ױ AstroQubic

$QUBIC is the future

[ױ AstroQubic @AstroQubic]

I've decided to believe that $QUBIC will be at the top when the news breaks in April 2027, so for me it's simple:

I've invested all the money I can afford to lose now at $0.000000703 and I'll wait 16 months.

If it works out, I'll be a millionaire; if not, I'll continue living as I have been.

So whatever happens with price in between it won’t change anything for me

Time will tell 🕰️

[Come-from-Beyond @c___f___b]

I confirm. Go to #Qubic discord and run Anna.exe published there, you will see that upon improvement of fitness function score of the training set (green column) you often get improvement of the validation set (yellow column). In a several weeks this architecture will be deployed to the #Qubic network as open source code and you'll become able to confirm it yourself.

[QUBIC NEWS ױ @ShibianaBones]

Sergey Ivancheglo AKA @c___f___b:

Founder of first DAG Protocol
Founder of first 100% PoS Protocol
Founder of first uPoW
Founded very first ICO project
Founded First #AGI on Blockchain
Founded Top #1 & #2 highest ROI
coins

#FWYK this is $QUBIC
feeless, 15 Million TPS, UEFI,…

[JOE @CryptoSailorJoe]

🚨MASSIVE BREAKTHROUGH🚨

#Qubic Science just dropped CuNxon!

Neuraxon is like a super advanced, brain inspired simulation system.

It’s not your average #AI.

These virtual “neurons” fire real electrical style signals (called spikes), constantly rewire and learn from experience (that’s plasticity), and even respond to chemical like signals that fine tune everything (neuromodulation).

Until now, all of that heavy brain like computing ran on regular old CPUs.

It was perfect for early experiments like the Game of Life simulator and basic testing.

But for what’s coming next?

CPUs were way too slow.

Enter CuNxon.

Every single operation Neuraxon can do is now ported straight into $NVIDIA CUDA kernels.

That means it runs natively and blazingly fast on GPUs the same powerful graphics cards that power video games, #AI training, and supercomputers.

And here’s why this is explosive…

There are roughly 5 million CUDA developers worldwide.

Most of them already live in the world of machine learning and #AI.

From today, every single one of them can jump in, build, test, and expand Neuraxon using the exact same GPU tools they already know and love.

The real rocket fuel?

When the #Aigarth evolutionary layer lands in the #Qubic network, miners and Computors will be able to train and evolve entire populations of Neuraxons using full GPU power not just slow CPUs.

One $100 budget GPU at home?

A billion dollar supercluster?

The library doesn’t care.

It scales perfectly.

And the best part?

It’s completely open source.

The age of GPU powered, brain like, evolving #intelligence on the #Qubic network just went from “someday” to right now.

You’re early Anon, #DYOR

#Qubic #Decentralised #Intelligence
#Crypto #Gem #AiGarth #AGI #IYKYK

[Chain INK @0xchainink]

Top 10 Crypto Communities 👥

(Ranked by Strength)

$QUBIC → 9.23
$KAS → 9.15
$TEL → 9.05
$ICP → 9.03
$TRAC → 9.01
$QUAI → 8.98
$ZBCN → 8.97
$SERV → 8.88
$WMTX → 8.88
$RENDER → 8.85

Purely subjective ranking

based on community activity, engagement, loyalty, and overall social presence.

[David Vivancos - e/acc @VivancosDavid]

These two (century old) ➵ hold the key to build #AGI #QAndC ... June 1st 2026

[Crypto-lowcap @CryptoRowenta01]

$QUBIC moved away from Monero onto Dogecoin. The crypto press got it wrong both times. Is it parasitic mining, or the most coherent PoW reframing in years? I give both cases their strongest form. $XMR dogecoin:native
https://t.co/Jw4wldpdc6

[David Vivancos - e/acc @VivancosDavid]

Meanwhile ready for #NeuraxonLive Sesion 2 , 10X map 100K tiles and up to 5K Alive Nxers, good for building a legacy... Already live at: https://t.co/lBg6TaGBm5
Also as requested check Family tree for you Nxer (while original Nxer alive)
Also Enhanced Nxon Editor

[ױ AstroQubic @AstroQubic]

Lately I've seen several posts about $Qubic and I think it's a perfect example of the Dunning-Kruger effect 🧠

Most people here have basic or advanced AI knowledge, but probably still don’t truly understand what’s being built behind the scenes. To top developers and @c___f___b , it’s likely like hearing a child explain math to a PhD.

The real opportunity is recognizing that you found QUBIC early, before the majority understands its potential. Sometimes the smartest move is simply investing early, being patient, and letting time do the work.

