Lichtso

Photopolymer Resin based printing has been around for a while now. Not sure how much the light source matters / can improve the speed though.

In short, yes: https://en.wikipedia.org/wiki/Blockchain#History

People conflate blockchains, distributed networks and cryptocurrencies.

It also uses a Merkle tree to compress the snapshot versions associated with commits. But the actual commit structure builds on top of that. A pure Merkle tree or forest would only give you a set of overlapping snapshots, without any directionality. So, I think it is fair to call it a blockchain as well.

Yes and no.

A local GIT repo can be changed (including its history) however you please. But once you have shared it with others you can't take that back. If you try to, then others will notice that the hashes mismatch and that their HEAD diffs uncleanly.

I know the term is infamous here, but GIT is essentially a blockchain. Each commit has a hash, which is based on the hashes of previous commits, forming a linked list (+ some DAG branching).

I literally said "they", I know, I know, in English that can also be interpreted as a gender unspecific singular.

Anyways, yes it is an interesting question whether he/she is alone or they are a group. Conway's law probably applies here as well. And my hunch in general is that these criminal mad minds operate individually / alone. Maybe they are hired by an agency but I don't count that as a group effort.

Once somebody actually does this people are gonna complain the same as always: "The sole purpose of your project is to rewrite perfectly fine stuff in Rust for the sake of it" or something along these lines.

They might have burnt the reputation built for this particular pseudonym but what is stopping them from doing it again? They were clearly in it for the long run.

Here is one of the recent advancements in performing similarity (including nearest neighbor) search on sparse high dimensional data using learned indices: https://arxiv.org/abs/2204.10028

The paper basically deals with the most adverse case but the approach should work in lower dimensions and in data with a non-uniform density distribution as well.

Am I imagining things or is there a trend here?

Seems like we get more and more generalist approaches which are less specific and combine a lot of what used to be individual steps and techniques. In doing so they don't only become conceptually simpler but surprisingly more accurate as well. Possibly because a unified approach is more integrated and thus better at filling the gaps in one sub-problem with information form other sub-problems.

The article mentions this in the very end, but isn't the "Shirky principle" just a case of perverse incentives? Allocating a budget to solving a problem continuously does set the incentives to prolong the problem.

I wonder how much paying after the problem is solved would help vs. paying in advance as it is often done for agencies / institutions.

If you think about doing something using ROCm, read these first to get a feeling for what to expect:

https://www.reddit.com/r/Amd/comments/a9tjge/amd_rocm_hcc_pr...

https://www.reddit.com/r/ROCm/

Germany had many big external investment + government subvention projects involving factories, data centers etc. announced in the recent years. None of them materialized and they got canceled because of the German balanced budget amendment [0].

[0]: https://de.wikipedia.org/wiki/Schuldenbremse_(Deutschland)

There is no such thing. Information is not a physical good that you can store in a safe. Access to it implies sharing it. At best what you can do is an API limit so that the thing is not immediately copied in its entirety. But then again, what possible statistical insights could you gain with only a small fraction?

Here is my prediction of how this will play out for the entertainment industry in the coming decades:

Phase 1 (we are here now): While generative AI is not good enough to directly produce parts of the final product, it can already be used to quickly prototype styles, stories, designs, moods, etc. A good chunk of the unnamed behind-the-scenes-people will loose their job.

Phase 2: While generative AI is still expensive, the output quality is sufficient to directly produce parts of / the entire final product. Big production outlets will use it to produce AAA titles and blockbusters. Even actors, directors and other high publicity positions will be replaced.

Phase 3: The production cost will sink further until it becomes attainable by smaller studios and indie productions. The already fierce markets will be completely flooded with more and more quantity over quality. Advertisement will not be pre-produced and cut into videos anymore but become very subtle product placements, impossible for ad-blockers to strip from the product.

Phase 4: Once the production cost falls below the price of one copy of the product, we will get completely customized entertainment products tailored to our personal taste. Online communities will emerge which craft skeletons / templates which then are filled out by the personal parameter sets of the consumers. That way you can still share the experience with friends even though everybody experiences a different variation.

