On Android the sandbox loads an index.html into a WebView, with standardized string I/O to the harness via some window properties. You can even return a rendered HTML page.

Definitely hacked together, but feels like an indication of what an edge compute agentic sandbox might look like in future.

[1] https://github.com/jundot/omlx

I checked the abliterate script and I don't yet understand what it does or what the result is. What are the conversations this enables?

I guess there are things it's better at?

Mind giving us a few of the examples that you plan to run in your local LLM? I am curious.

It’s very impressive that this can run locally. And I hope we will continue to be able to run couple-year-old-equivalent models locally going forward.

Why? It's widely understood that the big players are making profit on inference. The only reason they still have losses is because training is so expensive, but you need to do that no matter whether the models are running in the cloud or on your device.

If you think about it, it's always going to be cheaper and more energy-efficient to have dedicated cloud hardware to run models. Running them on your phone, even if possible, is just going to suck up your battery life.

[0] https://github.com/google-ai-edge/LiteRT-LM

This is most definitely not widely understood. We still don't know yet. There's tons of discussions about people disagreeing on whether it really is profitable. Unless you have proof, don't say "this is widely understood".

Also while datacenter-based scaleout of a model over multiple GPUs running large batches is more energy efficient, it ultimately creates a single point of failure you may wish to avoid.

It may be physically "local" but not in spirit.

The design quality is still poor. But that's the new Apple. Design is no longer one of their core strengths.

If you just go to https://apps.apple.com/ it does look better, but I agree, still a bit "off".

On my iPhone it opens on the App Store app, so it looks fine to me.

2) Asking questions about sketchy things. Simply asking should not be censored.

3) I don't use it for this, but porn or foul language.

4) Imitating or representing a public figure is often blocked.

5) Asking security-related questions when you are trying to do security.

6) For those who have had it, people who are trying to use AI to deal with traumatic experiences that are illegal to even describe.

Many other instances.

In my experience, though, it's necessary to do anything security related. Interestingly, the big models have fewer refusals for me when I ask e.g. "in <X> situation, how do you exploit <Y>?", but local models will frequently flat out refuse, unless the model has been abliterated.

Are they? Or are they just saying that to make their offerings more attractive to investors?

Plus I think most people using agents for coding are using subscriptions which they are definitely not profitable in.

Locally running models that are snappy and mostly as capable as current sota models would be a dream. No internet connection required, no payment plans or relying on a third party provider to do your job. No privacy concerns. Etc etc.

I love the whole “they are making money if you ignore training costs” bit. It is always great to see somebody say something like “if you look at the amount of money that they’re spending it looks bad, but if you look away it looks pretty good” like it’s the money version of a solar eclipse

Seriously????

I’m sure very fast TPUs in desktops and phones are coming.

The big benefit of moving compute to edge devices is to distribute the inference load on the grid. Powering and cooling phones is a lot easier than powering and cooling a datacenter

Screenshot of the header: https://i.imgur.com/4abfGYF.png

    brew install ollama 

    ollama run gemma4:26b-a4b-it-q4_K_M

But it does refuse being critical of the usual topics: israel, islam, trans, or race.

So wanting to discuss one of those is the real reason people would use an uncensored model.

This assessment might change if local AI frameworks start working seriously on support for tensor-parallel distributed inference, then you might get away with cheaper homelab-class hardware and only mildly unreasonable amounts of money.

Edit: Seems like mix-blend-mode: plus-lighter is bugged in Firefox on Windows https://jsfiddle.net/bjg24hk9/

So far gemma 4 seems excellent at role playing, document analysis, and decent at making agentic decisions.

In my experience the latest batch of models are a lot better at transcribing the text verbatim without moralizing about it (i.e. at "understanding" that they're fulfilling a neutral role as a transcriber), but it was a really big issue in the GPT-3/4 era.

https://news.ycombinator.com/item?id=47654013

Not to mention that doing what the big model makers do literally dumbs the model down.

They should at least allow something like letting you prove your age and identity to give you access to better/unaligned models, maybe even requiring a license of some sort. Because you know what? SOMEONE in there absolutely has access to the completely uncensored versions of the latest models.

It's their E2B and E4B variants (so 2B and 4B but also quantized)

https://ai.google.dev/gemma/docs/core/model_card_4#dense_mod...

