Artificial Intelligence

1707 Submissions

[24] viXra:1707.0394 [pdf] submitted on 2017-07-30 02:17:51

The Recursive Future Equation And The Recursive Past Equation Based On The Ananda-Damayanthi Normalized Similarity Measure. {File Closing Version-2}

Authors: Ramesh Chandra Bagadi
Comments: 3 Pages.

In this research Technical Note the author have presented a Recursive Future Equation and Recursive Past Equation to find one Step Future Element or a one Step Past Element of a given Time Series data Set.
Category: Artificial Intelligence

[23] viXra:1707.0389 [pdf] submitted on 2017-07-29 07:23:01

Machine Learning and Deep Learning

Authors: George Rajna
Comments: 27 Pages.

Deep learning and machine learning both offer ways to train models and classify data. This article compares the two and it offers ways to help you decide which one to use. [15] Physicists have shown that quantum effects have the potential to significantly improve a variety of interactive learning tasks in machine learning. [14] A Chinese team of physicists have trained a quantum computer to recognise handwritten characters, the first demonstration of " quantum artificial intelligence ". Physicists have long claimed that quantum computers have the potential to dramatically outperform the most powerful conventional processors. The secret sauce at work here is the strange quantum phenomenon of superposition, where a quantum object can exist in two states at the same time. [13] One of biology's biggest mysteries-how a sliced up flatworm can regenerate into new organisms-has been solved independently by a computer. The discovery marks the first time that a computer has come up with a new scientific theory without direct human help. [12] A team of researchers working at the University of California (and one from Stony Brook University) has for the first time created a neural-network chip that was built using just memristors. In their paper published in the journal Nature, the team describes how they built their chip and what capabilities it has. [11] A team of researchers used a promising new material to build more functional memristors, bringing us closer to brain-like computing. Both academic and industrial laboratories are working to develop computers that operate more like the human brain. Instead of operating like a conventional, digital system, these new devices could potentially function more like a network of neurons. [10] Cambridge Quantum Computing Limited (CQCL) has built a new Fastest Operating System aimed at running the futuristic superfast quantum computers. [9] IBM scientists today unveiled two critical advances towards the realization of a practical quantum computer. For the first time, they showed the ability to detect and measure both kinds of quantum errors simultaneously, as well as demonstrated a new, square quantum bit circuit design that is the only physical architecture that could successfully scale to larger dimensions. [8] Physicists at the Universities of Bonn and Cambridge have succeeded in linking two completely different quantum systems to one another. In doing so, they have taken an important step forward on the way to a quantum computer. To accomplish their feat the researchers used a method that seems to function as well in the quantum world as it does for us people: teamwork. The results have now been published in the "Physical Review Letters". [7] While physicists are continually looking for ways to unify the theory of relativity, which describes large-scale phenomena, with quantum theory, which describes small-scale phenomena, computer scientists are searching for technologies to build the quantum computer. The accelerating electrons explain not only the Maxwell Equations and the Special Relativity, but the Heisenberg Uncertainty Relation, the Wave-Particle Duality and the electron's spin also, building the Bridge between the Classical and Quantum Theories. The Planck Distribution Law of the electromagnetic oscillators explains the electron/proton mass rate and the Weak and Strong Interactions by the diffraction patterns. The Weak Interaction changes the diffraction patterns by moving the electric charge from one side to the other side of the diffraction pattern, which violates the CP and Time reversal symmetry. The diffraction patterns and the locality of the self-maintaining electromagnetic potential explains also the Quantum Entanglement, giving it as a natural part of the Relativistic Quantum Theory and making possible to build the Quantum Computer.
Category: Artificial Intelligence

[22] viXra:1707.0372 [pdf] submitted on 2017-07-28 06:35:21

The Recursive Future Equation And The Recursive Past Equation Based On The Ananda-Damayanthi Normalized Similarity Measure. {Future}

Authors: Ramesh Chandra Bagadi
Comments: 2 Pages.

