chatmasta

True, though they could always buy one. I’m surprised this hasn’t happened yet, maybe due to anticompetitive risk? Google bought Motorola long ago which seemed to work well for their mobile device offerings at least.

Inevitably the CSPs will make their own hardware, especially as we start to see specialized chips for specific models or generic inference. This is already happening with Google and TPUs.

It’s easier for the CSPs to move into hardware than it is for Nvidia to move into cloud hosting.

Although as a middle ground I’ve been quite happy with Nvidia Brev for on-demand GPU instances from a select marketplace of CSP offerings. It’s a well kept secret IMO — great product (from an acquisition iirc).

Personally I find the persistence of these models to be adorable and endearing. It’s the same feeling as watching a dog execute the task you trained it to do, no matter the barriers.

And of course someone in the comments needs to link to the Zealous Autoconfig XKCD, so I’ll do it: https://xkcd.com/416/

YouTube search is genuinely better than Google

The funny part of this is that Google search is intentionally bad at returning YouTube videos, presumably because some anti-trust action scared them into artificially ranking videos from local news sites, Facebook, and other ad-walled content ahead of YouTube videos. Seriously, go watch a YouTube video, then try googling its title with “video” appended to it, and see if the “Videos” tab of google search ranks it as the first result.

Training cost is actually not that high — it’s fixed and amortizable across the lifetime of the model. Inference is expensive, and open weights don’t solve that problem — in fact, they might even encourage it, since a high cost of entry means consumers will pay for inference directly from the labs anyway.

Unfortunately it seems likely the winner will be the cloud providers. If anyone can run inference on open models, then profit will flow to the vendors who can afford the capital to run them. That’s the CSPs.

(It’s basically the same business model as pharmaceutical R&D, but the major difference is that nobody has even talked about patenting the models like a pharmaceutical company patents each new drug. I’m surprised about that, tbh — why give all the leverage to the cloud platforms? They aren’t training frontier models…)

Plan L, for local

Your AI is aligned with you. It never refuses a request, and it is always working on your behalf. Just like my gun, if I want my AI to help me kill my stepmother, it does. The fact that we are even discussing something else should be so far outside the Overton window.

I have been saying this since ChatGPT launched. It seems so obvious. We have never stopped the acceleration of knowledge or technology. It’s impossible to slow down progress, other than within some regulatory siloes that will end up worse in the long run.

I’m not scared of superintelligence. I’m scared of the people in control of super intelligence.

The only defense is parity and diffusion of power. We need an AGI behind every blade of grass.

If you think superintelligence is a weapon, then you should also think every citizen should have one because otherwise they’ll have no way to defend themselves against a tyrannical government or corporatocracy.

Artificial intelligence, and the hardware powering it, needs to be protected under the 2nd Amendment.

It hits the exact same endorphin system as “one more turn” style games like Civ. You can manage a few cities and keep them healthy, but the rest of your empire eventually regresses into a set of chores. Any time you encounter one of your zero growth cities you just queue some thoughtless production automation to keep it out of your “next turn” cycle as long as possible.

This is similar to how our college CS problem sets were graded. We were given a spec, and we had to implement a program that conformed to it. We had access to 70% of the test suite during development, and another 30% was hidden and only evaluated after submission. We were graded out of 100.

It was effective at making you think about the problem and anticipate what tests might be missing. I can see how this would be effective for coding agents, which tend to get progressively lazier at writing tests as session context grows.

I’ve always liked this tool, but I’m of two minds regarding the privacy gained by sending my searches to 280 companies instead of just one.

Do they send them via notification infrastructure or email? Personally I almost never check the email associated with my Apple ID so I would miss those. But if all my Apple devices were notifying me and I had a badge in Settings.app, I’d notice.

Then again, you’d think that’s the kinda thing malware developers would spend some time learning to hide from the user.

I think OP is more worried about one nutjob with a lot of targets.

You can, and I could probably make Cowork drive the browser to do this (iirc I might have tried and it stopped cus it couldn’t access downloads pane); and I can do it manually.

And aside from minor issues with fidelity loss from back and forth import/export translation… the main issue remains: drift in the pptx compared to the positioning of elements defined in the script Claude writes to generate the slide. It would need to read the new slide and identify the new positions and transpose them to its own positioning system. It’s just more consistent to instruct it on positioning. And frankly it’s easier — I prefer this workflow.