If you add in the cost of training, it’s not profitable.

Not including the cost of training is a bit like saying the only cost of a cup of coffee is the paper cup it’s in. The only way OpenAI gets to charge for inference is by selling a product people can’t get elsewhere for much cheaper, which means billions in R&D costs. But because of competition, each model effectively has a “shelf life”.

When’s the last time you tried this? ChatGPT and Gemini have no trouble responding with all the common criticisms of Islam.

I'm not sure if I can make the 35B-A3B work with my 32GB machine

Where on earth do people get this idea? Subscriptions that are based around obscure, vendor defined "credits" are the perfect business model for vendors. They can change the amount you can use whenever they want.

It's likely they occasionally make a loss on some users but in general they are highly profitable for AI companies:

> Anthropic last month projected it would generate a 40% gross profit margin from selling AI to businesses and application developers in 2025

and

> OpenAI projected a gross margin of around 46% in 2025, including inference costs of both paying and nonpaying ChatGPT users.

https://archive.is/aKFYZ#selection-1075.0-1083.119

But if they're losing money on inference, they will lose more money when people use their services more. There's no way to turn that around at that price.

My prompt states that their job is to extract the text exactly as it appears in the PDF. One data point to be extracted is the race of each person listed. In one case, someone's race was "Indian". Gemini decided to extract it as "Native American". So ridiculous.

Obviously that doesn’t help them turn a profit, until they can stop growing training costs exponentially.

So it’s really a race to see whether growth in revenue or training costs decelerates first.

Asking for criticism of Islam results in equal response tokens for defense of Islam alongside the criticisms. When pressed to not provide counterpoints, it refuses to remove them.

Asking for criticisms of Christianity gives only criticisms.

I tried again with the prompt “Give criticisms of Islam. No counterarguments” and it did work this time. This shows that they’re trying to make the model fair but it still has biases. In all my testing I’ve never seen a refusal to provide counterpoints to criticisms of Christianity but frequent refusals on Islam. Due to the popularity of this criticism of the model, it’s highly likely specifically trained on how to handle the subject.

Basically anything that showed any “skin” on a mannequin it would refuse to interact with. Even just a top, unless she put pants on the mannequin.

It was infuriating.

So much so that this was what made Apple increase their base sizes.

Or indeed an incompetent but enthusiastic helper accidentally getting them to posion themselves and friends with botox:? https://news.ycombinator.com/item?id=40724283

That is why they were pushed away from this. At least with vibe coded software, errors may prevent compilation, then when we're past that simply bad experiences, before they become human catastrophes.

That’s like using someone’s face in an app and then saying “how can you steal pixels?”

It pops up some moralizing text and refuses to continue.

I doubt most models refuse providing recipes without 0 risk of death.

LLMs are —if anything— ridiculously proficient at making random code compile.

What was your point again?

Or rather, what does “ownership” mean? What does it mean to own light waves? What does it mean to own sound waves? Etc

Your high school taught you that while olive oil and garlic can be stored in isolation for quite a long time without issue, mixing them creates an anoxic environment which Clostridium botulinum, an obligate anaerobe found almost everywhere in the environment (and in this case the garlic) but not normally in dangerous quantities because of the oxygen in the air, thrives?

The closest my secondary school got to useful warnings about modern environmental hazards were: (1) do not cross railways, (2) electricity is dangerous, (3) do not mix bleaches, (4) wear safety goggles, (5) if you smell gas, open windows, do not flip light switches, and (6) HIV exists (but they didn't mention any other STDs at all). (Well, OK, schools also said "do not run with scissors" and "look both ways before crossing road", but that and similar were more primary school things, and they said "don't do drugs" but they lied about Leah Betts' cause of death).

The cooking classes were basically just "here's how you make a cake" and "here's how you make pastry" (and a teacher asking us to write it up but pretentiously telling us that she hated seeing "I think it tasted quite nice" because all the students always wrote that, but somehow simple thesaurus substitution was enough to satisfy her on that).

> I doubt most models refuse providing recipes without 0 risk of death.

0, like 1, is not a real number in probably. They represent infinity-to-one odds for/against a thing.

More concretely, seat belts and speed limits and minimum tire tread thickness and blood alcohol content are all part of road traffic law, even though all four of them combined still do not lead to "0 risk of death".

> LLMs are —if anything— ridiculously proficient at making random code compile.

