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Comment Re: Good luck, but I don't think it will work (Score 1) 11

That doesn't matter in the enterprise space, and even less when you're Microsoft and you control both the hosting environment and the software running in it. CUDA is important to researchers and hobbyists but an org the size of Microsoft can afford to write code to interface to something else even if they don't control all of it.

Comment Re:This will revolutionize igloo construction (Score 3, Interesting) 34

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.

Comment Re:wtf is JPEG-XL (Score 5, Informative) 33

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)

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