The current price doesn’t matter if you’re convinced of what is coming

[David Vivancos - e/acc @VivancosDavid]

More updates on the🪼#Neuraxon front from @_Qubic_ #OpenScience hybridized with #Aigarth

@josesanchezhb & @VivancosDavid are proud to share #NeuraxonLive
Game Of Life Server + Client so you can Deploy your own world of 🪼based on Game of Life 5.0

Full open source code at: https://t.co/SJuYIL0BOA

Deploy your own server or use ours.

Breed your own 🪼the first season just started,
is live at https://t.co/H5KcaO9vSy

- Will yours live forever? -> If so share your 🪼
- Will yours be on top of the rankings?

This season world max is 500🪼and max 100 Custom Nxers claim yours now!

Why it matters?
Neuraxon Live isn't a simulation you load and reset — it's one neural world running 24/7, "forever", where every creature carries a real g-capable brain that forages, mates, sings, and dies on its own.
You're not watching a replay; you're watching open-ended evolution and emergent intelligence happen live, ranked all-time across every NxEr that ever lived.
Open a browser, zoom in, and you can literally hear artificial minds being shaped by selection in real time. 🧠🌍

[Qubic @_Qubic_]

Doge Mining Revenue Report | Epoch 213

Mining Sample: QDOGE's Fluminer L1 (5.7 GH/s)

Revenue per GH/s per day:

Mining DOGE + LTC via Qubic
→ $1.00 / GH/s

Mining LTC + DOGE on traditional pools
→ $0.51 / GH/s

That's +$2.81/day. +$19.66 over the week. 97% more revenue on the same hardware.

[Qubic @_Qubic_]

Qubic just increased its per-tick transaction capacity by 4x.

The parameter moved from 1024 to 4096 transactions per tick today. Every tick of the network can now process four times as many transactions as it could yesterday.

Why now?

Look at the trajectory.

Epoch 210: 200 million transactions in seven days.

Epoch 211: 226 million.

Epoch 212: 246 million.

The load is climbing, driven by DOGE share validation flowing through Oracle Machines plus organic smart contract activity.

The core tech team raised the ceiling before it became a constraint, adding 4x headroom ahead of demand.

That usually only happens when the team knows exactly what they’re doing 😉.

[Investor Jordan 🌪️ @InvestorJordan]

I’ll be covering $QUBIC in my new video being posted tonight…📽️

Hint: I like it.

Any of you guys holding?

[David Vivancos - e/acc @VivancosDavid]

Today #MultiNeuraxon🪼joins the @nvidia #cuda family , very glad to release for @_Qubic_ #OpenScience The Cuda Kernels and library so you can teach your #bioinspired #AIs using Nvdia #GPUs too.

Code: https://t.co/SJuYIL0BOA

Why it matters?
It brings Multi-Neuraxon + #Aigarth evolution to GPU-native execution: CPUs orchestrate while NVIDIA GPUs teach, execute, and scale neural compute in parallel.

CPU + GPU together = Multi-Neuraxon at speed.

[ThatsNotMyCode @ThatsNotMyCode]

https://t.co/CJ9kvJm92Y

[BCharles @bruno_charlies]

Today I showed the QUBIC project to a computer engineering professor at the university where I study Artificial Intelligence (yes, I am an AI academic).

He called me a “liar” as if he were joking with me. I sent him the Whitepaper and asked if I was “crazy” or if all these years studying development had messed with my head.

The result after analyzing the material? He bought QUBIC. What do you think I ended up doing once again? I’m not the only crazy one… a professor has now joined me in this “madness.”

But let’s get to what really matters, because this will “enlighten” your expectations in a responsible and reflective way.

As a systems developer and Artificial Intelligence student, I need to explain some of the reasons why I am investing 80% of my net worth in QUBIC.

I also want to make it clear that whenever I decide to write about QUBIC, I always present three perspectives: The entrepreneur’s view, the developer’s view, and the investor’s view.

Just for the record, today I made another deposit thanks to my patience in waiting for the opportunity I had been expecting ; a new price correction in QUBIC.

From this point on, you will understand why QUBIC is currently in my phase of maximum accumulation.

Qubic will be used as the example model, as you already know, but first I want to show you the trajectory of other AIs before they exploded in their projects.

Once you understand the information below, you will realize that QUBIC is not just a “cryptocurrency.” It is like a company (in case you forgot) developing an extremely complex AI (AGI) software.

Now, reflect on the following information:

Name of the AI: Gemini
Company that Launched it: Google (Alphabet / DeepMind)
Time of development until ready: Launched as Bard in March 2023, renamed Gemini in February 2024 (about 1 year since the initial announcement, with roots in years of DeepMind research).
Machine Learning Model: Multimodal LLM (Large Language Model with text, image, audio, and video capabilities).
Current market value after launch: Contributed to Alphabet reaching a market cap above US$ 3.5 trillion, with annual AI investments around US$ 185 billion and strong user growth (750 million monthly users).