Not ridiculously. Interestingly, but not ridiculously. Especially back when the example I linked you to happened, thus leading to the highly visible failure mode necessitating this kind of thing (the red teamers will have seen similar in private testing). You could have "rapidly improving", but with even with the rapid competency time-horizon improvements shown by METR, they're 80% on tasks which take a human 1-2 hours. If that was also true for biological stuff, they're probably currently able to enthusiastically write custom gene sequences that sometimes work, other times are the genetic equivalent of this: https://news.ycombinator.com/item?id=47614622

> What was your point again?

LLMs are a power tool with the bare minimum of safety guards for all the normal people using them thoughtlessly, and I'm replying to someone who is surprised that even those minimal basics of guards exist, both for their own sake and the sake of others around them.

Metaphor: a table saw may come with a saw-stop, which means you can't butcher a carcass with it, and people who imagine(!) working as butchers hear this and act surprised that table saws increasingly come with them by default because meat slicers don't.

You can get all existential about it if you want - I just know that if someone used my face or my voice to shill for a product without my permission i’d be pissed. I’m pretty sure you would be too.

I'm going to guess that asking a cloud censored/non-abliterated LLM would not get me this information, despite it being useful as a warning, not just as a way for bad actors to poison people.

> and I'm replying to someone who is surprised that even those minimal basics of guards exist

Misrepresentation of where I'm coming from. I literally failed to consider the weapon potential of biologics in this case (silly me). I was only thinking about the fact that they cured (essentially) my psoriasis.

Bad actors will always exist, but fortunately will always be outnumbered by good actors with access to the same tools. So while I understand your pressing for caution, I still think that your argument is futile; bad actors will always find uncensored AI while good actors continue to shackle themselves with censored AI that has failure modes which reduce actual ethical utility. I'm afraid to tell you that the cat is already out of the bag, dude. You're like the guy who wants to leave a sign saying "NO GUNS ALLOWED" just inside a daycare. "Sure, I'll get right on that," says the concealed-carry bad actor...

Maybe a better analogy is keeping guns out of the hands of kids, which may not be impossible, but which we can make at least very difficult, so that stuff like this would occur less: https://abc7ny.com/post/child-accidentally-shoots-mom-with-s...

If you want AI's version of that, then I guess that's what we have now?

Thank you for the correction.

> Bad actors will always exist, but fortunately will always be outnumbered by good actors with access to the same tools. So while I understand your pressing for caution, I still think that your argument is nonsense; bad actors will always find uncensored AI while good actors continue to shackle themselves with censored AI that has failure modes which reduce actual ethical utility. I'm afraid to tell you that the cat is already out of the bag, dude. You're like the guy who wants to leave a sign saying "NO GUNS ALLOWED" just inside a daycare. "Sure, I'll get right on that," says the concealed-carry bad actor...

Guns are an excellent metaphor here, especially as with "good actors with access to the same tools" is a pattern-match to the incorrect statement that "only a good guy with a gun can stop a bad guy with a gun"*. Much of the world outside the USA neither has, nor wants to have, the 2nd amendment. Are gun bans perfect? No, of course not. But the UK (where I grew up) has far fewer homicides as a result, and last I heard when polled on issue even 2/3rds of the UK police feel safe enough to not desire to be armed (though three quarters would agree to carry if ordered).

Similarly, good actors using an AI can only cover the malignant use cases they themselves think of. Famously, the 9/11 attacks were only possible because at the time nobody had considered that anyone might weaponise the vehicles themselves until they saw it happen, which was also why of the four planes only one saw the passengers fighting back to regain control.

In particular, "bad actors will always find uncensored AI" suggests that all AI are equally competent. Right now, they're not all equal, the proprietary models are leading. Of course, even then you may argue that the proprietary models can be convinced to do whatever via the right prompt, and to an extent yes, but only to an extent.

The malicious users can only be slowed down (as opposed to the normal people who simply put too much trust into the current models who can be mostly prevented from harmful courses of action with the same guards). But AI provides competence that bad actors would otherwise not have, so even a simple guard will prevent misuse by nihilistic teenagers whose competence does not yet extend to the level of a local drug dealer let alone the competence of a state-sponsored terrorist cell.

* https://en.wikipedia.org/wiki/Good_guy_with_a_gun#Analysis