lucamark

Exactly! And they should also release the new inference engine in this month. Anyway, I am curious to try Opus 5, considering that previous versions (e.g., 4.8) were disappointing

But why GPT 5.6 Sol is so behind on the benchmarks? In real-world projects, it is the best frontier model to me in terms of accuracy, speed and consistency. It can just be compared to Fable 5, but I prefer GPT 5.6 Sol because of inference speed.

I've never trusted on model cards though. I'm sorry.

A month ago I posted Modeloop here, a visual environment for designing control systems (https://news.ycombinator.com/item?id=48543968).

In the comments,boscillator wrote:

"I'm always saying Simulink needs a text-based interface. Same signal flow programming model that supports scopes and continues time integrators, just with text instead of drag-and-drop." (https://news.ycombinator.com/item?id=48598291)

This has been on my own list for a long time too, so I built it. It's called MDL (Modeloop Description Language).

Every diagram now has an equivalent textual form, and the two stay synchronized in both directions. This allows users to decide if to create and modify diagrams as blocks on the canvas or as MDL text.

Curious what HN thinks — and boscillator, if you're around: this one's on you.

For firmware RE this would be most useful if every guess is tied to evidence

Using power as feedback is neat because it works when you can’t instrument the target but I wonder how they separate new behavior from boring analog noise, e.g. the clocks

I’d like to see which parts of the assurance case are language/toolchain dependent versus plain old process, tests and traceability.

Remember that such models are available to us thanks to NVIDIA GPUs

Never had rejections in the short time Fable was available

Agree. It is a mediocre model, expensive while not being a frontier

Wrong! Look at it better. It shows that Opus has superior performance but at higher cost.

You're referring to the Agentic search, but if you look at the Agentic computer use the cost is basically halved.

However, I am also confused about market positioning. Too expensive to perform daily tasks - open souce models are much cheaper - and not frontier model to address complex real world problems.

Rarely used Sonnet btw.

I checked before posting but I didn't find it

OpenRouter?

> In other words, the Trump administration appears to be pressuring OpenAI to do what Anthropic is already voluntarily doing: keeping its most powerful AI models under wraps.

while I generally agree that models with this level of cyber capability should not necessarily be released to everyone on day one, if a company or developer can meet compliance requirements, they should be eligible - and eligibility should not be based on nationality.

Your point is interesting! And with a Mythos-class model already on the market (e.g. DeepSeek or GLM), will OpenAI and Anthropic be forced to apply the same policy?

Uh great! I haven't seen these posts, thanks for the links :)

Expections occur

In many other european countries, the story doesn't change much - with some exceptions. The irony is that the EU is now discussing EU Inc. a law to let startups incorporate online within 48 hours, for at most €100, under a single optional corporate framework across Europe.

That is exactly the right direction. But for now it is just a proposal

Do you think that stuffs are different in Italy, Spain or France? Just to cite some others

Europe will suffocate under the weight of its own bureaucracy. The sad thing is that it is not new to me, I've heard so many stories like this one. This is the kind of friction that makes founders incorporate elsewhere.

Also, a founder spending months coordinating lawyers banks and tax advisors is not talking to customers or building the product. The opportunity cost here is huge.

Anyway, you are pretty close. One more push, don’t give up. :)

That's bad for ETF owners too. Funds will be legally forced to buy a tightly restricted supply that will pump the price even more

Let's grab some popcorn.

- Price/Sales about 128x (NVIDIA had a peak of a 40x at its peak)

- Bought Twitter per 44 billions. Inflated its valuation to $250 billion just by integrating it into X.AI

- EnterpriseValue/EBITDA about 219x (30x for scaleup business) and negative Price-to-Earnings

- Low free-float trick (minimal public shares available)

Even the market efficiency hypothesis struggles to justify it