user43928

I read earlier that the crime is making such threats in any manner where another person could see them.

I do not know whether it matters if the suspect knew that their chats could be viewed by Anthropic staff, or if the only thing that matters is whether another person was able to view the chats.

Edit: Upon searching I now also agree, it seems to require a state of mind and perhaps awareness of the possibility that the threat would be seen.

It's not a complicated distinction:

If you think they intentionally had their model hack third-party systems, you could do a criminal investigation.

I do not think that this is reasonable to believe given that clearly the VMs were not intended to have internet access and that committing such crimes wasn't in anyone's interest.

In the US, hacking laws require intent.

Software behaving differently than intended is therefore not a crime under these laws.

Not very interesting when you consider that in the first situation no laws were broken and no malice was intended, while in the second situation someone allegedly made threats against a police department and thus presumably committed a crime.

Isn't the AI stuff tinkering?

I've certainly thrown together more software and automations over the last year than I have in the other ~15 years since I started programming.

It's never been so fun.

Disagree.

Apple's remote access feature, that you would make remotely accessible for obvious reasons, apparently had a critical authentication bug.

Apple did not ship a security patch for this, allowing the vulnerability to be exploited a week later despite "automatically install security updates" being on.

Yes, OP could have prevented this by putting an additional VPN authentication layer in front of the Mac's built-in remote access.

That doesn't excuse the mistakes on Apple's part.

I think the point is that when a repo contains:

  program.bin
  install.sh

It seems rather pointless for me to thoroughly inspect the install script before I run the program.

Do you really need to know the language or is it enough to bother asking about improving the loading time or customizing the look?

It looks like crap.

Why would I want the terminal coding agents inside of a GUI app? The idea is terrible.

The first point in the explanations below makes no sense, claiming my agents will "keep working" if I close my notebook's lid or disconnect the network.

This is obviously not the case.

Using AI for the ComfyUI API or workflows worked pretty well for me even early this year.

However, today I don't see a reason to use ComfyUI at all.

For Qwen Image 2.1, I had Opus 5.5 create a backend outside of ComfyUI and it was able to make generation take 20% less time with some optimizations.

The optimizations it implemented were caching the text computation in Qwen Image 2.1 rather than including it in every step, fusing projections into a larger matrix multiplication, and decoding the VAE in horizontal bands or something like that.

If there was anything interesting in ComfyUI nodes, I imagine I could just have the AI adopt the relevant code instead of dealing with ComfyUI or custom nodes.

Nothing special at all, it just works.

One thing that I do is have each change reviewed by another model. If I implement with Codex, I would have Claude do the review, or the other way around.

I did not benchmark this against a review from a subagent with the same model, so I don't know if that in particular helps.

Not public.

It's a paid app, and after 6 months of work I expect to publish it this month.

In other words, you will have to take my word for its quality.

No, you don't.

I've stopped reviewing the code in my mobile app project months ago. I now only look at files changed and lines count in MRs. Functionality is best verified via manual QA testing.

I know that people here are going to doubt the quality of my project and say that it is impossible, but they are clueless and have evidently not build a project in this way. Experiences from eg. corporate backend work are hardly relevant.

It is clear to me that the fewer consequential mistakes people find during code review, their attention to code reviews is going to go down, to the point of also skipping them.

I expect that for most development, not reviewing the code will be the standard by March of next year. Only critical code like authentication will be reviewed.

For $15k you can rent like 14x B200 on-demand at retail prices and run them continuously for a week.

According to this analysis, at 70 tokens per second for Kimi K3, you could expect to run >800 parallel streams on that setup:

https://inferencex.semianalysis.com/run/kimi-k3-on-b200

It released on that date, the data before is a different model.

The chart shows GPT-5.6 Sol and a surprisingly large drop in performance when the switched it over to GPT-6 Sol.

What we were talking about here is the margin on inference as in:

Cost per GPU hour versus API price of generated tokens assuming 100% utilization.

This could be a margin around 98.3% for 5.6 Sol.

If the utilization of the GPU was 25%, it would drop to 93.1%.

Revenue sharing or training expenses are not considered here in this "inference margin".

Yes, competition is great for us.

I wonder if margins on GPT-6.1 Sol and Opus 5.5 are now 75% or 90%.

> All this must mean the Western AI companies are now extremely inference-margin positive.

> So the Chinese labs have thrown a lifeline to the Western loss-making labs, and I just have no clue as to why.

That inference wasn't profitable is a widespread myth.

Analysis based on Kimi K3 suggests that OpenAI and Anthropic have margins well north of 95%: https://inferencex.semianalysis.com/run/kimi-k3-on-b200

Over the last months I have seen news that OpenAI made breakthroughs in inference efficiency multiple times.

I have no reason to believe that the leading US labs don't have their own optimizations, or that they learned of this particular optimization from DeepSeek.

I do.

The results are less buggy, animations are much better.

It can work autonomously for hours and the result is decent most of the time.

That wasn't usually the case with 5.5, which needed more feedback and iterations to get things right.

I said it takes time to build and ship a good product, and 6 months is not a long time.

Not sure what point you're trying to make here.

The global GDP is $126T, a 5% productivity increase would correspond to $6.3T.

So, I have the following thoughts:

How much more productive can AI for knowledge work realistically make the global economy? 5%, 10%, 20%?

What if it also does robotics soon and can be deployed in manufacturing and construction? Can we get 50% more productive, or 200%?

Then there's science, medicine, and so on. Who is to say what happens if AI solves also that?

While I do not know if AI will be capable for these use cases, I see no reason to believe it unlikely that AI could be applicable to eg. robotics and speed up production by factor 3x.

I've been working on my project, a paid mobile app, for five months now.

I'm pretty confident I can release it in October, after some 500 hours of work.

Usually in these discussions I get "so it has zero users then".

One time someone on here told me that for AI to prove its worth for software engineering, my application would need to be in use already for at least ten years.

Which they are, so another way to see it would be that they make the API/enterprise cheaper.

However, I don't know how future larger models such as the cancelled 6.1 Astra will be priced.

If the price stays high, this would indeed be quite bad for the $200 subscription..

It is at least 3x cheaper than Astra in the 20x subscription.

So yes, it is clearly cheap in comparison.

Unfortunate that the Ultrafast is only available with the $500 subscription.

Tibo said that the existing $200 subscriptions keep the 20x factor for a while.

Ultrafast would have been nice with the temporary "Pro 400" plan.

They never nerfed any model after release.

The lackluster GPT-6 Sol has been superseded by this apparently much better 6.1 Sol within a week.

I am very skeptical of claims that old models weren't much worse. Compare this to February's GPT-5.3.

It's obviously true.

With the 80% price cut, this is competitive with Opus 5.5 despite the subscription downgrade.

Additionally, it was said that existing 20x subscriptions retain the higher limits for some time.

I have seen you make these immature accusations that users here are OpenAI employees multiple times today.

Showing alternatives alongside the recommended one, a single time after setting up the phone, seems like a very minor UX price.

It's pretty dumb below xhigh reasoning as far as I know.

It seems weird to me that just using a ton of output tokens manages to produce a decent result in the end.

It seems to work well though. Sometimes I fear that it might be more likely to eg. run an incorrect, destructive command, but maybe that concern is not justified.

I slightly prefer Astra to Opus 5.5.

It doesn't suffer the same verbosity issue and the writing is somewhat clearer.

The vision capabilities of Astra are a bit better I believe.

That said, Opus is 3x cheaper and the obvious winner when usage is considered.