0xBABAD00C

Yes, Cyrillic was closer to Greek, that's why it stuck better. Just edited to make it clear.

There are Byzantine Armenian dimensions to this story that I suspect not many people know. Cyrill and Methodius were taught by Leo the Philosopher and Photios, in the University established by Bardas, all Greek-Armenians who clearly knew the transformative effect of having your own writing system (it saved Armenians from assimilation just a few centuries prior to these events). It took Hellenic culture of Byzantine period and Armenian experience to give birth to the first Slavic writing of Moravia and Bulgaria, and later most of Eastern Europe.

Incidentally, the first writing system (Glagolithic) didn't stick nearly as well as the subsequent iteration (Cyrillic) because the latter was so much closer to Greek, and every educated person already knew how to read/write Greek so it was a much easier sell. Regardless, this invention and its promotion was very much a planned and well-understood Byzantine project.

> Thus Bardas founded the Magnaura School with seats for philosophy, grammar, astronomy and mathematics, supported scholars like Leo the Mathematician and promoted the missionary activities of Cyril and Methodius to Greater Moravia.

https://en.wikipedia.org/wiki/Bardas https://en.wikipedia.org/wiki/Leo_the_Mathematician https://en.wikipedia.org/wiki/John_VII_of_Constantinople https://en.wikipedia.org/wiki/Photios_I_of_Constantinople

(these further cite primary sources)

Oh he's "solving the problem efficiently", just not the problem he purports to be solving. It's all about misaligned incentives in large orgs: people act out of their own self interest, and if the incentive mechanisms are designed incorrectly (or evolved over time into a misaligned framework), you get situations like these. The higher-levels in big orgs typically do play an outright zero-sum game for positions of power, with the object-level problem/domain being mostly a nuisance.

I use this (should be the baseline I think): https://finviz.com/map.ashx?t=sec

Also, when have people not followed "false narratives"? The entire human civilization sits on a stack of false narratives.

This looks great! What are some of the verticals you think this will be most immediately applicable in, and are you integrating with any? I am thinking a lot of ads/marketing work can be jump-started with these notebooks.

Well, you can ask yourself what is "real value". In fact, more likely than not, it's just some imaginary stuff you ascribe value to, just like "prestige".

> what are the chances they already publish photos taken on devices that apply by default some form of AI-based generative/corrective algorithms

100%?

> In my experience with children, one of the easiest-to-grasp concepts of infinity is provided by the transfinite ordinals

Things people say on HN :)

> The author is basically a crank

Really not sure why do you say this. Is it something personal against him? Are you against people exploring weird interdisciplinary topics?

He has tons of publications [1], including co-authorship with people like this guy: https://en.wikipedia.org/wiki/Eugene_Koonin

Koonin is certainly not a crank, and is a rather well-known interdisciplinary researcher at the intersection of biology and physics.

[1] https://scholar.google.com/citations?hl=en&user=nEEFLp0AAAAJ...

Vanchurin is a physics professor, but ok https://twitter.com/vanchurin?lang=en

I actually think that interdisciplinary work like this can shed light into common structures across physics, biology, neuroscience, CS, etc. If anything, I wish there were more attempts to explore the connections between these disciplines.

Complex/imaginary numbers are just badly named for historical reasons, they represent an objectively central concept in math and physics, and can be derived from axioms of what we expect from a well-behaved number field. For reals, we have: (A) expected properties of addition and multiplication, (B) total order and other order-related nice properties (Dedekind-complete). Any mathematical structure satisfying (A,B) will be equivalent to real numbers. Now if we extend it to get (C) algebraic closure, so that all polynomials have roots, we get the complex numbers.

And not just a field, but the algebraic closure of real numbers.

There is research claiming the entire universe is a neural network: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7712105/

Yeah I tend to agree it feels like a little bit of everything, but mostly B. To be honest, this community survived longer than many others I've seen.

> Gradients Are Not All You Need

Sometimes you need to peek at the Hessian.

Seriously though, what is intelligence if not creative unrolling of the first few terms of the Taylor expansion?

Arguing against AI's "existence" or its dangers is cheap/free: if the whole thing flops, you get minor cookie points, and if it doesn't, people will have bigger problems to worry about than you or your opinion. AI is not gonna flop, and we better prepare.

> able to generalize language, math, and positional reasoning and mix it with the older parts of the brain for reward and training mechanisms and it can do it in real time

most brains I run into don't do that much at all, mostly just existing and adaptation-execution

It's not a strong argument to say "what could it be other than X? therefore, X"

> What could it be?

Sense of community is gone. Trust is at an all-time low. Traditional social institutions and scaffolding that held society together are gone. Families are more broken apart than ever. It's an entire regime change, and we're still operating with our old instincts/hardware, which expects to be raised in a village by a largely familiar and empathetic community. The farther we get from that model, the more we'll be stressed out (until and unless we upgrade our hardware somehow, or, more likely, die trying).