Phase 5: As consumers do not hit any production limits any more (e.g. binge watch their favorite series ad infinitum) and the product becomes optimized to be maximally addictive by measuring their reaction to it, it will become impossible for most human beings to resist. The entertainment mania will reach its peak and social isolation, health issues and economic factors will bring down the human reproduction rate to basically zero.

Phase 6: Human civilization collapsed within one or two generations and the only survivors will be extremely technology-adverse people by selection. AGI might have happened in the meantime but did not have the time to gracefully take over and remodel the human infrastructure to become self sufficient. Instead a strict religion will rule the lands and the dark ages begin anew.

Note that none of this is new, it is just the continuation and intensification of already existing trends. This is also not AGI doomerism as it does not involve a malicious AGI gone rouge or anything like that. It is simply what happens when human nature meets powerful technology.

TLDR: While I love the technology I can only see very negative long-term outcomes from this.

Cool project! Wish we would see more applications of SAT solvers or logic programming in general.

> we find that the technology has not been widely adopted in rendering engines so far

That is funny considering that Vulkan has added support for mesh shading roughly a year ago [1]. And, if you take a look at the members list of the Khronos group, you will find that AMD is listed in the top category [2] (what ever Ikea is doing there).

[1]: https://www.khronos.org/blog/mesh-shading-for-vulkan [2]: https://www.khronos.org/members/list

> Your approach doesn't apply to the semantic web.

Not sure which approach you are talking about.

> Two dimensional non-tree graph are neat but in most cases at best a debugging tool or whirlygig.

That is what I was saying. Layouting and rendering general case graphs is a mess.

Oh yes, edges of different types and their direction are definitely what the author of the post was missing.

This is precisely where triple (hyper) graphs and the idea of semantic networks comes in. Unfortunately, the designs, architecture and implementation of the semantic web are all completely impractical garbage.

I did a lot of research on rendering ontologies and in general the best way to do so is not at all. Instead try to do domain specific bijective projections (akin to DSLs). And if you really need graphs do not render the edges. It always leads to chaos, it is better to show all vertices and only display edges on request (e.g. on hover).

It is shocking to me how little known the rope data structure [0] and the order statistic tree [1] are. Especially in the context of text editors.

[0]: https://en.wikipedia.org/wiki/Rope_(data_structure) [1]: https://en.wikipedia.org/wiki/Order_statistic_tree

I might have expressed myself in an ambiguous and extravagated way, just to be clear, I was not complaining about WGSL. I actually do like it a little better than GLSL and HLSL, though it still leads to more standards / fragmentation.

And exactly, Apple did not want SPIR-V (a bytecode) and proposed WebHLSL (a textual source language) instead. So, I think my statement that Apple preferred a textual format over a bytecode is correct. They could have proposed another bytecode format, but as you noted, nobody did.

It does not really matter anyway, because the GPU hardware and software paradigms are still undergoing rapid change. And there are a whole lot of under-specified things like memory models, scheduling order, control flow uniformity etc. which I expect will take another iteration of standards to be established.

While that is true, it also true that Apple had a major influence on the current design and is e.g. the reason why we got WGSL [0] as a source language instead of a bytecode (a GPU WASM equivalent if you will).

[0]: https://www.w3.org/TR/WGSL/

The uncertainty principle is just a really misunderstood concept because it was first discovered in the context of quantum physics (Heisenberg 1927) and only later (Gabor 1946) the underlying mathematical principle that causes it was discovered.

It has nothing to do with measurement, knowledge, randomness or even our physical reality at all. It is a much more fundamental mathematical phenomenon [0] that always occurs when you switch representation between time and frequency domains and it tells you how you can arrange information in such mixed representations.

[0]: https://en.wikipedia.org/wiki/Uncertainty_principle#Signal_p...

The end of the gold standard [0]: "1971 when the United States unilaterally terminated convertibility of the US dollar to gold"

[0]: https://en.wikipedia.org/wiki/Gold_standard

The GA community in general is very small. So yes, tooling could be better, but IMO that is not even the problem. The lack of understanding how to use it is, because GA is not explicitly taught in schools or universities.

