Machine Intelligence and Learning (MIL?): Human AI/GenAI/LLMs as utter nonsense
AI, ANI, AGI, ASI as Utter Nonsense
Humans are singular creatures, which could be produced only by natural evolution, with all its complexity. Each human is absolutely unique, individual and special, regardless that society tries to make us ordinary and common and usual as biorobots.
Humans are classified under the genus Homo (man) and under the species sapiens (wise). The scientific name for a human is a Homo sapiens.
It is utter nonsense to define and design Artificial Intelligence (AI) as Human AI (HAI) or Artificial Human Intelligence (AHI):
“the simulation of human intelligence processes by machines, especially computer systems”, with all the branches as pictured below:
Or, AI as “technology that enables computers and machines to simulate human learning, comprehension, problem solving, decision making, creativity and autonomy” (IBM).
Or, AI as a technology with human-like problem-solving capabilities. AI in action appears to simulate human intelligence—it can recognize images, write poems, and make data-based predictions.
Or, AI as artificial general intelligence (AGI), a field of theoretical AI research that attempts to create a thinking machine or computer program with human comprehension and cognitive capabilities, software with human-like and human-level intelligence and the ability to self-teach, (Amazon),
AHI as Artificial superintelligence (ASI), super AI or superintelligent AI, a software-based system with intellectual powers beyond those of humans, including cognition, general intelligence, problem-solving abilities, social skills and creativity, across a comprehensive range of categories and fields of endeavor.
Again, all today's AI is weak AI or narrow AI, "AI systems limited to computing specifications, algorithms, and specific tasks they are designed for" have no intelligence at all.
The Singularity of Human Beings
Humans are singular creatures, which could be produced only by natural evolution, with all its complexity. Each human is absolutely unique, individual and special, regardless that society tries to make us ordinary and common and usual as biorobots.
Humans are classified under the genus Homo (man) and under the species sapiens (wise). The scientific name for a human is a Homo sapiens.
It is sapiens, INTELLECT, what distinguish human beings.
To be human is to be intelligent and be creative and innovative, as well as to be aware of ourselves, our surroundings, and our internal experiences. to feel, love and hate, have compassion. This self-awareness gives us the ability to reflect on our thoughts and emotions, contemplate our actions, and engage in critical thinking.
Again, each human is being the only one of its kind, and no machine could replicate, mimic or simulate you, your body, brain, brains, behavior or business,
But any intelligent entity, be it humans. machine intelligence, robots or aliens. necessitates intelligence, intentionality and agency to be able to encode, make sense and interact with the world.
Machine Intelligence and Learning (MIL?)
Real AI is not about fully replicating human creativity, emotions, or consciousness, but after the world modeling, simulating, understanding and interacting programs, algorithms, methods and techniques.
Or, machine intelligence and learning (MIL) models postulate, suggest or assume the existence, fact, or truth of the world. the universe, REALITY, as a basis for learning, inference or action.
The world modeling (simulating, learning, understanding and interaction) power is a necessary condition for any real intelligence, natural, real, artificial or alien.
As much as there is NO modern science and engineering or human minds without world modelling, there is NO real artificial intelligence (AI), artificial narrow intelligence (ANI), artificial general intelligence (AGI) or artificial superhuman intelligence (ASI) without the world modeling and simulation capabilities.
We advance a paradigm shift from the AI/AGI/ASI models of human intelligence into the MIL models of the world of reality, physical, mental, social, digital, virtual.
No autonomous existences could exist without having some world models, instinctively feeling or intelligently knowing how the world is organized and works, its reality and causality, structure, complexity and behavior.
Modelling is an essential and inseparable part of all substantial techno-scientific disciplines and knowledge domains.
The world models are fundamental to "what is what and who is who and why is why" and to the development of real-world, general intelligent systems as the Machine Intelligence and Learning (MIL?) machines.
If your would-be intelligent machines, AI systems and machine learning models or neural network algorithms machines or large language models (LLMs), have no world modeling capabilities, they are unintelligent by the very design,
Or, SOTA AI/ML/LLMs are not Generalists, regardless that GPT-4, Bard, Llama 2, or Claude involve a wide range of topics, execute a wide range of tasks, handle multimodal inputs and outputs, operate in multiple languages, and “learn” from zero-shot or few-shot examples, they lack the real-world learning and intelligence of <world modeling> generality and performance.
Mustafa Suleyman, the CEO of Microsoft AI, the co-founder and former head of applied AI at DeepMind, proposed his version of AGI/ACI (“Artificial Capable Intelligence”) as the “Modern Turing Test,” in which an AI would be given $100,000 of capital and tasked with turning that into $1,000,000 over a period of several months.
Now, we suggest more challenging TT, in which Machine Intelligence and Learning (MIL?) would be given $1T of capital and tasked with turning our decaying dumb world into an all-sustainable habitat over a period of 5-7 years. It makes less than a half of the United States' war spending in Afghanistan.
Resource
Researchers gave successive versions of a large language model information produced by previous generations of the AI — and observed rapid collapse.
Artificial intelligence in its current form is based on the wholesale appropriation of existing culture, and the notion that it is actually intelligent could be actively dangerous
SUPPLEMENT: MIL = Machine Intelligence + Machine Learning Algorithms
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ML can be categorized into three main types:
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This involves learning from labeled data. Algorithms are trained on input-output pairs to make predictions on new data.
● ???????????????????????????? (???????????????????? ????????????????????):
?Naive Bayes?Support Vector Machines?K-Nearest Neighbors?Decision Trees/Random Forests?Neural Networks
● ???????????????????? (???????????????????? ???????????????????? ????????????):
?Generalized Linear Models?Logistic Regression?Support Vector Regression?Ensemble Methods?Neural Networks
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Algorithms discover hidden patterns or groupings in data without ?labeled responses.
● Clustering (grouping data):
?K-means, Fuzzy Means?Gaussian Mixture Models?Hidden Markov Model?Spectral Clustering?Neural Networks
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In this type, an agent learns by interacting with its environment to maximize rewards.
● ??-???????????????? (???????????????? ?????????????? ??????????????):
Policy Grading?Trust Region Policy Optimization?Proximal Policy Optimization?Hindsight Experience Replay?Deep Q Neural Networks
Each algorithm has its strengths and is suited for different tasks.