Artificial Intelligence

1812 Submissions

[14] viXra:1812.0250 [pdf] submitted on 2018-12-14 11:59:51

Aspie96 at IronITA (EVALITA 2018): Irony Detection in Italian Tweets with Character-Level Convolutional RNN

Authors: Valentino Giudice
Comments: 6 Pages.

Irony is characterized by a strong contrast between what is said and what is meant: this makes its detection an important task in sentiment analysis. In recent years, neural networks have given promising results in different areas, including irony detection. In this report, I describe the system used by the Aspie96 team in the IronITA competition (part of EVALITA 2018) for irony and sarcasm detection in Italian tweets.
Category: Artificial Intelligence

[13] viXra:1812.0247 [pdf] submitted on 2018-12-15 05:30:08

Fair Computer-Aided Decisions

Authors: George Rajna
Comments: 44 Pages.

Algorithmic fairness is increasingly important because as more decisions of greater importance are made by computer programs, the potential for harm grows. [24] Intel's Gadi Singer believes his most important challenge is his latest: using artificial intelligence (AI) to reshape scientific exploration. [23] Artificial intelligence is astonishing in its potential. It will be more transformative than the PC and the Internet. Already it is poised to solve some of our biggest challenges. [22] In the search for extraterrestrial intelligence (SETI), we've often looked for signs of intelligence, technology and communication that are similar to our own. [21] Call it an a-MAZE-ing development: A U.K.-based team of researchers has developed an artificial intelligence program that can learn to take shortcuts through a labyrinth to reach its goal. In the process, the program developed structures akin to those in the human brain. [20]
Category: Artificial Intelligence

[12] viXra:1812.0185 [pdf] submitted on 2018-12-10 09:32:52

Machine Learning Design Peptides

Authors: George Rajna
Comments: 45 Pages.

Northwestern University researchers, teaming up with collaborators at Cornell University and the University of California, San Diego, have developed a new way of finding optimal peptide sequences: using a machine-learning algorithm as a collaborator. [28] A team of researchers led by Sanket Deshmukh, assistant professor of chemical engineering, has developed a method to investigate the structures of polymers that are sensitive to external stimuli. [27] In recent experiments studying analogous HYPERLINK "https://phys.org/tags/extreme+waves/" extreme waves of light, researchers have used artificial intelligence to study this problem, and have now determined a probability distribution that preferentially identifies the emergence of rogue waves. [26] Artificial intelligence's potential lies not only in its ability to help improve the educational performance of learners, but also in its capacity to foster respect and understanding between all humans. [25]
Category: Artificial Intelligence

[11] viXra:1812.0148 [pdf] submitted on 2018-12-08 23:57:26

Emotion Isn't First Principle

Authors: Miguel A. Sanchez-Rey
Comments: 7 Pages.

A winning strategy.
Category: Artificial Intelligence

[10] viXra:1812.0141 [pdf] submitted on 2018-12-07 07:58:14

AI Predict Rogue Waves of Light

Authors: George Rajna
Comments: 42 Pages.

In recent experiments studying analogous extreme waves of light, researchers have used artificial intelligence to study this problem, and have now determined a probability distribution that preferentially identifies the emergence of rogue waves. [26] Artificial intelligence's potential lies not only in its ability to help improve the educational performance of learners, but also in its capacity to foster respect and understanding between all humans. [25] The New York Times contacted IBM Research in late September asking for our help to use AI in a clever way to create art for the coming special section on AI. [24] Granting human rights to a computer would degrade human dignity. [23] IBM researchers are developing a new computer architecture, better equipped to handle increased data loads from artificial intelligence. [22] A computer built to mimic the brain's neural networks produces similar results to that of the best brain-simulation supercomputer software currently used for neural-signaling research, finds a new study published in the open-access journal Frontiers in Neuroscience. [21] The possibility of cognitive nuclear-spin processing came to Fisher in part through studies performed in the 1980s that reported a remarkable lithium isotope dependence on the behavior of mother rats. [20] And as will be presented today at the 25th annual meeting of the Cognitive Neuroscience Society (CNS), cognitive neuroscientists increasingly are using those emerging artificial networks to enhance their understanding of one of the most elusive intelligence systems, the human brain. [19] U.S. Army Research Laboratory scientists have discovered a way to leverage emerging brain-like computer architectures for an age-old number-theoretic problem known as integer factorization. [18] have come up with a novel machine learning method that enables scientists to derive insights from systems of previously intractable complexity in record time. [17]
Category: Artificial Intelligence

[9] viXra:1812.0124 [pdf] submitted on 2018-12-08 04:29:44

Machine Learning in Biomedical Field

Authors: George Rajna
Comments: 43 Pages.

