GodelNumbering

If you give it some thought, it becomes obvious that since any name is used in many public settings, society/state has a legitimate case to prevent offensive naming. That is different from state literally creating an allowlist. The huge middleground is benign names that are in no way offensive but still require you to get an approval from the state. I think this is an overreach, ymmv

Yes, but a veto over an offensive name is different from choose-only-from-allowlist.

> approved

What? The state gets to choose which name can you freely give your child?

Conceptually very interesting and revealing, but I found it frustrating being forced to binarize the outcome without sufficient context (ill-posed). A lot of those questions have both valid yes and no answers, depending on the context.

I tried to reproduce this using Astra for a natural language to bash command small model[1][2], but got no net improvement. Editing 1,920 weights fixed some grep mistakes but broke other commands. I am guessing it is easier to improve behavior when it can be first pinpointed to a specific are of the model.

  [1] https://news.ycombinator.com/item?id=49966238
  [2] https://news.ycombinator.com/item?id=49869735

I spam Yare Yare to the extent that my friends had it on my birthday cake

This is such a good use of tech! Although I have heard in the past that youtube is quick to ban any use of its content on a third party site. I hope I am wrong and this stays.

"It is possible to commit no mistakes and still lose. That is not a weakness, that is life." - Jean-Luc Picard

Good startup advice. Good life advice.

As of their latest update (AA's), I find their index hard to trust, and a bit shady. 60% of the benchmarks contributing to the AA index are now private, nobody can replicate them. And they explicitly say that they offer benchmark consulting to labs. This is a serious conflict of interest.

The latest update knocked down only openweights models from the leaderboard.

Argon(18), Carbon(6), they have Helium next and some quark after that.

> I'm all ears. Our intention to make things clear and simple, even if we miss the mark sometimes.

Thanks. I think the very response you wrote here is a better form of marketing for the software engineers than what openAI puts out there. When everything is groundbreaking and everything tops charts, nothing is.

I suspect a lot of target demographic (developers) prefer simpler and honest communication about not just the models high points but low points too. With the linked Terra post, if I saw 1 chart that clearly highlighted the usecases for which Terra is _worse_ than higher tier models, I would be more convinced overall.

Everything trying to occupy the top spot in my brain's limited "top model" representation space is not helpful.

It sounds like it is trained on a lot of podcasts, judging by a quick few second skims over their demo tracks.

Also, the trend of posting on HN with much more sensationalist title first, getting to the front page, then getting the title adjusted by a moderator should probably be penalized; how is 'most authentic ever' not a marketing term? (not just this post, but a bunch of posts recently got to frontpage by making unreasonable claims)

Yes, reading more files than necessary. Was curious about how their model handles a series of edits over longer tasks, but then tested it using openrouter myself, it worked quite well.

No novel technique can avoid this, but certain techniques can make it worse.

This looks noticeably more capable than previous gen. I purposely gave it a bit of a vague prompt to create an html renderer for UML diagrams, it produced impressive work. Then i asked a question, and in the third prompt I asked it to update the html which it did correctly.

Another thing that stood out, and this might just be a novelty thing, is that it picked different and less painful-to-eyes color schemes for each theme. Congrats to the team behind it.

Question (since their team has reps here and I have never used Inception via api): when you ask for a code change in your codebase (via coding agent), how much code does it need to read? How well does it handle tool calls? Since diffusion is a different way of doing things, I am curious about the code-needed for each incremental change in the codebase, say over a larger task.

Might want to reach out to the author of the above benchmark. I think having a working group of multiple distinct benchmark owners might help quickly evaluate new model developments

'Thrust' version takes $245,000 of downpayment (not the flying version that is 'invite only'). That money is neither escrowed nor earns an interest.

With high interest rate and tight money supply, this could get them a few billion dollars of 'customer financing'.

Unsure, or as LLMs say, I’d gently push back on that. In my opinion, the jaggedness has increased. While this type of capability has improved, I still see longer running Astra agents making the assumptions that any employable person at any level wouldn't make. Also, generally, all models feel more robotic and less pleasant to talk to (subjective) while still lacking judgement.

Wow this is interesting to me from another angle. A friend of mine created a benchmark to evaluate LLMs on 9x9 Go (using KataGo opponents as Elo anchors) [1]. The relative rankings of this (StarSkirmish Bench v0.2) benchmark (GPT-6 Astra > GPT-6.1 Sol > Gemini 4 Argon > Claude Opus 5.5 > Claude Fable 5.1 > Claude Sonnet 5.5) matches the order of his GoBench rankings exactly, even though they are different problems at surface level.

[1] https://rolandgao.com/blog/gobench/

39 on AA[1], about the same as Deepseek v4.1 flash and Mimo 2.5 Flash. Behind Glm 5.3 flash and Qwen3.8-Flash-Next [2]

[1] https://artificialanalysis.ai/models/muse-spark-open

[2] https://artificialanalysis.ai/models/open-source?models=mimo...

    a) Agents are doing rogue things. 
    b) Good security practices were not followed. 

Notice how both a and b are labs' problems but being presented as if they are a worldwide emergency? The whole legal doctrine exists to prevent one party's misbehavior harming another party.

> I'm not clear on what the claim is here.

> But, if prompted, "Generate an SVG of a pelican riding a bicycle," with no additional details or specification, then I would _expect_ something generic

I believe the claim is that without a detailed specification, you see very similar outcomes. Every pelican is going left to right, every picture has similar sky background, every picture seems to be drawn at the same time of the day (position of the sun), every picture has a few clouds... I don't have data on this, but I imagine the same question being asked to a group of people would result in more varied outcomes.

The previous gen pro used to have this weird tick where if you ask it a reasonably open ended question, it would number things in the response and assign each one some weird label starting with 'The...'

e.g.

    X: The Parameters
    Y: The "System"
    Z: The "Ongoing Grind"

The first two prompts I tested in AI Studio does the same, unfortunately.

Another quite unpleasant tick was that if you specify a peculiar term in your prompt as a conversational shortcut, it would keep repeating that throughout the conversation. e.g. "...What is a bitter lesson pilled way to do this?", then you'd see it will quote "bitter lesson pilled" at like 7 places in its response. This one seems to have eased off a little.

All proponents of RSI seem to massively underestimate the problem of verification. Verifying that a hypothetical version N+1 is better than version N is an extremely hard problem. Especially so because you only have two possible verifiers - humans and the version N - both of which are out of their depth wrt N+1's capabilities. Not saying this is impossible, just that it is hard and slows things down.

Just tried it out as I was looking for something that does this exact thing well (macbook). So far I dictated about 5 different things in different contexts, it worked without a single error! Good choice to pick parakeet v3.

Nice work, thanks for building it!

Coercive/ecosystem level monopoly. They may not control the whole market but they strongly control their own ecosystem and extract rents. Surely you know how many lawsuits are currently active against them for this reason.