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The almanac about new method of information processing
What's actually wrong with the concept of AI
Biology and artificial intelligence
Cognitive science: a beginning without an end
Holism and brain studies
Theory of Active Perception
Why perception is necessary for modeling human-like thinking
What's actually wrong with the concept of AI
Evolution of ideas underlying AI: Brief Description
Biology does not understand how the brain works
Why AI does need biology after all
How far artificial neurons are from the real ones
Creating something really similar to how the brain works
Cognitive science: a beginning without an end
Cognitive science has never produced anything practical
Consciousness is not amenable to science
No one knows what consciousness is, everyone keeps talking about it
A sudden idea — the quantum nature of consciousness
Orchestrated objective reduction: what it is and what for
Another theory of consciousness: the integrated information theory
Global workspace theory
Conscious and unconscious thinking. Questions to an academic
Questions for Theories of Consciousness
Ultimate ways to study consciousness without cutting into the brain
Albert Einstein suspected something
Why has psychoanalysis progressed more than science without scientific methods
Insights from intuition and deep observation are not exhausted and are as good as AI
There is no computation in the brain as we all know it. What kind is there?
Why it’s unreasonable to use word Learning in relation to AI
There is a different calculability: what Hilbert and Gödel discovered
Why the brain should be studied as a whole
TAPe models the workings of the mechanisms of perception
Language is a complete system, it’s how it should be studied
The principles by which the Language of Thought functions
The isomorphism of Chinese characters and TAPe
T-Bit: a unit of information 1000x of times more efficient
AI
MEMORY
CHAT GPT
SCIENCE
What's actually wrong
with the concept of AI
Computer science has developed to a stage where delivering solutions/products doesn’t require direct programming. Many consider it a real breakthrough. The phenomenon is called
artificial intelligence
or, more rarely,
machine learning
. Even as we write this, a revision of AI achievements and efficiency is gradually taking root.
01
02
In its current state, the power of AI is greatly exaggerated. For now, it’s just a brilliant engineering solution. To qualify as intelligence — not to mention AGI — at least in some way, machine learning needs elements of human thinking.
The term
artificial intelligence
was coined in 1956 by John McCarthy, one of the founding fathers of the discipline. He defined AI as the "science and technology of creating intelligent machines."
04
AI does not, and cannot, possess any of the above. The one thing that has really been done well is ML methods for algorithmization of endless databases. Modern AI, or rather machine learning to be more accurate, can be referred to as database algorithmization (finding connections without understanding the "meaning"), a kind of infinite memory.
07
As such, intelligence (from Latin
intellectus
) means "understanding", “reasoning." It is derived from a combination of the words
intelligere
, i.e.,
"to perceive", "to cognize", "to think", and
legere
, i.e., "to collect." Consequently, to be called intelligence, artificial intelligence must be able to reason, understand, perceive, and think.
06
Scientists, developers, and engineers seem to have long ago "lost" the "super idea" of "artificial intelligence", which was about creating an artificial mind, an emulation of how the human brain functions. The level of AI development currently compared to the human brain is as infinitely far from it as a calculator.
03
But there is still no single answer to the question of what intelligence is. Philosophy has not yet resolved the question of the status of the human intellect. No criterion has yet been set as to when computers can be said to have achieved “sapience." Will we be able to come up with any such test at all before we find a universal (accepted by all) philosophical, metaphysical, and scientific answer to the question of what intelligence, let alone consciousness, is?
05
We know robots whose mechanics were "taken" from the mechanics of the human body. Airplane wings copy the way bird wings work. In "artificial intelligence", biology-related ideas are virtually non-existent, and at least for this reason, no comparison could be made to natural intelligence. It has NOTHING to do with thinking.
14
So what exactly is the problem? Let's try and look at it from another angle: artificial intelligence has NOTHING related to biology except for the word
neuron
, and an artificial neuron has nothing to do with a natural one.
13
As we can see, ChatGPT and its analogs are not capable of "human-like" learning and could only write a freshman term paper if consuming gigantic amounts of energy.
12
After graduating from school, institute, etc., people aren't supposed to refresh what they already learned. The purpose of learning is to transform the acquired knowledge into skills to be further used and improved. Otherwise, particularly talkative parrots could also be defined as multitaskers.
11
Today, there's ChatGPT, alongside Gemini and the like, and they seem to be solving a variety of problems. But these AI models are still a world away from human intelligence.
10
But this has not been done — and is unlikely to be. At most, this could qualify as some, albeit huge, set of facts/data/information, but certainly not a world model. It's like referring to an encyclopedia as a world model.
09
Modern multi-tasking AI systems were made to focus on games and tasks formulated in natural language. Thus, AI people are convinced that the self-supervised learning approach, for example, will allow creating a certain world model (e.g., for a game or a language) and then reusing that model to solve various end tasks rather than just the one for which that solution was created and customized.
08