.

This offers us two axes of 'better', but these axes are also not directly comparable. An earlier but bigger model may or may not beat a newer but smaller model. This is where 'spiky' intelligence comes in.

This is also where calls to 'run your own evaluation' really do start to matter. If you care enough about this performance[1], then you also have specific problems that you care about. No generic benchmark can fully answer that question, hence the need for a specific evaluation.

[1] — And you don't have to! A casual user is probably served reasonably well by anything put out in the past six months. I think Microsoft is still serving GPT-4o under some Copilot branding.

Also less useful than one might think at first.

Lots of code "typos" aren't immediately syntactic errors. Misbalanced parentheses, for example, only bite when one needs to close the series. The solution is to go back and fix the original error, but that option is foreclosed to autoregressive LLMs. In the meantime, forcing the model off what it "wants" to generate might make the remaining syntactically valid tokens semantically meaningless, impairing future generation in a way that's hard to quntify.

Constrained generation for tool calls is certainly a type of syntax checking, but it's one that can be justified because the "hard" syntax choices come up front, both in the very format of the tool call itself to the name of the tool and its parameters. Errors are more likely to be detected in the same root-cause tokens that generate them.

> Why would you leave out the form specified by the GP? Representative (republican) government where the 40 members would hold an election to nominate a smaller number of representatives to decide on what should be done and bind everyone to abide by their decisions.

Define 'bind', please.

If my neighbourhood elects representatives who decide that we should all have black trash bins, then how am I 'bound to abide by their decision' if I want to put out a green bin instead?

The problem is moot if the decision is unanimous, since a unanimous decision has no dissent by definition. It comes back with any rule from authority, even if that authority is republican in nature. Note that I said coercion, which is broader than a simple threat of violence; shame and shunning are some of the oldest coercive tactics in the book.

Majoritarian government is great because it offers an easy path to legitimacy, overcoming the 'who died and made you leader?' problem. However, my argument speaks to the leader part of that question, not the you part.

> If you do not have a mandate to govern from the people, you need unanimity from all homeowners. Those are the alternatives.

You don't strictly need a mandate from the people; authoritarian governments can be legitimate despite not having such a mandate. However, it's an impossible trilemma: successful action needs at least one of unanimity (parent commenter's approach), threat of coercion (government), or tolerance of free-riding (charity).

> One thing that's different about Sinai is that it keeps the code author and reviewer in separate agents with separate context. At the time we built it, we suspected that this would lead to better outcomes, but again, we haven't validated that it does.

I use a similar process for a local agent swarm approach (locally hosted Qwen-3.8-27b or Qwen-Flash-Next), used so far for personal-grade projects. Through tool and process accretion, the review stages are told to check both the work and reasoning of the implementation stage, via processing the pi.dev session log.

Through parsing the jsonl log, the reviewer sees the subagent prompt, the tool call sequence, and non-thinking narration along the way. That allows the reviewr to audit the implementer's process (e.g. were tests run?) and spot procedure violations or gross hallucinations. The reviewer also independently runs the test suite, so even a hallucinated pass is caught.

It's relatively expensive both in tokens and time spent running ideally duplicate tests, but the independent workflow has nonetheless caught errors that would very likely have been missed by a same session, same context review.

Funny that we've automated meeting hell. Definitely a truism that we reimplement the org chart in software.

> You would need sufficient evidence to support a claim that NVIDIA intentionally lied, which you obviously don't have otherwise you would have mentioned it in your post.

Would even an intentional lie act to to reset the limitation period here? The hypothetical lie wasn't a deep secret exposed by some whistleblower, it came to light by... reading the vesting agreement. Since AFAIK limitation periods run from "know or ought to have known," I can't see a viable construction to keep the dispute live after 30 years.

> They should just offer to settle at a reasonable value

Since litigation is costly, the acceptable range for a settlement is centered around the expected outcome of a trial, plus or minus each party's cost of litigation (including opportunity cost).

In this case, "the claim is barred by the statute of limitations" implies that the expected outcome of litigation would be approximately $0. The net range for a settlement is then the 'nuisance value' of a lawsuit including any PR damage for airing the case publicly; that would be orders of magnitude below the $1bn claim.

> This feels like an obvious jab at Navier-Stokes, but where we get to shift the numbers around to hide where the compute actually is being spent ... compute is being spent. It's either being spent in amortization to make the search smarter ahead of time, during training, or its being spent after.

I think that argument is recursive? These posts aren't very complicated for either of us, but they're written on devices that are fabricated with billions of dollars of semiconductor equipment. At what point do we just acknowledge that we stand on the shoulders of giants?

To me, the distinguishing factor is that the expense not special-purpose but upfront. The model here is trained without foreknowledge of what problems it will solve. Solutions like nine loops are genuine expressions of a pre-existing model capability, even if that capability has not pre-existed for very long.

I can't speak for the authors' mindsets, but the Stars! map had pointwise movement rather than via strict stellar/planetary waypoints. When fleet interceptions can happen midcourse[1], there's not a whole lot of design room within the Win16 style.

[1] — If I remember correctly, there even was some special-case code for ship pursuit cycles.

Wasn't the shareware version fully featured, such that only the key was necessary?