The Future Of Artificial Intelligence: an Intelligent Global Prediction System (I-GPS)
Prediction is the Essence of Intelligence, Natural and Artificial
Any action, event, activity or change has numberless consequences, predicted or unpredicted, intended or unintended, anticipated or unanticipated, beneficial or harmful, good or bad...
The Law of Infinite Consequences refers to all actions, physical or social, including the development and commercialization of technologies, machines and structures. It is clear that many technologies bring huge benefits for humans and much harm for nature.
The same rule applies to digital technologies, social media, online gaming, mobile phones, ML tools, or LLMs.
Intelligence is the power to predict, ideally, all major possible results and effects, outcomes and consequences.
It was the lack of predictive intelligence when the fossil fuel transportation was massively introduced, instead of e-cars at the beginning of the 20th century.
It is the want of predictive intelligence when machine rote learning tools and deepfake statistical software impersonated as AI, real machine intelligence and learning...
We need to think WHOLISTICALLY before doing something... trying to PREDICT all externalities.
For the last 2-3 years, the world has been heavily impacted by the black swan events, unpredictable, with significant consequences and externalities.
It is the COVID-19 pandemic, the Ukraine-Russia war and now the Israel-Hamas war, all with unknown unpredictable effects.
We hardly could survive and prosper without building automated intelligent global prediction systems, considering the increasing complexity of the world and its global data flow volume. By 2022, yearly total internet traffic reached 4.8 zettabytes, being equal to 150,000 GB per second or1.5 GB per person per day.
The world is full of risks and complexities and uncertainties, and humanity has been navigating it without any reliable intelligent predictive systems at local, national, international and global levels.
There are the internet and satellite surveying networks, intelligent agencies, from CIA to FSB, traditional media, from newspapers to TV networks, social media platforms, from Google to Microsoft Bing, Twitter to YouTube, social networks services, from Facebook and LinkedIn, smart phones, and other digital data processing systems.
Again, most of critical national infrastructure (CNI) providing essential services, including telecommunications, the internet, power grids, water supply networks, transportation systems, and government services are digitized.
The intelligent services across the world which are supposed to collect foreign, military and domestic intelligence to forecast the possible outcomes for national security are ineffective. Just the U.S. Intelligence Community is a coalition of 18 agencies and organizations, including the ODNI. And it is out of counting the total number of intelligence agencies responsible for the collection, analysis, and exploitation of intelligence to "produce geopolitical, economic, and security reports; monitors threats from terrorism, organized crime, piracy, and social unrest; follows social networks, etc."
The future has many surprises, threats and opportunities, risks and possibilities, like as listed in the WEF's networks of global risks, geopolitical, environmental, economic, societal and technological, migration, climate change or cybersecurity.
Why I-GPS so Critically Critical?
What we have as the GPS examples, it is the numerical weather prediction models, as Global Deterministic Prediction System (GDPS). Or, the Global Forecast System (GFS), a "National Centers for Environmental Prediction (NCEP) weather forecast model that generates data for dozens of atmospheric and land-soil variables, including temperatures, winds, precipitation, soil moisture, and atmospheric ozone concentration. The system couples four separate models (atmosphere, ocean model, land/soil model, and sea ice) that work together to accurately depict weather conditions".
What the world really wants, it is an intelligent global prediction/forecasting system (I-GPS) to forecast or predict, recommend or prevent all possible scenarios and plausible futures and their implications, as global trends and trajectories, patterns and prospects, in all major domains, from the climate change to geopolitical threats.
Provided the I-GPS, the world could avoid the "black swan" global shocks, from the COVID-19 pandemic to the geopolitical threats and conflicts, with countless economic and social and political consequences.
Today's world led for decades by globalization and geoeconomics is a world grounded in geopolitical risks, significantly reordering global structures and international relationships in 2023, like as:
Russia-NATO tensions
China-US tensions
Russia-Ukraine [civil] war
Israel-Hamas war...
Overall, there are 110 armed conflicts, as major wars, civil wars, conflicts or clashes, having significant impacts on the populations and resulting in a high number of casualties and humanitarian crises.
The regions involved in international armed conflict (IACs) or non-international armed conflicts (NIACs) are almost all the continents, excluding only Antarctica:
MIDDLE EAST AND NORTH AFRICA: MORE THAN 45 ARMED CONFLICTS + Israel-Hamas IAC
AFRICA: MORE THAN 35 ARMED CONFLICTS
ASIA: 21 ARMED CONFLICTS
LATIN AMERICA: SIX ARMED CONFLICTS
EUROPE: SEVEN ARMED CONFLICTS
There is an increasing risk of a direct global conflict of superpowers, Russia & China vs. US, having devastating consequences for the whole world.
The i-GPS is to predict all the possible scenarios, avoiding the US-China IAC, or
valuating the efficiency of the economic sanctions imposed on Russia and the support by NATO membership countries for Ukraine in the form of financial and military aid.
The i-GPS and its predictive intelligence
Prediction is the essence of intelligence, human or machine.
Science,?as a rigorous,?systematic?endeavor, builds and organizes?knowledge?in the form of?testable?explanations?and?often quantitative predictions?about the world.
Predictive intelligence is the essence of the i-GPS.
