scholarly journals Human-Brain Artificial-Intelligence Matrix

2020 ◽  
Author(s):  
John Ibrahim
Keyword(s):  
Artificial Intelligence ◽  
Action Potential ◽  
Human Brain ◽  
New Technology ◽  
Quantum Mechanical ◽  
Dual Nature ◽  
Potential Wells ◽  
Whole Process ◽  
The Brain ◽  
A Current

Human-Brain Artificial-Intelligence Matrix is a new technology aims to connect the human brain with the machine for the purpose of enabling the human brain to perform defined functions even if it becomes unable to perform them such as performing the function of vision in case of blindness, the function of hearing in case of deafness, Performing the function of motion in case of paralysis and many other functions. This technology will be based on the Cognition Theory which I argue about that the whole process of cognition can be treated quantum-mechanically. The cognition starts when a neuron sends data to be processed in the brain and ends in an effector to respond. The data “action potential” is a current of particles which can be described quantum-mechanically as a wave-impulse based on the dual nature of the particles. The neurons are a net of entangled cells classically and quantum-mechanically. When the action potential changes the potential of the neurons, it creates quantum mechanical potential wells and barriers. The action potential perfectly transmits in and out the neurons through quantum mechanical tunnels. The form of energy before processing is not the same after, but the amount of energy is always conserved. Since the neurons are entangled during the action potential transmission, the brain and effector will be entangled during the action potential processing. The effector’s cognition of data must be a discrete cognition of single-valued data from its self-adjoint matrix which entangled with brain matrix.

scholarly journals Computers That Look Like the Brain

2020 ◽  
Vol 8 ◽  
Author(s):  
Shahar Kvatinsky
Keyword(s):  
Artificial Intelligence ◽  
Human Brain ◽  
The Past ◽  
Computer Structure ◽  
The Brain ◽  
The Way

Artificial intelligence applications have been developing rapidly over the past few years, allowing computers to perform complex actions, such as driving without a driver, making decisions, and recognizing faces. These applications require that many calculations be performed in parallel and immense amounts of information are needed. This article demonstrates how inefficient today’s computer structure is for performing artificial intelligence applications. To deal with this challenge and improve artificial intelligence applications, we will see how inspiration from the way the human brain works will allow us to build completely new computers, which will rock the way computers have been built for many years.

scholarly journals Multilayered model of speech

2018 ◽  
Author(s):  
Andrey Chistyakov
Keyword(s):  
Artificial Intelligence ◽  
Human Brain ◽  
Modern Science ◽  
Human Speech ◽  
Brain Simulation ◽  
The Brain

Human speech is the most important part of General Artificial Intelligence and subject of much research. The hypothesis proposed in this article provides explanation of difficulties that modern science tackles in the field of human brain simulation. The hypothesis is based on the author’s conviction that the brain of any given person has different ability to process and store information. Therefore, the approaches that are currently used to create General Artificial Intelligence have to be altered.

scholarly journals Enclosing Machine Learning

2011 ◽  
pp. 744-751
Author(s):  
Xunkai Wei
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Human Brain ◽  
Statistical Learning ◽  
Neural Computing ◽  
Working Mechanism ◽  
Feature Information ◽  
Active Research ◽  
Intelligent Information ◽  
The Brain

As known to us, the cognition process is the instinct learning ability of the human being. This process is perhaps one of the most complex human behaviors. It is a highly efficient and intelligent information processing process. For a cognition process of the natural world, humans always transfer the feature information to the brain through their perception, and then the brain processes the feature information and remembers it. Due to the invention of computers, scientists are now working toward improving its artificial intelligence, and they hope that one day the computer could have its intelligent “brain” as human does. However, it is still a long way for us to go in order to let a computer truly “think” by itself. Currently, artificial intelligence is an important and active research topic. It imitates the human brain using the idea of function equivalence. Traditionally, the neural computing and neural networks families are the majority parts of the direction (Haykin, 1994). By imitating the working mechanism of the human-brain neuron, scientists have built the neural networks theory following experimental research such as perception neurons and spiking neurons (Gerstner & Kistler, 2002) in order to understand the working mechanism of neurons. Neural-computing and neural networks (NN) families (Bishop, 1995) have made great achievements in various aspects. Recently, statistical learning and support vector machines (SVM) (Vapnik, 1995) have drawn extensive attention and shown better performances in various areas (Li, Wei & Liu, 2004) than NN, which implies that artificial intelligence can also be made via advanced statistical computing theory. Nowadays, these two methods tend to merge under the statistical learning theory framework

scholarly journals Connections

2020 ◽  
Vol 2 (3(September-December)) ◽  
pp. e642020
Author(s):  
Ricardo Santos De Oliveira
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Neural Networks ◽  
Nervous System ◽  
Human Brain ◽  
Nerve Cells ◽  
Seer Database ◽  
Biological Neural Network ◽  
Artificial Neural ◽  
The Brain

