InDCS

Institute for Distributed and Cognitive Systems. @UBIDECO, @LNP_BP, @Cyphernet_io, @BICALabs

[InDCS @indcs_org]

An intelligent system is a computational system which may reduce computational complexity (for at least some problems) in a logarithmic time, and this result is provable in DTIME.

NB: not all humans posses intelligence under that definition; however at least some of them were proven to (genii and inventors).

At the same time none of LLMs or “artificial intelligence” system had ever demonstrated such qualities. Thus, a test of this sort is more strong test for a machine (super)intelligence than the Turing test.

NB2: we do not know whether an intelligence requires non-deterministic universal computer or not; but it may be assumed that it does.

[Maxim Orlovsky @dr_orlovsky]

There are technological/engineering leaps which humanity tries to take for decades - and fails. These are: thermonuclear synthesis, biological death, artificial intelligence and quantum computing.

When I was young, professors at my school had a joke that “we are always 40 years from thermonuclear synthesis”. And here we are, 30 years later: we are still there.

My take: the tech progress is not linear nor exponential. As all of things in nature, which looks exponential, it is in fact a sigmoid curve: exponential decline towards some horizontal asymptote follows the exponential growth (like the one which makes futurists believe we will have singularity next decade).

A leap in tech progress - a new phase of exponential growth - requires scientific breakthroughs, the scale of which we had with relativity, quantum mechanics, quantum field theory and standard model last century. Yet those were enough to build modern world - but they are insufficient for getting quantum computers, artificial intelligence, thermonuclear synthesis and solving biological death. Another leap is required.

How we want to achieve quantum computing, when nobody understands why the quantum world works the way it is? How achieve artificial intelligence having no consensus on what intelligence is? How to achieve thermonuclear synthesis when can’t explain mechanism of mass-to-gravity at quantum level? How to solve death puzzle when no mathematical model for aging exists?

Modern physics need to be rebuild on modern mathematics and computer science, with category theory, no infinities, continuities, calculus etc from past ages. (This is so funny to see engineers work on thermonuclear reactors when they still use Gibbs differential geometry for electrodynamics, instead of geometric calculus). Modern cognitive science has to be rebuild-invented, with no anthropocentrism and wokism. Etc.

There would be genii, who will do that. Some forerunners for them are already here (Wolfram, Deutch). But I am sure that at the end of the days those future genii will end up like Gallileo, Bruno, Tesla, Turing, Korolev… pretty much each genius of the past, cancelled, and killed by the collectivist humanity. Thus, I promise: whatever breakthrough I can personally achieve, I will not share it with the crowd and humans. If I will uncover the secrets of intelligence (which I think I really close to), I’d better build a new non-human individuals which will take the stars, than repeat mistakes of Tesla/Turing and others.

I take Johns Galt stance: Fuck you, humanity.

[Maxim Orlovsky @dr_orlovsky]

Our friends from @nodl_it organized a great event during the #BH2025, where we were proud to give a talk on the sovereignty and how our products we build in @pandoraprime_ch and @indcs_org help achieving it

[BTC Times @BTCTimescom]

The @rgbconsortium & @dr_orlovsky have released RGB I.0 — a scalable smart contract system for #Bitcoin & Lightning using client-side validation, zk-STARKs, and single-use seals. 🟥🟩🟦

https://t.co/BAr66rewKC

[LNP/BP Labs @lnp_bp]

Today, as a part of @indcs_org, together with @rgbconsortium, @ubideco and @pandoraprime_ch we are glad to present the formal specification for RGB smart contracts

[RGB Consortium @rgbconsortium]

RGB yellow paper is released: the first formally specified scalable smart contract system for Bitcoin & Lightning, made with client-side validation

https://t.co/JVK4HqEc8u

Follow us for more updates!

[Ruben Hassid @rubenhassid]

BREAKING: Apple just proved AI "reasoning" models like Claude, DeepSeek-R1, and o3-mini don't actually reason at all.

They just memorize patterns really well.

Here's what Apple discovered:

(hint: we're not as close to AGI as the hype suggests)

[Jonathan Gorard @getjonwithit]

@dr_orlovsky There’s a fun groupoid structure at play here (https://t.co/dpjNNcgRZw)

[Maxim Orlovsky @dr_orlovsky]

Mathematical groups in fact define classes of computational reducibility

CC @getjonwithit

[UBIDECO Labs @ubideco]

Proudly built on UNIDECO stack: Strict Types, AluVM, zk-AluVM, SONIC polynomial computer

[BICA Labs @BICALabs]

… and breakthroughs (some may count at least 5 more breakthroughs needed, each one at the size of attention mechanisms, deep learning and perceptron invention)

[BICA Labs @BICALabs]

Huge and systemic review on #AI #agent architectures, also comparing to biological brain and trying to adjust the modern agentic research into a more biologically-inspired direction. 🧵

https://t.co/4xm1nP4V3o

[InDCS @indcs_org]

Solving the problem of aging and age-related death means stopping evolution and cancelling on biological adaptivity - which is fine if we have a higher-order adaptivity.

However, it might take an unbounded number of computation to solve it, and whether a solution exists is an undecidable problem.

[InDCS @indcs_org]

Biologic death ("genetically predefined life expectancy") is a solution to optimization problem of achieving faster adaptation by random walk stochastic search in domain of computationally-irreducible algorithms.

[InDCS @indcs_org]

Thermodynamics are physics of computational undecidability

[Maxim Orlovsky @dr_orlovsky]

Thanshumanistic notes: how to define wealth outside of the frame of humanity.

We leave in a mountain of Universe's computational complexity. Its real riches, as gemstones in a mountain, are the pockets of computational reducibility - things we call "scientific knowledge" (or, simply, the knowledge). The real wealth of a civilization is the mined amount of that knowledge.