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Meta-AI: как создать настоящий ИИ для платформ Metaverse, или что не так с суперкомпьютером ИИ следующего поколения от Meta

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Meta Platforms (former Facebook) has introduced the AI Research SuperCluster (RSC) as the world’s fastest AI supercomputers to accelerate AI research and help us build for the metaverse.

RSC is supposed to help us build new and better AI models that can learn from trillions of examples; work across hundreds of different languages; seamlessly analyze text, images and video together; develop new augmented reality tools and more. All to pave the way toward building technologies for the next major computing platform — the metaverse, where AI-driven applications and products will play an important role.

Before the end of 2022, though, phase two of RSC will be complete. At that point, it’ll contain some 16,000 total GPUs and will be able to train AI systems “with more than a trillion parameters on data sets as large as an exabyte.” (for comparison’s sake, Microsoft’s AI supercomputer built with research lab OpenAI is built from 10,000 GPUs.)

The speculative technology market has voted for such a brute-force compute power metaverse idea by dumping the Meta stocks, and Meta erased $250 Billion in value, biggest one-day wipeout in history, while Zuckerberg personally lost 29 billion (about 24 percent) of his net worth.

The next generation of AI is not about powerful supercomputers capable of quintillions of operations per second, but about a really intelligent AI capable of interacting with the world, physical or digital, basing on the comprehensive world model and smart data science and engineering analytics, algorithms, models and techniques.

What is the next best technology?

It is Causal Machine Intelligence and Learning, innovated as Meta-AI or Trans-AI.

Meta-AI is an integrative general-purpose technology for advanced digital and emerging technologies, like as

Smart Robotics and Automation,

Blockchain technology,

Nano-, bio-neuro-, cognitive, info-, or social technologies,

the IoT, Edge Computing, Smart Devices,

Metaverse technology,

the Extended Reality of AR and VR, etc.

Machine learning deep neural networks could become the real start of the next best Meta-AI technology, as automated autonomous artificial man-machine meta-intelligence.

The ecosystem of the Meta-AI technology is:

Reality = the World = Everything >

Mapping = Representing = Modeling >>

World Data << World Information << World Knowledge >>

All Science > Statistics + Mathematics <<

Data Science and Engineering + Computer Science and Engineering >

Deep Neural Networks (DNNs) = DL << ML << AI =

Narrow AI << Weak AI << Strong AI = AGI << Artificial Superintelligence <<

Real AI + Human Intelligence =

Trans-AI or Meta-AI =

DCN (Deep Causal Networks) + Global Data Ontology + Global Knowledge Graph + Supercomputing =

New Reality (Physical Reality + Digital Reality = Metaverse = Transworld) 

Trans-AI: How to Build True AI or Real Machine Intelligence and Learning

We are at the edge of colossal changes.

This is a critical moment of historical choice and opportunity. It could be the best 5 years ahead of us that we have ever had in human history or one of the worst, because we have all the power, technology and knowledge to create the most fundamental general-purpose technology (GPT), which could completely upend the whole human history. The most important GPTs were fire, the wheel, language, writing, the printing press, the steam engine, electric power, information and telecommunications technology, all to be topped by real artificial intelligence technology. Our study refers to Why and How the Real Machine Intelligence or True AI or Real Superintelligence (RSI) could be designed and developed, deployed and distributed in the next 5 years. The whole idea of RSI took about three decades in three phases.

The first conceptual model of TransAI was published in 1989. It covered all possible physical phenomena, effects and processes. The more extended model of Real AI was developed in 1999. A complete theory of superintelligence, with its reality model, global knowledge base, NL programing language, and master algorithm, was presented in 2008. The RSI project has been finally completed in 2020, with some key findings and discoveries being published on the EU AI Alliance/Futurium site in 20+ articles.

The RSI features a unifying World Metamodel (Global Ontology), with a General Intelligence Framework (Master Algorithm), Standard Data Type Hierarchy, NL Programming Language, to effectively interact with the world by intelligent processing of its data, from the web data to the real-world data. The basic results with technical specifications, classifications, formulas, algorithms, designs and patterns, were kept as a trade secret and documented as the Corporate Confidential Report: How to Engineer Man-Machine Superintelligence 2025.

As a member of EU AI Alliance, the author has proposed the Man-Machine RSI Platform as a key part of Transnational EU-Russia Project. To shape a smart and sustainable future, the world should invest into the RSI Science and Technology, for the Trans-AI paradigm is the way to an inclusive, instrumented, interconnected and intelligent world.



Trans-AI: How to Build True AI or Real Machine Intelligence and Learning Meta-AI

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