When the US was attacked, we sent our children to die in one of your foreign wars.

When WE were attacked, the largest war in the continent since World War II, you abandoned us - even witholding things that cost you *literally nothing*, like intel to help intercept drones and missiles targeting civilians - and switched to instead threatening to attack us as well, helping pick us apart piece by piece.

  Do not act surprised when you get seen as duplicitous snakes and we take action to separate ourselves from your levers of pressure.

O Lord of the Abyss, Prince of Darkness, Morning-Star, please hear my cry: I invoke thee, Lucifer! Turn your gaze toward the Vatican's operating rooms! Guide the surgeon's scalpel with your claws! Burn the tumors from the Holy Father's chest with the infernal fires of Hell! Cast your curses upon any bacterium that may seek to cause opportunistic infection! In the darkness I beseech thee.

Hail Satan, please save the Pope, Amen.

It's cheap and easy to audit OSS for malicious code with AI these days.

It's not really about Microsoft. Increasingly, Europe sees the US as a potential threat who blackmails allies, even a potential invader, rather than an ally.

Literally just yesterday the US shut off intel-sharing to Ukraine (which mainly helps with targeting incoming drones) and blocked all Starlink terminals in Ukraine moving faster than 100kph (e.g. terminals on air-defense interceptor drones), both in effect dramatically hurting Ukraine's ability to defend against Russia's nightly drone waves - all in order to pressure Ukraine into stopping striking Russian oil refineries while Trump seeks to buy more Russian oil and Russia keeps strikig Ukraine's energy infrastructure.

We all know that the US could do this sort of stuff to any of us. We have to move US companies out of our critical paths.

Once upon a time, when the US called for aid after 9/11, Europe stood up. More Danes died per capita fighting in Afghanistan, in a war that was not their own, than Americans did. This year, Denmark was rapidly rushing explosives and bags of blood to Greenland to prepare for firefights against invading US forces.

All of Europe got the message. We're not dining with friends - we're on the menu.

Run yourself *on normal hardware*? Yeah, there's a pretty big gulf between that and a frontier model.

It's not about the specific "BioPykrete" example, it's the technique that's interesting: using proteins to bridge dissimilar materials in composites. It's using them in a way that's sort of like how an emulsifier lets you bridge lipophilic and hydrophilic compounds

Think, say, plastic-ceramic or plastic-metal composites. We can do these today (say, Colorfabb Bronzefill 3d printing filament), but the addition of ceramic or metallic particles makes the material properties generally worse, not better. The plastic just does not bond well to the particles; you have to significantly limit the percentage of metal or ceramic in your mix, and it makes them much harder to work. But what if they *did* bound well? You could easily produce materials with significantly boosted strength, abrasion resistance, etc, but with the low-temperature workability of plastics (note: they'd probably have to be thermoset, not thermoplastic, or low-temperature thermoplastics; proteins have heat survivability limits)

And why stop at metals and ceramics? You could literally just use "dust", just ordinary mineral dusts (clays, silt, etc) as a bulk filler in plastics, yet instead of ending up with a weaker product than working with pure plastic, you'd end up with a stronger one.

Maybe you don't even need a plastic. Maybe you can do what they're doing and bridge cellulose to an inorganic material? Then you're *really* operating on waste. Ice has the advantage of a low melting point in this situation, letting you use that component as a fluid - but cellulose can be dissolved in a number of substances, so perhaps you mix a cellulose-protein slurry with metal or mineral powders and then vaporize/recover the solvent?

Or even forgetting "novel" products, what about conventional composites? If you can bridge high-tensile fibres (such as carbon fibre) better to the polymer matrix that they're in, then you can help eliminate one of the main failure mechanisms of said composites, as well as making the behavior far more predictable. Because like metals (and unlike ceramics), a protein-bridged compound shouldn't be brittle; breaking one bond shouldn't introduce a discontinuity (like a ceramic), it should just reconnect after breakage (like a metal). Such composites should have ductility.

I don't know how widely applicable this will be, but technology that helps bridge dissimilar compounds is nothing to scoff at. And today we have tools like AlphaFold to assist with the design

As for the caveats:

* The concept of coupling agents is also not new, we already use various coupling agents to bond plastic to metal particles in metal-plastic composites and the like - they're just not great at their jobs.

* The aforementioned temperature limits

* Potential production challenges (though industrial enzymes are as cheap as like $15-50/kg, so seems viable?)