The human brain contains around 86 billion nerve cells and about as many glial cells [1]. In addition, there are about 100 trillion connections between the nerve cells alone. While mapping all the connections of a human brain remains out of reach, scientists have started to address the problem on a smaller scale. The term artificial neural networks (ANNs or simply neural networks (NNs), encompassing a family of nonlinear computational methods that, at least in the early stage of their development, were inspired by the functioning of the human brain. Indeed, the first ANNs were nothing more than integrated circuits devised to reproduce and understand the transmission of nerve stimuli and signals in the human central nervous system [2]. The correct way of doing it is to the first study human behavior. The human brain has a biological neural network that has billions of interconnections. As the brain learns, these connections are either formed, changed or removed, similar to how an artificial neural network adjusts its weights to account for a new training example. This complexity is the reason why it is said that practice makes one perfect since a greater number of learning instances allow the biological neural network to become better at whatever it is doing. Depending upon the stimulus, only a certain subset of neurons are activated in the nervous system. Recently, Moreau et al., [3] published an interesting paper studying how artificial intelligence can help doctors and patients with meningiomas make better treatment decisions, according to a new study. They demonstrated that their models were capable of predicting meaningful individual-specific clinical outcome variables and show good generalizability across the Surveillance, Epidemiology, and End Results (SEER) database to predict meningioma malignancy and survival after specific treatments. Statistical learning models were trained and validated on 62,844 patients from the SEER database and a model scoring for the malignancy model was performed using a series of metrics. A free smartphone and web application were also provided for readers to access and test the predictive models (www.meningioma.app). The use of artificial intelligence techniques is gradually bringing efficient theoretical solutions to a large number of real-world clinical problems related to the brain (4). Specifically, recently, thanks to the accumulation of relevant data and the development of increasingly effective algorithms, it has been possible to significantly increase the understanding of complex brain mechanisms. The researchers' efforts are creating increasingly sophisticated and interpretable algorithms, which could favor a more intensive use of “intelligent” technologies in practical clinical contexts. Brain and machine working together will improve the power of these methods to make individual-patient predictions could lead to improved diagnosis, patient counseling, and outcomes.

scholarly journals Human Brain Disorders: A Review

2020 ◽  
Vol 8 (1) ◽  
pp. 6-21
Author(s):  
Falaq Naz ◽  
Yasir Hasan Siddique
Keyword(s):  
Human Brain ◽  
Brain Structure ◽  
New Technology ◽  
Treatment Strategies ◽  
Brain Diseases ◽  
Brain Disorders ◽  
Ancient Greek ◽  
The Subject ◽  
The Brain ◽  
Structure And Functions

Background: Due to the stressful life, brain disorders are considered as a significant global healthcare problem. It has generated a great need for continuous research for understanding brain structure as well as functions in context to health and diseases. Scope and Approach: The structure and functions of the brain were questioned and studied since Ancient Greek times and led to the compilation of enormous information on the subject globally. With the advent of new technology, the researchers are able to discover the causes of brain diseases/disorders. Conclusion: In the present review, we have compiled various diseases and disorders related to the brain, along with their symptoms and the treatment strategies.

scholarly journals Multilayered model of speech

2018 ◽  
Author(s):  
Andrey Chistyakov
Keyword(s):  
Artificial Intelligence ◽  
Human Brain ◽  
Modern Science ◽  
Human Speech ◽  
Brain Simulation ◽  
The Brain

Human speech is the most important part of General Artificial Intelligence and subject of much research. The hypothesis proposed in this article provides explanation of difficulties that modern science tackles in the field of human brain simulation. The hypothesis is based on the author’s conviction that the brain of any given person has different ability to process and store information. Therefore, the approaches that are currently used to create General Artificial Intelligence have to be altered.

