broms ױ @br6ms

Happy to share again that our bio-inspired #Neuraxon 2.0 by @VivancosDavid & @josesanchezhb with @_Qubic_ #OpenScience #AIgarth @c___f___b is showing promissing results in the most challenging #AI #AGI #benchmark #ARCAGI 3 by @fchollet @mikeknoop and team @arcprize Last Entry we get 0.21% almost double than our first entry at 0.13% Most Frontier AI's rank 0% or close to it, we are already better than most llms. Btw: 1.- We use no LLMs or VLMs or alike, just Neuraxon Architecture so no call's to expensive APIs 2.- and 0% GPUs in this case raw plain CPUs still Long road ahead to rise the rankings but stay tuned for the updates & follow the progress here: kaggle.com/competitions/a… Neuraxon is #OpenSource in GitHub github.com/DavidVivancos/… Demos & Datasets at @huggingface @ClementDelangue and team huggingface.co/spaces/DavidVi…

@cryptokendefi I would recommend to provide this feedback in the channel for this proposal so comps can actually see it. With proposals being its own section there's less activity in those channels and it's the main source of feedback that the comps see.

ASICs for #AI will be trinary.

@PumpitFox All the people who were posting this drama ,all didn't ask questions in discord, very disappointing. Seems like they'd rather farm engagement on X.

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

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While others hadn’t even seen the problem yet, $QUBIC already had the #solution ready. Think about it: it’s absurd to spend billions building massive data centers that, once switched on, fail to meet the exploding demand and deliver poor returns. Countless projects have been forced to cancel everything, leaving behind only enormous financial waste and mountains of unused advanced chips. The real revolution lies elsewhere. You don’t need to compete with the giants by building ever-larger and more expensive structures. The #key is intelligently sharing #energy and computing power through a #decentralized, efficient, and accessible #network. 🗝️🚪 #Qubic is a visionary project that looked beyond the obvious. While everyone thought the solution was reserved exclusively for Big Tech, Qubic chose the smarter path: making the impossible possible and democratizing the future of computing. The future isn’t built by centralizing power. It’s built by distributing it. And @_Qubic_ understood this first.​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​ #AI #AGI #AIgarth #Neuraxon

Cointelegraph @Cointelegraph

3 months ago

🚨 LATEST: BlackRock CEO Larry Fink predicts a futures market for computing power will emerge, as global demand outpaces supply. "There is not an AI bubble. We have supply shortages."

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@cryptokendefi 🔥🔥

@CadeONeill Low target

@Quorumdidit @LondonCoinGuy there seems to be a trend where people talk shit for some reason but their emotionally attached still and cant get themselves to sell, its very weird tbh. just be a man and sell instead of complaining on X

@JLewids @Quorumdidit yeah bud sorry to tell you but the cycle is the same

#AIgarth progress looks like improving a single branch of a technology tree in a strategy computer game. It's all about energy. Trinary and CPU were the easiest discoveries. Anti-attractors felt like discovery of an alien tech, we still don't fully understand how to unlock its potential. Recently we removed some things which happened to be different aspects of the same phenomenon (separation to training and testing datasets, precise representation of data). For that we looked at the whole concept pretending to be a 4-dimensional being. Now we have to find much more energy than is currently available to the #Qubic ecosystem. But why should hoomans and their computers do all the work?.. So here is the plan: 1. Implement Outsourced Computations feature to give #AI ability to affect the outer world. 2. Run #IntelligentTissue on the network. 3. Target mining power towards improvement of that #IntelligentTissue. 4. Set the main task for that thing to bringing more energy into the ecosystem.

@Andy_Qus @_Qubic_ Keep up the great work Andy

@stepbystep1983 Microsoft with trits, Nvidia with evolutions, other companies with other aspects copying #Aigarth would be happy to read the details. But I prefer prioritizing interests of $QUBIC holders.

x.com/i/article/2044…

@0xSweep

x.com/i/article/2042…