Rhys Lee








The contemplation of computation and Turing Machine.

Self-aware systems and consciousness.


Artificial Neural Network in comparison to biological counterparts.


Searching for the Gestalt of a Biological neural network.

Intelligence by adventitious incidents and their principium.

My model of artificial neural network.

Self-improvable systems are intelligent.

The contemplation of theoretical intelligence.

Is Hyper-Intelligence self-contradictory?

Intelligence and its manifestation.


The ultimate subset, Intelligence and Computation.

Computational Intelligence or Computational Unintelligence, the real boundary.

Artificial computation, and its indefinite plateau.

Convolutional Neural Network, the spatial-sensitive abstraction.

Evaluation of Fully-Connected Layers in Convolutional Neural Networks

Artificial intelligence, a misused definition.

Consciousness, evidence of  biological intelligence?

Sociology & Politics

Individuality is a functional delusion

Stability of Regimes through transformation

The power of Materialism

Changing role of private companies

Are education institutions competent to educate the talented

The disruptive effects of Technology

A society of absolute wealth and poverty

Who hebetates the population

Ethics, the vital and constantly failing social organ

Traces of extraterrestrial influence in society

The power of faith and religion

The essential differences between Autocracy and Democracy

Ethics, the vital and constantly failing social organ

Gradational transformation to post-AI society

Diminishing appeal of Democracy

The hidden structures and how society really works






AI am


& Perception

updated: 12-13-2014

Human intelligence

Human intelligence is the intellectual capacity of humans, which is characterized by perception, consciousness, self-awareness, and volition. Through their intelligence, humans possess the cognitive abilities to learn, form concepts, understand, and reason, including the capacities to recognize patterns, comprehend ideas, plan, problem solve, and use language to communicate. Intelligence enables humans to experience and think.


Animal and plant intelligence

The common chimpanzee can use tools. This chimpanzee is using a stick to get food.

Although humans have been the primary focus of intelligence researchers, scientists have also attempted to investigate animal intelligence, or more broadly, animal cognition. These researchers are interested in studying both mental ability in a particular species, and comparing abilities between species. They study various measures of problem solving, as well as numerical and verbal reasoning abilities.

It has been argued that plants should also be classified as being in some sense intelligent based on their ability to sense the environment and adjust their morphology, physiology and phenotype accordingly.


Artificial intelligence

Artificial intelligence (or AI) is both the intelligence of machines and the branch of computer science which aims to create it, through "the study and design of intelligent agents" or "rational agents", where an intelligent agent is a system that perceives its environment and takes actions which maximize its chances of success. Achievements in artificial intelligence include constrained and well-defined problems such as games, crossword-solving and optical character recognition and a few more general problems such as autonomous cars. General intelligence or strong AI has not yet been achieved and is a long-term goal of AI research.

Among the traits that researchers hope machines will exhibit are reasoning, knowledge, planning, learning, communication, perception, and the ability to move and manipulate objects. In the field of artificial intelligence there is no consensus on how closely the brain should be simulated.



Neural Network

Examinations of humans' central nervous systems inspired the concept of artificial neural networks. In an artificial neural network, simple artificial nodes, known as "neurons", "neurodes", "processing elements" or "units", are connected together to form a network which mimics a biological neural network.


There is no single formal definition of what an artificial neural network is. However, a class of statistical models may commonly be called "neural" if it possesses the following characteristics: contains sets of adaptive weights, i.e. numerical parameters that are tuned by a learning algorithm, and capability of approximating non-linear functions of their inputs. The adaptive weights can be thought of as connection strengths between neurons, which are activated during training and prediction.


Neural networks are similar to biological neural networks in the performing of functions collectively and in parallel by the units, rather than there being a clear delineation of subtasks to which individual units are assigned. The term "neural network" usually refers to models employed in statistics, cognitive psychology and artificial intelligence. Neural network models which command the central nervous system and the rest of the brain are part of theoretical neuroscience and computational neuroscience.


When used for image recognition, convolutional neural networks (CNNs) consist of multiple layers of small neuron collections which look at small portions of the input image, called receptive fields. The results of these collections are then tiled so that they overlap to obtain a better representation of the original image; this is repeated for every such layer. Because of this, they are able to tolerate translation of the input image.[4] Convolutional networks may include local or global pooling layers, which combine the outputs of neuron clusters.[5][6] They also consist of various combinations of convolutional layers and fully connected layers, with pointwise nonlinearity applied at the end of or after each layer.[7] It is inspired by biological processes. To avoid the situation that there exist billions of parameters if all layers are fully connected, the idea of using a convolution operation on small regions has been introduced. One major advantage of convolutional networks is the use of shared weight in convolutional layers, which means that the same filter (weights bank) is used for each pixel in the layer; this both reduces required memory size and improves performance.[3]


Some time delay neural networks also use a very similar architecture to convolutional neural networks, especially those for image recognition and/or classification tasks, since the "tiling" of the neuron outputs can easily be carried out in timed stages in a manner useful for analysis of images.[8]


Compared to other image classification algorithms, convolutional neural networks use relatively little pre-processing. This means that the network is responsible for learning the filters that in traditional algorithms were hand-engineered. The lack of a dependence on prior-knowledge and the existence of difficult to design hand-engineered features is a major advantage for CNNs.





The way you are supposed to be, Omnipotent.

Consciousness is the quality or state of awareness, or, of being aware of an external object or something within oneself. It has been defined as: sentience, awareness, subjectivity, the ability to experience or to feel, wakefulness, having a sense of selfhood, and the executive control system of the mind. Despite the difficulty in definition, many philosophers believe that there is a broadly shared underlying intuition about what consciousness is. As Max Velmans and Susan Schneider wrote in The Blackwell Companion to Consciousness: "Anything that we are aware of at a given moment forms part of our consciousness, making conscious experience at once the most familiar and most mysterious aspect of our lives."


Western philosophers since the time of Descartes and Locke have struggled to comprehend the nature of consciousness and pin down its essential properties. Issues of concern in the philosophy of consciousness include whether the concept is fundamentally coherent; whether consciousness can ever be explained mechanistically; whether non-human consciousness exists and if so how it can be recognized; how consciousness relates to language; whether consciousness can be understood in a way that does not require a dualistic distinction between mental and physical states or properties; and whether it may ever be possible for computing machines like computers or robots to be conscious, a topic studied in the field of artificial intelligence.


At one time consciousness was viewed with skepticism by many scientists, but in recent years it has become a significant topic of research in psychology, neuropsychology and neuroscience. The primary focus is on understanding what it means biologically and psychologically for information to be present in consciousness—that is, on determining the neural and psychological correlates of consciousness. The majority of experimental studies assess consciousness by asking human subjects for a verbal report of their experiences (e.g., "tell me if you notice anything when I do this"). Issues of interest include phenomena such as subliminal perception, blindsight, denial of impairment, and altered states of consciousness produced by drugs and alcohol, or spiritual or meditative techniques.


Time Line


13th Oct. 2013


16th Dec. 2014



11th Nov. 2015




21th Apr. 2014



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