Frontier concept of rabi chip for intelligent humanoid

2018 ◽  
Vol 1 (2) ◽  
Author(s):  
Preecha Yupapin ◽  
Amiri I. S. ◽  
Ali J. ◽  
Ponsuwancharoen N. ◽  
Youplao P.
Keyword(s):  
Human Brain ◽  
Brain Function ◽  
Rabi Oscillation ◽  
Liquid Core ◽  
Brain Surface ◽  
Dipole Oscillation ◽  
On Chip ◽  
The Brain ◽  
Robotic Applications ◽  
Atom System

The sequence of the human brain can be configured by the originated strongly coupling fields to a pair of the ionic substances(bio-cells) within the microtubules. From which the dipole oscillation begins and transports by the strong trapped force, which is known as a tweezer. The tweezers are the trapped polaritons, which are the electrical charges with information. They will be collected on the brain surface and transport via the liquid core guide wave, which is the mixture of blood content and water. The oscillation frequency is called the Rabi frequency, is formed by the two-level atom system. Our aim will manipulate the Rabi oscillation by an on-chip device, where the quantum outputs may help to form the realistic human brain function for humanoid robotic applications.

TIMELESS BUILDINGS AND THE HUMAN BRAIN: The Effect of Spiritual Spaces on Human Brain Waves

2014 ◽  
Vol 8 (1) ◽  
pp. 133
Author(s):  
Sally M. Essawy ◽  
Basil Kamel ◽  
Mohamed S. Elsawy
Keyword(s):  
Human Brain ◽  
Case Studies ◽  
Spiritual Experience ◽  
Brain Wave ◽  
Human Comfort ◽  
Beliefs And Practices ◽  
Brain Waves ◽  
Space Design ◽  
State Of Mind ◽  
The Brain

Some buildings hold certain qualities of space design similar to those originated from nature in harmony with its surroundings. These buildings, mostly associated with religious beliefs and practices, allow for human comfort and a unique state of mind. This paper aims to verify such effect on the human brain. It concentrates on measuring brain waves when the user is located in several spots (coordinates) in some of these buildings. Several experiments are conducted on selected case studies to identify whether certain buildings affect the brain wave frequencies of their users or not. These are measured in terms of Brain Wave Frequency Charts through EEG Device. The changes identified on the brain were then translated into a brain diagram that reflects the spiritual experience all through the trip inside the selected buildings. This could then be used in architecture to enhance such unique quality.

Art and the Brain’s Reward System

2018 ◽  
Author(s):  
Henrik Hogh-Olesen
Keyword(s):  
Human Brain ◽  
Reward System ◽  
Human Existence ◽  
Brain Scans ◽  
System P ◽  
The Aesthetic ◽  
The Brain ◽  
Reward Circuit

Chapter 7 takes the investigation of the aesthetic impulse into the human brain to understand, first, why only we—and not our closest relatives among the primates—express ourselves aesthetically; and second, how the brain reacts when presented with aesthetic material. Brain scans are less useful when you are interested in the Why of aesthetic behavior rather than the How. Nevertheless, some brain studies have been ground-breaking, and neuroaesthetics offers a pivotal argument for the key function of the aesthetic impulse in human lives; it shows us that the brain’s reward circuit is activated when we are presented with aesthetic objects and stimuli. For why reward a perception or an activity that is evolutionarily useless and worthless in relation to human existence?

scholarly journals Is There a Brain Microbiome?

2021 ◽  
Vol 16 ◽  
pp. 263310552110187
Author(s):  
Christopher D Link
Keyword(s):  
Animal Models ◽  
Human Brain ◽  
Neurodegenerative Diseases ◽  
Ground Truth ◽  
Healthy Human ◽  
Strong Motivation ◽  
The Many ◽  
The Brain

Numerous studies have identified microbial sequences or epitopes in pathological and non-pathological human brain samples. It has not been resolved if these observations are artifactual, or truly represent population of the brain by microbes. Given the tempting speculation that resident microbes could play a role in the many neuropsychiatric and neurodegenerative diseases that currently lack clear etiologies, there is a strong motivation to determine the “ground truth” of microbial existence in living brains. Here I argue that the evidence for the presence of microbes in diseased brains is quite strong, but a compelling demonstration of resident microbes in the healthy human brain remains to be done. Dedicated animal models studies may be required to determine if there is indeed a “brain microbiome.”

Sign in / Sign up

Export Citation Format

Share Document