In this research Technical Note the author have presented a Recursive Future Equation and Recursive Past Equation to find one Step Future Element or a one Step Past Element of a given Time Series data Set.
Category: Artificial Intelligence

[21] viXra:1707.0268 [pdf] submitted on 2017-07-20 02:20:32

Finding The Optimal Number ‘K’ In The K-Means Algorithm

Authors: Ramesh Chandra Bagadi
Comments: 2 Pages.

In this research Technical Note the author has presented a novel method to find the Optimal Number ‘K’ in the K-Means Algorithm.
Category: Artificial Intelligence

[20] viXra:1707.0255 [pdf] submitted on 2017-07-19 05:05:13

Humanize Artificial Intelligent

Authors: George Rajna
Comments: 41 Pages.

Google recently launched PAIR, an acronym of People + AI Research, in an attempt to increase the utility of AI and improve human to AI interaction. [25] Now, researchers at Google's DeepMind have developed a simple algorithm to handle such reasoning—and it has already beaten humans at a complex image comprehension test. [24] A marimba-playing robot with four arms and eight sticks is writing and playing its own compositions in a lab at the Georgia Institute of Technology. The pieces are generated using artificial intelligence and deep learning. [23] Now, a team of researchers at MIT and elsewhere has developed a new approach to such computations, using light instead of electricity, which they say could vastly improve the speed and efficiency of certain deep learning computations. [22] Physicists have found that the structure of certain types of quantum learning algorithms is very similar to their classical counterparts—a finding that will help scientists further develop the quantum versions. [21] We should remain optimistic that quantum computing and AI will continue to improve our lives, but we also should continue to hold companies, organizations, and governments accountable for how our private data is used, as well as the technology's impact on the environment. [20] It's man vs machine this week as Google's artificial intelligence programme AlphaGo faces the world's top-ranked Go player in a contest expected to end in another victory for rapid advances in AI. [19] Google's computer programs are gaining a better understanding of the world, and now it wants them to handle more of the decision-making for the billions of people who use its services. [18] Microsoft on Wednesday unveiled new tools intended to democratize artificial intelligence by enabling machine smarts to be built into software from smartphone games to factory floors. [17] The closer we can get a machine translation to be on par with expert human translation, the happier lots of people struggling with translations will be. [16] Researchers have created a large, open source database to support the development of robot activities based on natural language input. [15]
Category: Artificial Intelligence

[19] viXra:1707.0254 [pdf] submitted on 2017-07-19 06:01:57

Using the Appropriate Norm In The K-Nearest Neighbours Analysis. ISSN 1751-3030

Authors: Ramesh Chandra Bagadi
Comments: 1 Page.

In this research Technical Note, the author has detailed a novel technique of finding the distance metric to be used for any given set of points.
Category: Artificial Intelligence

[18] viXra:1707.0252 [pdf] submitted on 2017-07-19 06:40:54

A Generalized Similarity Measure {File Closing Version 2} ISSN 1751-3030

Authors: Ramesh Chandra Bagadi
Comments: 2 Pages.

In this research Technical Note the author has presented a novel method of finding a Generalized Similarity Measure between two Vectors or Matrices or Higher Dimensional Data of different sizes.
Category: Artificial Intelligence

[17] viXra:1707.0230 [pdf] submitted on 2017-07-17 05:49:20

A Generalized Similarity Measure ISSN 1751-3030

Authors: Ramesh Chandra Bagadi
Comments: 2 Pages.

In this research Technical Note the author has presented a novel method of finding a Generalized Similarity Measure between two Vectors or Matrices or Higher Dimensional Data of different sizes.
Category: Artificial Intelligence

[16] viXra:1707.0225 [pdf] submitted on 2017-07-17 01:50:21

Multi Class Classification Using Holistic Non-Unique Clustering {File Closing Version 8}. ISSN 1751-3030

Authors: Ramesh Chandra Bagadi
Comments: 3 Pages.

In this research Technical Note the author has presented a novel method to find all Possible Clusters given a set of M points in N Space.
Category: Artificial Intelligence

[15] viXra:1707.0200 [pdf] submitted on 2017-07-14 04:55:42

Multi Class Classification Using Holistic Non-Unique Clustering ISSN 1751-3030

Authors: Ramesh Chandra Bagadi
Comments: 1 Page.