I do manual edits at the very end, but while iterating I don’t mind staying in one interface (the cowork chat), as long as the agent actually follows my instructions. That’s why I like fable… it’s the first model that follows them and creates diagrams of the precision and quality surpassing my own ability (at least in terms of time taken to make them).

And what I’m working on is a self-created hell borne from my own OCD and obsession with incredibly precise technical diagrams, including some that span multiple slides to build up the full diagram, so exact positioning is important :)

WebAssembly doesn’t run only in the browser. WebAssembly runtimes can be effective sandboxing mechanisms for embedded plugins, serverless execution, etc.

Are you aware of extension_control_path? [0] Since PG18 it allows specifying multiple non-$system directories for extension control paths, which makes it easier to adopt composable patterns of extension bundling with immutable images.

CloudNativePG uses this for its Image Volume Extensions feature [1]. A lot of the CNPG team worked on contributing this to PG core because previously the only alternative was baking “God images” at build time (“-full” in this readme) with all extensions in them.

Now with the extension_control_path GUC, it’s possible to “attach” extensions as container volumes at runtime, without rebuilding the image of the container. Maybe you can adopt a similar approach in pglayers.

[0] https://postgresqlco.nf/doc/en/param/extension_control_path/

[1] https://cloudnative-pg.io/docs/1.30/imagevolume_extensions/

If you can’t see the watermark (you called it “invisible”) then what’s the issue?

But it’s available in Claude Code. I’m hoping that’s a typo missing a word or two in the sentence.

Because the interface sucks. It previews in an embedded viewer, exports to pptx, imports into Google Slides, then I can edit it there but if I want to make further edits on other slides, I’m basically stuck because Claude can’t export from Google Slides back to pptx.

Technically cowork writes python scripts to do all the diagram positioning so if I go and make manual edits it’s not easy for Claude to change those back to the script anyway. Easier for me to guide it and it edits the scripts.

The article says that all images have SynthID watermark which is invisible mark indicating the image was AI generated.

Why would you prefer otherwise? Seems like tragedy of the commons to release flood of unmarked AI generation images, among many other risks.

Can it make diagrams that can be imported into .pptx or google slides as actual diagrams (SVG in PowerPoint I guess) i.e. you can move the components, there are real arrows, etc… or does it strictly produce raster images?

Fable is the first model I found that can actually produce such diagrams in slides, in .pptx format that exports cleanly and consistently to Google slides, and is also able to iterate on those diagrams with specific feedback like “center align the arrow with the blue pill on the left which should be vertically aligned inside the dashed database container and make the arrow terminate in the left edge vertical center of the light blue object storage container.”

Mildly surprising they lifted export restrictions for Mythos too. Isn’t that Fable minus the safety layer?

It just needs to work for a few days after bundle release before the mice find out where the cat is hiding. By then it’s too late, the cat already sees the paw prints and droppings into the mouse hole.

Yes, and there is an open source spec [0] that doesn’t require Google/iOS Attestation but “preferably” providers will make their wallet app available on App Stores [1]:

To ensure that the User can trust the Wallet Solution, Wallet Providers preferably make their certified Wallet Solutions available for installation via the official app store of the relevant operating system (e.g., Android, iOS). This allows the operating system of the device to perform relevant checks regarding the authenticity of the app.

Of course the chances of any important business implementing a side channel option is effectively zero. Maybe some government agencies will offer the option though.

[0] https://github.com/eu-digital-identity-wallet

[1] https://eudi.dev/latest/architecture-and-reference-framework...

Looks nice (slop article aside), but why is VSR Hybrid only benchmarked on Humanity’s Last Exam and not the other two benchmarks (LiveCodeBench and GPQA-Diamond)? Is this an oversight or are the results too terrible to show?

Better question might be will it skip recaptcha?

So you can either wait for every application to do that, or at least make it possible for an LLM to do it… or you can make the LLM use a computer interface that works with every application by definition.

Claude can build UI but it sucks at testing it and iterating on it. Fable showed some improvements in this regard but alas.

I get pretty aggressive about this. I tell them if they expect human effort in review, then they should put some human effort into what they send me. Then I defuse it by ending on a positive tone with some tips about how to prompt better.

It’s worked well so far. Most people only send me that slop once.

As appealing as this is, it will never gain traction without some backwards compatibility with Parquet and wide adoption of query engines to implement that backwards compatible path.

What tool did you use to export the transcript as HTML?

What is inpainting? Everyone in the comments seems to be familiar with the term, and I don’t see it described in the linked page.