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It can be used to forecast the future and to predict the probability of outcomes for various events and complex processes, physical, chemical, biological, mental, social, digital or virtual.
Predictive intelligence is the use of world models, its scientific knowledge and theories, data and algorithms, predictive analytics, and AI/ML techniques to analyze patterns and make predictions, explanations and recommendations about future events or behaviors.
It involves collecting and analyzing large amounts of data from various sources to identify trends, patterns, and relationships that can be used to predict future outcomes and possible effects.
Predictive intelligence could be used not only in science and technology or future studies, as well as in marketing, finance, healthcare, cybersecurity or strategic policy planning to make informed decisions and predictions, recommendations and actions.
What is the difference between predictive intelligence and predictive analytics or machine learning?
Predictive intelligence and predictive analytics are related concepts, with some significant difference between the two.
Predictive intelligence refers to the use of world modeling and the sciences, data, algorithms, and machine learning techniques to analyze patterns and predict future events or behaviors.
It involves consolidating and analyzing large amounts of knowledge, global and local, with data from various sources to infer/identify CAUSAL trends, patterns, and relationships that can be used to predict or forecast future outcomes.
Predictive analytics is a subset of predictive intelligence that focuses specifically on using statistical models and algorithms to analyze historical data and make predictions about future events or behaviors.
Predictive analytics typically involves using advanced statistical techniques such as statistical inference, regression analysis, decision trees, clustering, and neural networks, driving today's statistical AI and machine learning algorithms.
Machine learning prediction, or prediction in machine learning, refers to the output of an algorithm that has been trained on a historical dataset. The algorithm then generates probable values for unknown variables in each record of the new data. The purpose of ML prediction is to project a probable data set that relates back to the original data.
This mostly applied by businesses to predict future customer behaviors and market changes, detect fraud in previous transactions, or recommend information items, products and services, from the Google search engine to the Netflix recommender system.
In essence, predictive intelligence is a broader concept that encompasses all forms of human knowledge/science/information/data/technology-driven forecasting/prediction-making, while predictive analytics is a specific approach within predictive intelligence that relies on statistical modeling and analysis.
Thus, the i-GPS is to provide accurate prediction and forecasting in traditionally very difficult areas for human intelligence, such as?geopolitical conflicts, natural disasters,?pandemics,?demography,?population dynamics?and?meteorology.
The i-GPS as a Strategic Intelligence Machine
As for the NATO/Ukraine-Russia IAC, the i-GPS could predict and prevent global consequences by forecasting a negligible probability of winning over the largest country in the world with a total area of 17,098,242 Km2 (6,601,665 mi2) and a land area of 16,376,870 Km2 (6,323,142 mi2), equivalent to 11% of the total world's landmass of 148,940,000 Km2 (57,510,000 square miles).
The i-GPS will take into account all the major causal variables, from military to technological to geographic, including a virtually infinite natural capital, "the country’s stocks of natural assets which include geology, soil, air, water and all living things.
As of 2021, Russia held natural resources amounting to an estimated total value of 75 trillion U.S. dollars, including valuable natural resources, as coal, oil, natural gas, platinum, gold, timber, diamonds, and rare earth metals, among others.
The estimated value of natural resources in the U. S. is $45 trillion, almost 90% of which are timber and coal.
Together with Iran, $27.3 trillion, China, $23 trillion, Brazil, $21.8 trillion, Saudi Arabia, $34.4 trillion, the BRIC rules the future world.
There is a natural causal relationship between the economy and the world's natural resources—as the global economy grows, demand for commodities continues to rise.
Another i-GPS predictions, Russians, as well as Chinese or Brazilians or Iranians, could be among the most prosperous nations in the future world, given the socially responsible effective smart states.
What is the Future AI?
There are three generations of the future AI to be developed at the same time, ANI and AGI, or human-mimicking/fake/false/imitating AI, the I-GPS, as Real AI, or Scientific/True AI:
ANI, Narrow, human-like AI systems (ANI), imitating parts of human intelligence (all today’s AI/ML/DL are narrow and weak AI, as LLMs, ChatGPT).
AGI, General, human-like and human-level AI systems (HLAI, Full AI, Strong AI), imitating all human intelligence (Multi-modal and multi-task AI, OpenAI Project, DeepMind AI project, etc).
I-GPS, Really intelligent, autonomous machines, augmenting and complementing humans (Causal Machine Intelligence and Learning, Man-Machine Hyperintelligence, Real Superintelligence).
In reality, there is nothing common between machine intelligence and human intelligence, if only both of them are black box data/information/knowledge systems.
Machines operate in terms of world models and causal patterns, computing power and algorithms, quantities and data, numbers and statistics, figures and digits, tokens and syntax, mathematics and probabilities, precision and accuracy.
It is a stimulus-response black box model, having its inputs and outputs (or transfer characteristics, a transfer function, system function, or network function) producing useful conclusions/information without showing any information about its internal workings, which mechanisms/explanations remain opaque/“black.”
Humans think in terms of world models but qualities, senses and meanings, concepts and ideas, thoughts and images, semantics and pragmatics, biases and prejudices.
In all, it is two different worlds, the world of quantitative/physical/cybernetic/causal machines and the world of qualitative/emotional/feeling/reasoning/live humans.
Machines are machines, humans are humans, they can only complement each other, as the I-GPS.
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