In this research technical Note the author have presented a novel method to find all Possible Clusters given a set of M points in N Space.
Category: Artificial Intelligence

[14] viXra:1707.0198 [pdf] submitted on 2017-07-14 05:30:10

Multi Class Classification Using Holistic Non-Unique Clustering. {File Closing Version 7} ISSN 1751-3030

Authors: Ramesh Chandra Bagadi
Comments: 1 Page.

In this research technical Note the author have presented a novel method to find all Possible Clusters given a set of M points in N Space.
Category: Artificial Intelligence

[13] viXra:1707.0179 [pdf] submitted on 2017-07-13 01:20:46

Modification To The Scaling Aspect In Gower’s Scheme Of Calculating Similarity Coefficient

Authors: Ramesh Chandra Bagadi
Comments: 1 Page.

In this research technical Note the author have presented a tiny modification to the Numeric Variables Scaling Aspect In Gower’s Scheme of calculating Similarity Coefficient.
Category: Artificial Intelligence

[12] viXra:1707.0178 [pdf] submitted on 2017-07-13 02:34:27

Recursive Future Average Of A Time Series Data Based On Cosine Similarity

Authors: Ramesh Chandra Bagadi
Comments: 2 Pages.

In this research Technical Note the author have presented a Recursive Future Average Of A Time Series Data Based on Cosine Similarity.
Category: Artificial Intelligence

[11] viXra:1707.0166 [pdf] submitted on 2017-07-12 01:12:07

Theoretical Materials

Authors: George Rajna
Comments: 49 Pages.

University have created the first general-purpose method for using machine learning to predict the properties of new metals, ceramics and other crystalline materials and to find new uses for existing materials, a discovery that could save countless hours wasted in the trial-and-error process of creating new and better materials. [28] As machine learning breakthroughs abound, researchers look to democratize benefits. [27] Machine-learning system spontaneously reproduces aspects of human neurology. [26] Surviving breast cancer changed the course of Regina Barzilay's research. The experience showed her, in stark relief, that oncologists and their patients lack tools for data-driven decision making. [25] New research, led by the University of Southampton, has demonstrated that a nanoscale device, called a memristor, could be used to power artificial systems that can mimic the human brain. [24] Scientists at Helmholtz-Zentrum Dresden-Rossendorf conducted electricity through DNA-based nanowires by placing gold-plated nanoparticles on them. In this way it could become possible to develop circuits based on genetic material. [23] Researchers at the Nanoscale Transport Physics Laboratory from the School of Physics at the University of the Witwatersrand have found a technique to improve carbon superlattices for quantum electronic device applications. [22] The researchers have found that these previously underestimated interactions can play a significant role in preventing heat dissipation in microelectronic devices. [21] LCLS works like an extraordinary strobe light: Its ultrabright X-rays take snapshots of materials with atomic resolution and capture motions as fast as a few femtoseconds, or millionths of a billionth of a second. For comparison, one femtosecond is to a second what seven minutes is to the age of the universe. [20] A 'nonlinear' effect that seemingly turns materials transparent is seen for the first time in X-rays at SLAC's LCLS. [19]
Category: Artificial Intelligence

[10] viXra:1707.0165 [pdf] submitted on 2017-07-12 01:25:24

Multi Class Classification Using Holistic Non-Unique Clustering

Authors: Ramesh Chandra Bagadi
Comments: 2 Pages.

In this research technical Note the author have presented a novel method to find all Possible Clusters given a set of M points in N Space.
Category: Artificial Intelligence

[9] viXra:1707.0145 [pdf] submitted on 2017-07-11 02:29:17

A Novel Type Of Time Series Type Forecasting

Authors: Ramesh Chandra Bagadi
Comments: 3 Pages.

In this research investigation, the author has detailed a novel Time series type of forecasting.
Category: Artificial Intelligence

[8] viXra:1707.0142 [pdf] submitted on 2017-07-11 04:48:06

A Novel Type Of Time Series Type Forecasting. {File Closing Version 1}

Authors: Ramesh Chandra Bagadi
Comments: 3 Pages.