I have written a compiler which generates SIMD ready typed code for the desired GAs. You can then use that output as a normal library for your application.

https://github.com/Lichtso/geometric_algebra

I read the paper and I am aware that the gaussian projection is an approximation anyway (hence I spoke about ellipsoids, not gaussians). Still, one could at least aim to get the iso contour right and yes using the Jacobian matrix is not unsound, just incomplete. As I said, this approach can not produce the distinctive "wiggle" that you get from rotating an ellipsoid while staring dead center at it.

Depends, radiance field approaches (like gaussian splatting) are basically 3D photos. They do only capture color at geometry (position and direction), but have no concept of surfaces, materials and light transport in general (emission, absorption, transmission, reflection, scattering, etc.). In other words, they can only do static scenes (no animations) with pre-baked lighting.

The industry seems to be trying to move away from this with things like PBR (physical based rendering) and ray / path tracing which enables far better dynamic lighting.

Also, they are extremely space inefficient at the moment. A scene that would take a good traditional rendering engine a few dozen GB would take TB instead. Though, that might improve in the future with more optimization.

One exception to the above, where gaussian splatting might be interesting to see is procedural / generated content (possibly even animated). Especially for volumetric effects which currently use particle systems, like smoke, fire, clouds, flowing water, etc.

Really cool, I am also working on a port of gaussian-splatting [0] but to WebGPU.

Like all the other implementations I have seen so far, this also makes the same mistake when projecting the ellipsoids in a perspective: First you calculate the covariance in 3D and then project that to 2D [1]. This approach only works with parallel / orthographic projections and applying it to perspectives leads to incorrect results. That is because perspective projections have three additional effects:

- Parallax movements (that is the view plane moves parallel to the ellipsoids) change the shape of the projected ellipse. E.g. a sphere only appears circular when in center of the view, once it moves to the edges it becomes stretched into an ellipse. This effect is manually counter balanced by this matrix I believe [2].

- Rotating an ellipse can change the position it appears at, or in other words creates additional translation. This effect is zero if the ellipse has one of its three axes pointing straight at the view (parallel to the normal of the view plane). But, if it is rotated 45°, then the tip of the ellipse that is closer to the view plane becomes larger through the perspective while the other end becomes smaller. Put together, this slightly shifts the center of the appearance away from the projected center of the ellipsoid.

- Conic sections can not only result in ellipses but also parabola and hyperbola. This however is an edge case that only happens when the ellipsoid intersects with the view plane and can probably be ignored as one would clip away such ellipsoids anyway.

The last two effects are not accounted for in these calculations in any of the implementations I have seen so far. What would be correct to do instead? Do not calculate the 3D covariance. Instead calculate the bounding cone around the ellipsoid which has its vertex at the camera position (perspective origin). Then intersect that with the view plane and the resulting conic section is guaranteed to be the correct contour of the perspective projection of the ellipsoid.

[0]: https://github.com/graphdeco-inria/gaussian-splatting [1]: https://github.com/antimatter15/splat/blob/3695c57e8828fedc2... [2]: https://github.com/antimatter15/splat/blob/3695c57e8828fedc2...

That is a good point and the answer in short is: No.

Radiance fields have no concept of light emission, reflection, absorption, etc. instead everything is mushed into one value: The light transported. In that sense radiance fields are just 3D photos.

You would have to perform reverse-rendering / photo grammetry and estimate where the light sources and the surfaces are, what materials they have and so on. Then you could use traditional path tracing methods on that again.

Another thing to think about might be videos (not animation): Continuously capture the radiance field over time and then try to compress away the similarities in between frames to gain temporal coherence.

Talks in length about suffix arrays and yet never mentions the BWT:

https://en.wikipedia.org/wiki/Burrows%E2%80%93Wheeler_transf...

Not as a number, but as a unit it actually exists. It is called a "mort" (from mortality). In that sense one mort is "so much, you'll die".

Though, the commonly used scale is a mort * 10 ^ -6. https://en.wikipedia.org/wiki/Micromort