The AI Singularity or Singularity AI: Global Data Engine and AI Industry 4.0

General observations why humanity is in need of machine superintelligence.

Here is an example of human confirmation bias re. how the Space Age could be missed.

In 1954, Mstislav Keldysh,?Sergei Korolev?and?Mikhail Tikhonravov?submitted a letter to the Soviet Government proposing development of an?artificial satellite?to orbit the Earth. The letter was rejected, but?some Soviet newspaper MT-translated articles?influenced American authorities to start satellite programs. This had culminated in the world's first satellite,?Sputnik 1?in October 1957, which marked the beginning of mankind's?Space Age.

We are plagued with a multitude of cognitive biases, causing all possible and impossible problems, risks and threats, from inequalities and injustices to never-ending conflicts and wars.

In all, intelligence, human or machine, depends on the key variables of the world of reality:

world's data/statistics/variables/nominal/ordinal/interval/ration/numeral

world's models/theories/laws/rules/schema/systems

algorithms/programs/software

memory/knowledge bases/databases

computing power/brain/hardware.

Human intelligence is fixed by the natural, biological limitations on its data processing, memory capacity and computational power of the brain. Machines are free to grow their data, algorithmic, memory and computing power capacities without limitations.

Some naively believe that the AI algorithms running on stable quantum computers could unlock a superintelligence.

It is hardly, for the core of [super]intelligence is the world's models, which is still the human mind's prerogative.

Ada Lovelace, the first computer programmer, was a rare mind who imagined a "thinking machine" capable of reasoning about "all the subjects in the universe", writing the program for the theoretical device, the Analytical Engine.

In other words, omniscience is the key attribute of the Singularity?AI, which model prototype could be completed by 2025-2026. [Trans-AI: How to Build True AI or Real Machine Intelligence and Learning]

Again, the foundation model AI of /NLP/NLG/DML algorithms?pre-trained with multi-million costs energy-hungry extremely large data sets scraped from the public internet are defective by their design.

They are lacking the world's data/knowledge, codified by a comprehensive and consistent condensed scientific world model (global ontology) and world's data framework:

Real AI > The AI Singularity AI = World's Knowledge + Data/Statistics Ontology + Foundational Model (DL)?+ LLMs (Bert, GPT-3, Chat GPT, BLOOM, etc.)?+ Narrow AIs +...?

It looks like Google's?Bard NLP/AI has better prospects here, regardless of its first demo mistakes, again, done due to lack of the world model; for if you believe its?CEO:?"Bard seeks to combine the breadth of the world’s knowledge with the power, intelligence and creativity of our large language models".

The Singularity is everywhere

The AI singularity is coming now, in all different ways, via specialized AI hardware and software, ML models and DL algorithms, LLMs, self-driving vehicles, IoT, intelligent devices, smart assistants, trading algorithms, intelligent humanoid robotics, etc.

The issue is a man-machine-machine-man interaction, a universal AI interface, which is interoperating and integrating all AI/ML/DL models and intelligent applications.

From one side, the Narrow/Weak AI (ML, DL, ANNs) technology has been exhausted. Its trial and error heuristic rules cost us a couple of billions of years of biological evolution history. Unsupervised, supervised, semi- or self-supervised learning or reinforcement learning (RL), without a consistent and comprehensive scientific internal models of reality, is the way to nowhere, if you don't have behind some billion of years for your learning and experience.

From other side, it is transforming to Trans- AI or Meta-AI Technology or AI Singularity:

Artificial Intelligence, Machine Learning, Deep learning Artificial Neural Networks +

Data Analytics +

Robotics +

6G +

IoT +

Digital Realities (XR, VR, AR, MR) +

Autonomous Mobility +

Humanoid Robots +

AI Defence + Cybersecurity +

Metaverse +

Meta-AI or Trans-AI (Real Machine Intelligence and Learning), Real ASI or Singularity AI

Singularity as the most critical construct ever

Within 3 decades, the idea of singularity has become one of the most critical conceptions ever.

In 1993 the magazine?Whole Earth Review?published “Technological Singularity” by?Vernor Vinge, who imagined that future information networks and?human-machine interfaces?would lead to novel conditions with new qualities: “a new reality rules.”?

The technological singularity marks the future state of the world, when:

• technology growth is out of control and irreversible, due to a recursive self-improvement of intelligent machines and intelligence explosion effect,
• intelligent and powerful technologies unpredictably and radically transform our reality,
• a synthesis of emerging technologies will radically change all the realities, physical, mental, social, digital or virtual.

The AI would involve computer hardware, software, programs and algorithms, as becoming so advanced that?it transcends all human intelligence, erasing any distinctions between humanity and computing machinery, and emerging as AI Singularity or Singularity AI, Global AI, Real AI, Real Superintelligence, or Trans-AI.