In this research investigation, the author has detailed a novel Time series type of forecasting.
Category: Artificial Intelligence

[7] viXra:1707.0102 [pdf] submitted on 2017-07-07 01:23:03

Holistic Non-Unique Clsutering. {File Closing Version 1} ISSN 1751-3030

Authors: Ramesh Chandra Bagadi
Comments: 2 Pages.

In this research technical Note the author have presented a novel method to find all Possible Clusters given a set of points in N Space.
Category: Artificial Intelligence

[6] viXra:1707.0098 [pdf] submitted on 2017-07-07 01:44:57

Holistic Non-Unique Clsutering. {File Closing Version 2} ISSN 1751-3030

Authors: Ramesh Chandra Bagadi
Comments: 2 Pages.

In this research technical Note the author have presented a novel method to find all Possible Clusters given a set of M points in N Space.
Category: Artificial Intelligence

[5] viXra:1707.0071 [pdf] submitted on 2017-07-05 08:51:43

Seeing All The Clusters

Authors: Ramesh Chandra Bagadi
Comments: 1 Page.

In this technical note the author has presented a novel method to find all the clusters (overlapping and non-unique) formed by a given set of points.
Category: Artificial Intelligence

[4] viXra:1707.0070 [pdf] submitted on 2017-07-05 08:58:23

Seeing All Clusters Formed By A Given Set Of Points (File Closing Version) ISSN 1751-3030

Authors: Ramesh Chandra Bagadi
Comments: 1 Page.

In this research investigation, the author has presented a novel technique to find all Clusters that may be overlapping to some extent.
Category: Artificial Intelligence

[3] viXra:1707.0061 [pdf] submitted on 2017-07-05 06:54:24

Holistic Non-Unique Clsutering. ISSN 1751-3030

Authors: Ramesh Chandra Bagadi
Comments: 1 Page.

In this technical note, the author has presented a novel scheme of Holistic Non-Unique Clustering.
Category: Artificial Intelligence

[2] viXra:1707.0043 [pdf] submitted on 2017-07-03 22:47:02

Using the Appropriate Norm In The K-Nearest Neighbours Analysis

Authors: Ramesh Chandra Bagadi
Comments: 1 Page.

In this Technical Note the author has presented and alternative to the use of L2 Norm for Nearness Analysis in K-Nearest Neighbours Algorithm.
Category: Artificial Intelligence

[1] viXra:1707.0002 [pdf] submitted on 2017-07-01 04:24:01

Inner Workings of Neural Networks

Authors: George Rajna
Comments: 33 Pages.

Neural networks learn to perform computational tasks by analyzing large sets of training data. But once they've been trained, even their designers rarely have any idea what data elements they're processing. [20] Researchers from Disney Research, Pixar Animation Studios, and the University of California, Santa Barbara have developed a new technology based on artificial intelligence (AI) and deep learning that eliminates this noise and thereby enables production-quality rendering at much faster speeds. [19] Now, one group reports in ACS Nano that they have developed an artificial synapse capable of simulating a fundamental function of our nervous system— the release of inhibitory and stimulatory signals from the same "pre-synaptic" terminal. [18] Researchers from France and the University of Arkansas have created an artificial synapse capable of autonomous learning, a component of artificial intelligence. [17] Intelligent machines of the future will help restore memory, mind your children, fetch your coffee and even care for aging parents. [16] Unlike experimental neuroscientists who deal with real-life neurons, computational neuroscientists use model simulations to investigate how the brain functions. [15] A pair of physicists with ETH Zurich has developed a way to use an artificial neural network to characterize the wave function of a quantum many-body system. [14] A team of researchers at Google's DeepMind Technologies has been working on a means to increase the capabilities of computers by combining aspects of data processing and artificial intelligence and have come up with what they are calling a differentiable neural computer (DNC.) In their paper published in the journal Nature, they describe the work they are doing and where they believe it is headed. To make the work more accessible to the public team members, Alexander Graves and Greg Wayne have posted an explanatory page on the DeepMind website. [13] Nobody understands why deep neural networks are so good at solving complex problems. Now physicists say the secret is buried in the laws of physics. [12] A team of researchers working at the University of California (and one from Stony Brook University) has for the first time created a neural-network chip
Category: Artificial Intelligence