A team of researchers led by Sanket Deshmukh, assistant professor of chemical engineering, has developed a method to investigate the structures of polymers that are sensitive to external stimuli. [27] In recent experiments studying analogous extreme waves of light, researchers have used artificial intelligence to study this problem, and have now determined a probability distribution that preferentially identifies the emergence of rogue waves. [26] Artificial intelligence's potential lies not only in its ability to help improve the educational performance of learners, but also in its capacity to foster respect and understanding between all humans. [25] The New York Times contacted IBM Research in late September asking for our help to use AI in a clever way to create art for the coming special section on AI. [24] Granting human rights to a computer would degrade human dignity. [23] IBM researchers are developing a new computer architecture, better equipped to handle increased data loads from artificial intelligence. [22] A computer built to mimic the brain's neural networks produces similar results to that of the best brain-simulation supercomputer software currently used for neural-signaling research, finds a new study published in the open-access journal Frontiers in Neuroscience. [21] The possibility of cognitive nuclear-spin processing came to Fisher in part through studies performed in the 1980s that reported a remarkable lithium isotope dependence on the behavior of mother rats. [20] And as will be presented today at the 25th annual meeting of the Cognitive Neuroscience Society (CNS), cognitive neuroscientists increasingly are using those emerging artificial networks to enhance their understanding of one of the most elusive intelligence systems, the human brain. [19] U.S. Army Research Laboratory scientists have discovered a way to leverage emerging brain-like computer architectures for an age-old number-theoretic problem known as integer factorization. [18]
Category: Artificial Intelligence

[8] viXra:1812.0094 [pdf] submitted on 2018-12-05 10:06:34

AI Transform Education

Authors: George Rajna
Comments: 40 Pages.

Artificial intelligence's potential lies not only in its ability to help improve the educational performance of learners, but also in its capacity to foster respect and understanding between all humans. [25] The New York Times contacted IBM Research in late September asking for our help to use AI in a clever way to create art for the coming special section on AI. [24] Granting human rights to a computer would degrade human dignity. [23] IBM researchers are developing a new computer architecture, better equipped to handle increased data loads from artificial intelligence. [22] A computer built to mimic the brain's neural networks produces similar results to that of the best brain-simulation supercomputer software currently used for neural-signaling research, finds a new study published in the open-access journal Frontiers in Neuroscience. [21]
Category: Artificial Intelligence

[7] viXra:1812.0081 [pdf] submitted on 2018-12-04 09:41:03

AI Chip Radiation at CERN

Authors: George Rajna
Comments: 44 Pages.

An ESA-led team subjected Intel's new Myriad 2 artificial intelligence chip to one of the most energetic radiation beams available on Earth. [24] Intel's Gadi Singer believes his most important challenge is his latest: using artificial intelligence (AI) to reshape scientific exploration. [23] Artificial intelligence is astonishing in its potential. It will be more transformative than the PC and the Internet. Already it is poised to solve some of our biggest challenges. [22] In the search for extraterrestrial intelligence (SETI), we've often looked for signs of intelligence, technology and communication that are similar to our own. [21] Call it an aMAZE -ing development: A U.K.-based team of researchers has developed an artificial intelligence program that can learn to take shortcuts through a labyrinth to reach its goal. In the process, the program developed structures akin to those in the human brain. [20] And as will be presented today at the 25th annual meeting of the Cognitive Neuroscience networks to enhance their understanding of one of the most elusive intelligence systems, the human brain. [19] U.S. Army Research Laboratory scientists have discovered a way to leverage emerging brain-like computer architectures for an age-old number-theoretic problem known as integer factorization. [18] have come up with a novel machine learning method that enables scientists to derive insights from systems of previously intractable complexity in record time. [17] Quantum computers can be made to utilize effects such as quantum coherence and entanglement to accelerate machine learning. [16] Neural networks learn how to carry out certain tasks by analyzing large amounts of data displayed to them. [15] Who is the better experimentalist, a human or a robot? When it comes to exploring synthetic and crystallization conditions for inorganic gigantic molecules, actively learning machines are clearly ahead, as demonstrated by British Scientists in an experiment with polyoxometalates published in the journal Angewandte Chemie. [14]
Category: Artificial Intelligence

[6] viXra:1812.0080 [pdf] submitted on 2018-12-04 10:06:16

AI-Motorized Wheelchair

Authors: George Rajna
Comments: 34 Pages.

A new wheelchair may give people with severe mobility challenges another reason to smile about artificial intelligence—that grin might literally help them control their wheelchair. [22] Now, researchers at Stanford University have devised a new type of artificially intelligent camera system that can classify images faster and more energy efficiently, and that could one day be built small enough to be embedded in the devices themselves, something that is not possible today. [21] Today, deep neural networks with different architectures, such as convolutional, recurrent and autoencoder networks, are becoming an increasingly popular area of research. [20] A deep neural network running on an ordinary desktop computer is interpreting highly technical data related to national security as well as—and sometimes better than— today's best automated methods or even human experts. [19] Scientists at the National Center for Supercomputing Applications (NCSA), located at the University of Illinois at Urbana-Champaign, have pioneered the use of GPU-accelerated deep learning for rapid detection and characterization of gravitational waves. [18] Researchers from Queen Mary University of London have developed a mathematical model for the emergence of innovations. [17] Quantum computers can be made to utilize effects such as quantum coherence and entanglement to accelerate machine learning. [16] Neural networks learn how to carry out certain tasks by analyzing large amounts of data displayed to them. [15] Who is the better experimentalist, a human or a robot? When it comes to exploring synthetic and crystallization conditions for inorganic gigantic molecules, actively learning machines are clearly ahead, as demonstrated by British Scientists in an experiment with polyoxometalates published in the journal Angewandte Chemie. [14] Machine learning algorithms are designed to improve as they encounter more data, making them a versatile technology for understanding large sets of photos such as those accessible from Google Images. Elizabeth Holm, professor of materials science and engineering at Carnegie Mellon University, is leveraging this technology to better understand the enormous number of research images accumulated in the field of materials science. [13]
Category: Artificial Intelligence