* Other coupling agents may offer better advantages; it's not a static field.

I haven't looked up the history, but I would imagine that the "XL" is for the fact that it can handle images up to 1B x 1B pixels (1 exapixel).

Both lossy and lossless, and so much more.

It's this.

And on the compression side, there's a lot of really cool stuff that lets it happen. For example, it dynamically resizes the blocks from 2x2 to 256x256, and they don't even have to be square. It may apply DCT in one, AFAS in another, etc - whatever is most efficient. It uses edge preserving filters to keep the edges of features clean. It can draw in splines and clone regions from one part of an image to another. Where it has to throw away high frequency noise (film grain, noisy textures, etc), it statistically samples the properties of the noise and saves that, and then regenerates equivalent noise. In "busy" areas, like say tree bark or whatnot (where the human eye isn't good at discerning changes), it throws away more precision there, and instead allocates it to details located in fragile flat areas, such as skin and shadows, that the eye is attracted to. It works in default in XYB colour space, based on the actual interactions of the cones in the eye, so it can aggressively quantize things which the brain cannot detect. And in the choice between fast but not-great Huffman coding vs. better but slow and patent-encumbered arithmetic coding, they instead use rANS, which is nearly as fast as Huffman but as efficient as arithmetic coding, and faces no patent challenges. Which is also why you can take a legacy JPEG and rapidly losslessly reincode as JPEG-XL and get a file that's ~20% smaller - you're swapping Huffman for rANS.

(That's the lossy mode - there's also a dedicated lossless mode)

Ahem

Don't we all! Hard drives, RAM, *and* GPUs, I'm in the market for it all.

I also want to buy silver-tin alloy for casting, and hey, what do you know, silver and tin are also both at astronomical prices due to in no small part the AI boom.

At one point you have to just stop waiting. Prices could start falling tomorrow, but then again, that could have been said at any point for the past several years.

They don't have the revenue to survive much longer,

They were profitable in Q2. You can't extrapolate that endlessly, but they're not a cash incinerator anymore. And they have $15-20B on-hand pre-IPO. They're fine.

Anthropic is more or less breakeven *despite* being engaged in a massive 10x YoY scaleup for approaching 4 years running. Companies undergoing even "normal" scaleup rates are almost never profitable, let alone 10x/yr. Any slowdown in scaleup, or any shift in market pressures from intense jockeying for position to starting to pay back investors, and this drives them into deep profitability

The threat to Anthropic has nothing to do with whether its current business is sustainable or deeply profitable at its core. It is. Its threat is one I've been highlighting for years and now we're really starting to see: once something is "good enough", people start to question why they should be paying more for better. We now have the rise of a bunch of crazy cheap, yet quite coding-competent models like GLM 5.3 Flash, Qwen 3 Flash, MiMo 2.6 Pro, MiMo 2.6 Flash, Muse Spark 1.3 Contributor, etc. The latter two are almost too cheap to meter. Now, you still need an orchestrator, for planning, supervision, management, etc; it can either be a human or a higher-end model. But you don't need to pay for, say, Opus to get good coding done these days. Anthropic, like OpenAI, is built on charging a sizable premium over inference costs because they have the best and people will pay for it. And sure, in non-verifiable fields (say, medicine), maybe people keep paying for the best, whatever it may happen to be. But the more of the "bulk" coding and the like moves off these premium models and into dirt-cheap models, that seems to represent a real threat to their business model.

Anthropic's response thusfar seems to be "join them". Claude 5.5 Haiku is a good model "flash" model, and they've set quite affordable pricing for it, definitely fitting into the above category. But that doesn't really solve the problem. Their best hope is that Jevon's Paradox kicks up: that now that big projects are so cheap to implement, people keep taking on even bigger projects, scaling their income from cheap flash models like Haiku, orchestrators like Sonnet and Opus, and non-verifiable tasks where people will generally always want to pay for the best. But will that compensate? Hard to tell. This is the threat to Anthropic.

Huh, does stuff like this work in vim? /prompt write me an implementation of the Navier-Stokes equations for a zero-turbulence boundary condition in python, with a sleek modern GUI and test geometry

Unrelated aside, but back in the day when there was just vi, there was always a debate as to whether it's pronounced "vee" or "vie". Eventually my friends and I agreed on a way to settle the debate: we'd have a text-to-speech program read it out for us, and treat whatever it said as canon.

It said: "six".

And those corrections require atomic clocks.