It doesn't help that the author is rather withdrawn and not willing to spend any effort in making it more approachable.

Some tried, and said they found gaps in the proof, to which the author responded, but they were not convinced.

And that's essentially the situation since 2018.

It's not bought for its long-shelflife property anymore, it's basically just an ingredient in some popular traditional local recipes. Sure, those recipes emerged because the shelflife used to make hard-tack a reliably available source of calories, but that's basically gastronomical skeumorphism.

Sure, you can probably find a way to achieve a "good enough" result with normal household appliances, especially when it doesn't actually need to be stored for years and you're just going to soak it again for some tranditional recipe.

But it's a lot more effort than most people want to invest when they just want to replicate that recipe.

> Because it is only the proof calculi that have proof objects that seemingly need to put everything into the kernel.

I interpret that to mean that for some reason, having proof objects requires or at least encourages putting more logic in the kernel (which is apparently equivalent to having more axioms) and that results in a greater risk of having bugs in the proof checker itself.

If not, I'd say they don't even count in the "everyone"-

mary_curr - mary_old = ann_curr - ann_old

since they must have aged the same amount of years.

time dilation joke incoming

No, with AI it's because it's MUCH faster than evaluating substance, and fast ways to weed out AI slop are desparately needed, since it can be produced so quickly.

That's a complete non-starter unless you're serving some extreme luxury premium market with absurd margins, and/or your customer interactions already require a lot of human involvement. So 99.9% of digital products are right out.

Good human support is absurdly expensive and will easily make your product 10 times more expensive than your competitor's. But almost no customer is willing to pay 10 times more for good support.

It's basically the Turing test.

> To setup a cross business kubernetes cluster will take 2 years with unknown results.

Do you seriously believe those times will not go down 95% if the CEO pushes for it to get done yesterday because it will save the company millions in expenses?

Though I think there's at least one more important thing missing, namely the ability to form memories - to incorporate recent context into the model's weights. I don't think it's a coincidence that this is a very complex process in humans as well (involving sleep and dreams as neccessary mechanisms).