The AI Singularity is to emerge as the summit of all human knowledge and practice:

Mythology > Religion > Metaphysics > Philosophy > Mathematics > Science & Technology > Computing Machines > the Internet/WWW > Emerging Technologies > NAI/ML/DL > BCI > Human Intelligence > Digital Superintelligence >?Global Human-AI Superintelligence (RSI) = Trans-AI = Man-Machine Superintelligence = AI Singularity

Singularity, Technological Singularity, Singularity AI or AI Singularity

In all, there are five kinds of singularity, leaving aside mathematical singularities (Y = 1/X):

• Cosmological singularity, gravitational?singularity, spacetime?singularity?when gravity is so intense that the laws of physics cease to act, spacetime curves infinitely, gravity is infinite, if to exclude the causal set theory of space-time atoms. The physical "singularities" are suggested in the centers of black holes and at the beginning of the?Big Bang, as conical or curved or naked singularities.?

• Non-AI singularity, as emerging technologies, from blockchain to molecular nanotechnology.
• Human AI singularity, as an AGI or ASI, human-like superintelligence, hyperintelligence, or superhuman intelligence, superhuman or trans-human minds, when an intelligent human-like agent is far surpassing the brightest and most gifted human minds or all human intelligence, or when human brains are scanned and digitized, creating "uploads" or digital versions of human consciousness, or when intelligence amplification of human brains by bioengineering or brain-computer interfaces.
• Superhuman or trans-human minds, when human brains are scanned and digitized, creating "uploads" or digital versions of human consciousness, or when intelligence of human brains amplified by bioengineering or brain-computer interfaces.
• Singularity AI, Real, Non-Human AI singularity, complementing human intelligence, Ultra-intelligence, Trans-AI, Meta-AI, or Global AI, as parts of Man-Machine Superintelligence, which is to interact with the world with all the entirety of data/information/knowledge, in consistent and comprehensive and useful ways.

Most predictions relate to the fictitious human-like superhuman AI singularity, as it is pictured in Ex Machina.

Predictions of Human Finality

Good (1965) predicts an ultraintelligent machine by 2000, Vinge (1993) predicts greater-than-human intelligence between 2005 and 2030, Yudkowsky (1996) predicts a singularity by 2021, and Kurzweil (2005) predicts human-level artificial intelligence by 2030, Moravec (1998/1999) predicts human-level artificial intelligence by 2040, and intelligence far beyond human by 2050. Kurzweil predicts human-level intelligence by 2029 and billion fold intelligence and singularity by 2045. Four polls of AI researchers (2012 and 2013) suggested a confidence of 50% that (AGI) would be developed by 2040–2050.

Real AI vs. Fake AI

Today’s AI is broadly defined in two categories: Fake AI (human artificial narrow intelligence (HANI) and human artificial general intelligence (HAGI)) and Real/True AI, as Causal Machine Intelligence and Learning, or the Singularity AI.

Most of what we know as AI today has narrow and weak intelligence – where a particular system addresses a particular problem. Unlike human intelligence, such narrow AI intelligence is effective only in the area in which it has been trained: self-driving, fraud detection, facial recognition or social recommendations. To date, HAGI does not exist, and hardly ever appears.

The false AI is: “AI as the simulation of human thought processes in a computerized model. AI involves self-learning systems that use data mining, pattern recognition and natural language processing to mimic the way the human brain works (IBM, Fundamentals)”.

Or, “Artificial Intelligence as an attempt to make a computer, a robot, or other piece of technology ‘think’ and process data in the same way as we humans do. AI therefore has to study how the human brain ‘thinks’, learns, and makes decisions when it tries to solve problems or execute a task” (Microsoft, Fundamentals of AI). It is studied by the sciences as below:

Mathematics, Linear Algebra, Calculus, Probability theory and Statistics

Cognitive Science, Neuroscience, Linguistics

Computer Science, Programming

The true AI: AI as the simulation and modelling of reality and causality, its entities and processes, in a computerized model. AI involves autonomous self-learning systems that use real-world data processing, causative pattern recognition and NL semantic processing to effectively interact with the world, systems and people. It is studied by the sciences and engineering as below:

Philosophy, Ontology, Epistemology, Semantics, Logic, Ethics

Mathematics, Linear and Abstract Algebra, Set Theory and Category Theory, Calculus, Probability theory and Statistics

Data Science and Engineering

Cognitive Science, Linguistics

Computer Science, Programming

Science, Physical, Social and Technological Sciences

To qualify as real AI, a system must exhibit dynamic intelligence and transfer learning, autonomy and adapting. For this reason, common decision-making systems, automation, statistical machine learning and experts systems, or rules-based AI, are not true AI.