[5] viXra:1812.0079 [pdf] submitted on 2018-12-04 10:20:56

On-Demand Video Dispatch Networks: A Scalable End-to-End Learning Approach

Authors: Damao Yang, Sihan Peng, He Huang, Hongliang Xue
Comments: 11 Pages.

We design a dispatch system to improve the peak service quality of video on demand (VOD). Our system predicts the hot videos during the peak hours of the next day based on the historical requests, and dispatches to the content delivery networks (CDNs) at the previous off-peak time. In order to scale to billions of videos, we build the system with two neural networks, one for video clustering and the other for dispatch policy developing. The clustering network employs autoencoder layers and reduces the video number to a fixed value. The policy network employs fully connected layers and ranks the clustered videos with dispatch probabilities. The two networks are coupled with weight-sharing temporal layers, which analyze the video request sequences with convolutional and recurrent modules. Therefore, the clustering and dispatch tasks are trained in an end-to-end mechanism. The real-world results show that our approach achieves an average prediction accuracy of 17%, compared with 3% from the present baseline method, for the same amount of dispatches.
Category: Artificial Intelligence

[4] viXra:1812.0069 [pdf] submitted on 2018-12-05 00:04:07

Divergence Measure of Intuitionistic Fuzzy Sets

Authors: Fuyuan Xiao
Comments: 9 Pages.

As a generation of fuzzy sets, the intuitionistic fuzzy sets (IFSs) have more powerful ability to represent and deal with the uncertainty of information. The distance measure between the IFSs is still an open question. In this paper, we propose a new distance measure between the IFSs on the basis of the Jensen{ Shannon divergence. The new distance measure of IFSs not only can satisfy the axiomatic de nition of distance measure, but also can discriminate the diference between the IFSs more better. As a result, the new distance measure can generate more reasonable results.
Category: Artificial Intelligence

[3] viXra:1812.0059 [pdf] submitted on 2018-12-03 07:53:03

Dual 8-bit Breakthrough in AI

Authors: George Rajna
Comments: 43 Pages.

IBM Research launched the reduced-precision approach to AI model training and inference with a landmark paper describing a novel dataflow approach for conventional CMOS technologies to rev up hardware platforms by dramatically reducing the bit precision of data and computations. [24] Recent successful applications of deep learning include medical image analysis, speech recognition, language translation, image classification, as well as addressing more specific tasks, such as solving inverse imaging problems. [23] Researchers at Caltech have developed an artificial neural network made out of DNA that can solve a classic machine learning problem: correctly identifying handwritten numbers. [22] Researchers have devised a magnetic control system to make tiny DNA-based robots move on demand—and much faster than recently possible. [21] Humans have 46 chromosomes, and each one is capped at either end by repetitive sequences called telomeres. [20] Just like any long polymer chain, DNA tends to form knots. Using technology that allows them to stretch DNA molecules and image the behavior of these knots, MIT researchers have discovered, for the first time, the factors that determine whether a knot moves along the strand or "jams" in place. [19] Researchers at Delft University of Technology, in collaboration with colleagues at the Autonomous University of Madrid, have created an artificial DNA blueprint for the replication of DNA in a cell-like structure. [18] An LMU team now reveals the inner workings of a molecular motor made of proteins which packs and unpacks DNA. [17] Chemist Ivan Huc finds the inspiration for his work in the molecular principles that underlie biological systems. [16] What makes particles self-assemble into complex biological structures? [15]
Category: Artificial Intelligence

[2] viXra:1812.0054 [pdf] submitted on 2018-12-03 11:32:36

Universal Forecasting Scheme By Professor Ramesh Chandra Bagadi

Authors: Ramesh Chandra Bagadi
Comments: 2 Pages.

In this research investigation, the author has presented a Universal Forecasting Scheme.
Category: Artificial Intelligence

[1] viXra:1812.0053 [pdf] submitted on 2018-12-03 11:40:35

Theoretical Model For Holistic Non Unique Clustering By Professor Ramesh Chandra Bagadi

Authors: Ramesh Chandra Bagadi
Comments: 2 Pages.

In this research investigation, the author has presented the analysis of Theoretical Model For Holistic Non Unique Clustering.
Category: Artificial Intelligence