Name of the AI: ChatGPT
Company that Launched it: OpenAI (with strong Microsoft partnership)
Time of development until ready: Founded in 2015, but ChatGPT launched in November 2022 (explosion within months after GPT-3).
Machine Learning Model: LLM (based on GPT series, generative transformers).
Current market value after launch: OpenAI valued at approximately US$ 852 billion after massive funding rounds (e.g., US$ 122 billion in one round).

Name of the AI: Claude
Company that Launched it: Anthropic
Time of development until ready: Founded in 2021 by ex-OpenAI members, Claude 1 launched in 2023 (about 2 years until the main product).
Machine Learning Model: LLM focused on Constitutional AI and safety.
Current market value after launch: Anthropic valued at US$ 380 billion (with recent rounds of US$ 30 billion).

Name of the AI: Llama (family of models)
Company that Launched it: Meta
Time of development until ready: Llama 1 launched in February 2023, with rapid iterations (Llama 3/4 in 2024-2025).
Machine Learning Model: Open-source LLM (large language models).
Current market value after launch: Contributed to Meta surpassing US$ 1 trillion in market cap, with Llama generating billions of downloads and an ecosystem (direct business value estimates of US$ 10-20 billion+ for the Llama business).

Name of the AI: Copilot
Company that Launched it: Microsoft (integrating OpenAI)
Time of development until ready: Announced in 2023, with wide rollout in 2024 (fast, leveraging US$ 13B+ investment in OpenAI).
Machine Learning Model: Integrated LLM (based on GPT).
Current market value after launch: Powers Microsoft’s AI division, expected to be the fastest to reach US$ 10 billion in annual revenue; contributes to Microsoft’s market cap above US$ 3 trillion.

Name of the AI: Grok
Company that Launched it: xAI (Elon Musk)
Time of development until ready: xAI founded in 2023, Grok launched in November 2023 (accelerated development in months).
Machine Learning Model: LLM focused on reasoning and real-time data from X.

Current market value after launch: xAI valued at around US$ 200-230 billion after rounds such as US$ 20 billion.

Final Reflection on the QUBIC Scenario: If all these AIs, based on traditional LLM models, reached billions (and even trillions in market impact) in just a few years after launch, what do you think will happen when an AI (AGI) starts running on QUBIC with evolutionary machine learning?

Be honest with yourself in your answer!

In Qubic’s model, Aigarth uses Intelligent Tissue (intelligent tissue) with ternary computing (-1, 0, +1), Useful Proof-of-Work (uPoW) that turns mining into distributed neural network training, Darwinian evolution through mutation, natural selection, and fitness functions. This creates an emergent, decentralized, and self-improving AGI, without the centralized bottlenecks of LLMs.

As soon as it is launched in the market, QUBIC has the potential to be selected as the world cradle for hosting Autonomous AI Agents, generating exponentially greater value due to its resilience, feeless scalability, and true evolutionary nature.

But the cherry on top has never been said.When an AGI is launched by QUBIC, it will attract millions of users, massively scaling the adoption of QUBIC’s AGI. In addition to regular users, we will have institutional users ; companies ; and sovereign users (governments).

Or do you think tests won’t be conducted from all over the world to see if it’s possible to develop their own tools using a decentralized AGI?

Remember the current problems: governments are racing to develop their own AI technologies. There is also huge demand for energy sources, and a race of all kinds is forming.

How much do you think QUBIC will be worth, considering it will not be an LLM, but a completely superior model?

Qubic will soon be on this list, but don’t think it will be worth just a few “billions.”

I estimate that having an AGI running with functionality and performance that meets even simple needs will already reach hundreds of billions of dollars in market cap.

If a centralized one reached trillions, imagine an AGI built the right way? Yes, gentlemen, there is no exaggeration in the calculations ; there is only the development time and getting the functionality right at launch!A tip?

Accumulate while there is still time!!

QUBIC IS INEVITABLE!

#qubic #aigarth

[Come-from-Beyond @c___f___b]

https://t.co/ZNTfgTxEhp

[Rypto @RyptoCrypto]

$QUBIC

[Come-from-Beyond @c___f___b]

Those who understand ANNs well may think it's not a big deal. And they'll be wrong. Because #Aigarth is developing a paradigm capable of creation of #AI solving any task. This means Artificial General Intelligence.

[Come-from-Beyond @c___f___b]

After discovering that anti-attractors enormously reduce energy requirement for creation of #AI, #Aigarth has discovered another technique reducing amount of energy even further. It's keeping parameter space dimensions count constant. This means choosing number of neurons and synapses in the very beginning and never changing it.

#Qubic