In all, real-world data/information/knowledge, causal world models and algorithms and smart computational infrastructure form the foundation of the AI singularity to be emerging by 2025–2030.

Global AI Data Pyramid: World Data Machine

For superintelligent machine, all world's data falls into one or more of five categories:?nominal,?ordinal,?interval,?ratio, and numeral/numbers, going as the levels or scales of measurements.?

• Nominal data/numbers, the simplest data type, classifying (or naming) data without any relationship, dividing variables into mutually exclusive label categories,?as basic ontological categories, countries, species of animals or PII labels (see the Supplement).
• Ordinal data/numbers,?classifying data but it introduces the concept of ranking, as all hierarchical?ontological categories

• Interval data/numbers,?both classifying and ranking data (like ordinal data) but introduces continuous measurements, as the time of day or temperature measured on either the Celsius and Fahrenheit scale.?
• Ratio data/numbers,?it classifies and ranks data, and uses measured, continuous intervals, just like interval data. But, unlike interval data, ratio data has a true zero,?an absolute, below which there are no meaningful values. All physical quantities, as mass, speed, age, or weight are examples?of the?RD
• Numeral data/Numbers (Digital data or?analog data?),?they?count,?measure, order, and?label, number sets or number systems, N-natural numbers, Z-integers, Q-rationals, R-reals and C-complex numbers (number theory, set theory, arithmetic, statistics, algebra, probability theory)??

The first four classes were introduced in 1946 by the psychologist Stanley Smith Stevens,?as a level of measurement?or?scale of measure,?widely used in sciences and engineering, statistics, data analytics, data science and business marketing. What is missing is the base, ground, or foundation of any real metrics, the base of reference and of?measurement?units for counting or measuring,?labeling and ordering,?numbers.

They are used for counting and measuring, for labels (as with?numbering schemes for assigning nominal numbers to entities, names, ID numbers, routing numbers, telephone numbers, IP addresses), for ordering (as with?serial numbers), and for codes (as with?ISBNs, bank codes, postal codes)".

In all, it is a hierarchical scale, each level builds on the one that comes before it, as?nominal numbers?> ordinal numbers > interval numbers > ratio numbers > numbers.

It is crucial that for the singularity AI intelligent machines, the Data Universe Pyramid is replacing the?DIKW pyramid, the?DIKW hierarchy,?wisdom hierarchy,?knowledge hierarchy,?information hierarchy, information pyramid, or data hierarchy,?the Data, Information, Knowledge, Wisdom.

The Data Universe Pyramid is the soul of the World Data Machine, the engine of the Global AI.

Global AI Industry 4.0

The AI singularity is to transform all industries, however they are classified, creating real AI industry 4.0:

construction industry,

chemical industry,

petroleum industry,

automotive industry,

electronic industry,

power engineering and power manufacturing (such as gas or wind turbines),

meatpacking industry,

hospitality industry,

food industry,

fish industry,

software industry,

paper industry,

entertainment industry,

semiconductor industry,

cultural industry,

and poverty industry.

Every of five sector is to be transformed:

primary (extraction and agriculture),

secondary (manufacturing),

tertiary (services),

quaternary (knowledge), based on pure knowledge and skill of a person and includes knowledge-oriented economic sectors such as information technology; media; research and development; information-based services such as information-generation and information-sharing; and knowledge-based services such as consultation, education, financial planning, blogging, and designing. It consists of intellectual industries providing information services, such as computing and ICT, consultancy and R&D.

quinary, focus on control, such as government, and creation of information and new technologies; senior business executives, government officials, research scientists, financial and legal consultants, etc; the highest level of decision making or policy making.

AI Industry X.0 is the DATA-intensive transformation of manufacturing (and related industries) in a connected environment of AI (AI engines, machine learning, Robotic Process Automation), big data, people, processes, services, systems, IoT, cyber-physical systems and machines, with the generation, leverage and utilization of real world data and information to realize smart industry.

WHEN WILL ARTIFICIAL INTELLIGENCE REACH SINGULARITY?

SUPPLEMENT: PII as Nominal Data

Personal Identifiable Information (PII) is a label used to describe data that directly or indirectly identifies a specific individual.

PII include names, addresses, biometrics and alphanumeric account numbers.

• Name -- includes full names, maiden names, mother‘s maiden names, nicknames and aliases.
• Address -- includes street addresses, email addresses,?IP addresses?and?MAC addresses.
• Biometrics -- includes photographs, x-rays and other?types of bio-based data?such as fingerprints.
• Alphanumeric account numbers -- includes telephone numbers, driver‘s license numbers, taxpayer IDs, patient IDs, vehicle registration numbers, credit card numbers, Social Security number, etc.

PII data has to be collected, stored and destroyed in accordance with compliance rules and regulations.