Social media is small potatoes in comparison to the changes that have happened already, and especially to those that are coming.

> dynamic programming only comes up when I'm studying for interviews

I worked a SWE job years ago which was heavily reliant on dynamic programming and string search/alignment/etc. It really depends.

Human beings are not the top-level cognitive agents, there are egregores at higher levels of organization (related to memeplexes, meta-organisms, etc). It's just hard to define and talk about them concretely, our language is not well-suited to reason about agency above the human level. One century-old example of identifying an egregore is the meme "A spectre is haunting Europe — the spectre of communism." It's nothing supernatural, just like a combination of neurons computing each their own thing gives rise to a new agent (human), a combination of humans computing each their own thing gives rise to a superhuman agent (spectre of communism).

Here's the analogy, per Sean Carroll [1]:

- There seems to be a special direction "down", where things fall by default, because we live in the vicinity of an influential object in space, called Earth

- There seems to be a special direction "forward in time", where things happen by default, because we live in the vicinity of an influential event in time, called Big Bang

If we had stuck to the local Earth context and geocentrism, the objectivity of the "down" direction would remain unquestioned. It's when we started modeling other things outside of Earth, it became clear there's no objective "down" direction, just a more general concept of Gravity.

Carroll's argument is that it's the Big Bang, an extremely low-entropy configuration of the universe, that gives rise to the 2nd Law of Thermodynamics and the resulting emergence of an arrow of time in the forward direction. It's purely a statistical phenomenon at larger scales, and attributable to being "next to an influential event", according to him.

[1] https://www.youtube.com/watch?v=AZsmyTE3j9o

I don't think what you're saying contradicts what I'm saying. My baseline / reference point wasn't CNNs.

> scaling the model and having more data completely beats inductive bias

The analogy in my mind is this: "burning natural oil/gas completely beats figuring out cleaner & more sustainable energy sources"

My point is that "more data" here simply represents the mental effort that has already been exerted in pre-AI/DL era, which we're now capitalizing on while we can. Similar to how fossil fuels represent the energy storage efforts by earlier lifeforms that we're now capitalizing on, again while we can. It's a system way out of equilibrium, progressing while it can on borrowed resources from the prior generations.

In the long run, the AI agents will be less wasteful as they reach the limits of what data or energy is available on the margins to compete within themselves and to reach their goals. It's just we haven't reached that limit yet, and the competition at this stage is on processing more data and scaling the models at any cost.

+1 for probability via measure theory & functional analysis

I would add the need for geometry and topology becoming more of a pre-requisite for picking up modern methods: https://arxiv.org/abs/2104.13478

> ChatGPT is more of an existential threat because it will propagate to infect other knowledge bases. Luke Wikipedia relies on "published" facts as an authority, but ChatGPT output is going to wind up as a source one way or another. And worse, then ChatGPT will digest its own excrement, worsening its own results further.

This is what people do collectively, long before any GPTs were in sight. Lots of strong convictions people hold today and publish all over the place, are re-processed excrements of long-gone mental viruses of past civilizations.

> Whales, dolphins, and orcas are damn smart, and I think there's evidence enough that we cannot conclude that they aren't more intelligent than us.

Where's this evidence? What exactly does "more intelligent" mean to you? Do you think a dolphin can learn to play e.g. Chess? I doubt you can teach them to play even tic-tac-toe.

If your job is to attract an agent that is playing a careful balance between exploration and exploitation, while on tight computational budget, then you want to attract them with some initial hooks (e.g. bright colors) and appease their computational risk assessment module with high compressibility (e.g. symmetries and self-similar patterns).

https://arxiv.org/abs/0812.4360

> what the point of life is to the universe

Life is the evolution of (increasingly) complex adaptive systems in non-equilibrium state, driven by external energy and enabling a new regime of faster entropy increase, thus faster descent towards the "heat death". This is contrary to the popular belief that life somehow goes against the 2nd law of thermodynamics. In fact, it is the 2nd law of thermodynamics, the universal drive towards higher-entropy states (we are essentially specs of dust in a slow-motion explosion, since the Big Bang), that enables life-like systems to evolve under the right conditions to accelerate the slide towards a higher-entropy state.

Specifically in case of carbon-based biological life, one succinct tongue-in-cheek way to put it is "life's purpose is to hydrogenate carbon dioxide". See the "Nick Lane" discussion thread from today: https://news.ycombinator.com/item?id=32392937

> We won't know the answer to this challenge for a very long time.

This is essentially the "halting problem", or the "principle of computational irreducibility", or whatever equivalent formulation you want to pick. We'll never know the answer -- for most computations there are no shortcuts to predict their outcomes.