| viXra.org > Artificial Intelligence > 2001 |
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| viXra.org > Artificial Intelligence > 2001 |
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[13] viXra:2001.0426 [pdf] submitted on 2020-01-21 06:54:24
Authors: George Rajna
Comments: 44 Pages.
It may seem surprising, but theories and formulas derived from physics turn out to be useful tools for understanding the ways democratic elections work, including how these systems break down and how they could be improved. [28] Electrons whizzing around each other and humans crammed together at a political rally don't seem to have much in common, but researchers at Cornell are connecting the dots. [27] Now a group of actual physicists from Australia and Switzerland have proposed a device which uses the quantum tunneling of magnetic flux around a capacitor, breaking time-reversal symmetry. [26] The arrow of time and the accelerated expansion are two fundamental empirical facts of the universe. [25] The intensive, worldwide search for dark matter, the missing mass in the universe, has so far failed to find an abundance of dark, massive stars or scads of strange new weakly interacting particles, but a new candidate is slowly gaining followers and observational support. [24] "We invoke a different theory, the self-interacting dark matter model or SIDM, to show that dark matter self-interactions thermalize the inner halo, which ties ordinary dark matter and dark matter distributions together so that they behave like a collective unit." [23] Technology proposed 30 years ago to search for dark matter is finally seeing the light. [22] They're looking for dark matter-the stuff that theoretically makes up a quarter of our universe. [21] Results from its first run indicate that XENON1T is the most sensitive dark matter detector on Earth. [20]
Category: Artificial Intelligence
[12] viXra:2001.0366 [pdf] submitted on 2020-01-19 04:46:28
Authors: George Rajna
Comments: 46 Pages.
A team of researchers affiliated with several institutions in China and two in the U.S. has developed a way to use machine learning to get a better look at the past. In their paper published in the journal Science, the group describes how they used machine learning to analyze records of the past. [28] Bioinformatics researchers at Heinrich Heine University Düsseldorf (HHU) and the University of California at San Diego (UCSD) are using machine learning techniques to better understand enzyme kinetics and thus also complex metabolic processes. [27] DNA regions susceptible to breakage and loss are genetic hot spots for important evolutionary changes, according to a Stanford study. [26] For the English scientists involved, perhaps the most important fact is that their DNA read was about twice as long as the previous record, held by their Australian rivals. [25] Researchers from the University of Chicago have developed a high-throughput RNA sequencing strategy to study the activity of the gut microbiome. [24] Today a large international consortium of researchers published a complex but important study looking at how DNA works in animals. [23] Asymmetry plays a major role in biology at every scale: think of DNA spirals, the fact that the human heart is positioned on the left, our preference to use our left or right hand ... [22] Scientists reveal how a 'molecular machine' in bacterial cells prevents fatal DNA twisting, which could be crucial in the development of new antibiotic treatments. [21] In new research, Hao Yan of Arizona State University and his colleagues describe an innovative DNA HYPERLINK "https://phys.org/tags/walker/" walker, capable of rapidly traversing a prepared track. [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]
Category: Artificial Intelligence
[11] viXra:2001.0318 [pdf] submitted on 2020-01-16 10:59:06
Authors: George Rajna
Comments: 48 Pages.
Researchers have harnessed the power of a type of artificial intelligence known as deep learning to create a new laser-based system that can image around corners in real time. [28] A team of scientists at Freie Universität Berlin has developed an Artificial Intelligence (AI) method that provides a fundamentally new solution of the "sampling problem" in statistical physics. [27] Deep learning, which uses multi-layered artificial neural networks, is a form of machine learning that has demonstrated significant advances in many fields, including natural language processing, image/video labeling and captioning. [26]
Category: Artificial Intelligence
[10] viXra:2001.0218 [pdf] replaced on 2020-01-17 01:21:27
Authors: Nirmal Tej Kumar
Comments: 5 Pages. Short Communication - Revised
[ PART A ] - Python
Medical Image Processing & Electron Microscopy Image Processing Informatics Using Python/LLVM.
[ PART B ] - Haskell
Exploring a JIT Compiler with Haskell and LLVM in the Context of Medical Image Processing & Electron Microscopy Image Processing Software R&D
Using Mandelbrot Algorithms.
Category: Artificial Intelligence
[9] viXra:2001.0196 [pdf] submitted on 2020-01-11 02:16:36
Authors: George Rajna
Comments: 40 Pages.
Now, Purdue University researchers have designed a novel approach to use deep learning to better understand how proteins interact in the body—paving the way to producing accurate structure models of protein interactions involved in various diseases and to design better drugs that specifically target protein interactions. [26]
Researchers, from biochemists to material scientists, have long relied on the rich variety of organic molecules to solve pressing challenges. [25]
Social, economic, environmental and health inequalities within cities can be detected using street imagery. [24]
Category: Artificial Intelligence
[8] viXra:2001.0192 [pdf] submitted on 2020-01-11 04:57:31
Authors: George Rajna
Comments: 51 Pages.
Analog machine learning hardware offers a promising alternative to digital counterparts as a more energy efficient and faster platform. Wave physics based on acoustics and optics is a natural candidate to build analog processors for time-varying signals. [29] Recent advances in optical neural networks, however, are closing that gap by simulating the way neurons respond in the human brain. [28] An international team of scientists from Eindhoven University of Technology, University of Texas at Austin, and University of Derby, has developed a revolutionary method that quadratically accelerates artificial intelligence (AI) training algorithms. [27] Predictions for an AI-dominated future are increasingly common, but Antoine Blondeau has experience in reading, and arguably manipulating, the runes-he helped develop technology that evolved into predictive texting and Apple's Siri. [26] Artificial intelligence can improve health care by analyzing data from apps, smartphones and wearable technology. [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]
Category: Artificial Intelligence
[7] viXra:2001.0119 [pdf] submitted on 2020-01-08 08:36:17
Authors: George Rajna
Comments: 49 Pages.
The neural network subsequently identified the relevant parameters as the ones required to calculate the position of Mars on the basis of the heliocentric worldview. [29]
A team of researchers from the University of Münster, the University of Oxford and the University of Exeter has built an all-optical neural network on a single chip. [28]
Physicists from Petrozavodsk State University have proposed a new method for oscillatory neural network to recognize simple images. Such networks with an adjustable synchronous state of individual neurons have, presumably, dynamics similar to neurons in the living brain. [27]
Category: Artificial Intelligence
[6] viXra:2001.0106 [pdf] submitted on 2020-01-07 02:09:22
Authors: Abhinav Mathur, Sunny Verma
Comments: 7 Pages.
Good generalized machine learning models should have high variability post learning 1. Tree-based approaches2 are very popular due to their inherent ability in being visually representable for decision consumption as well as robustness and reduced training times. However, tree-based approaches lack the ability to generate variations in regression problems. The maximum variation generated by any single tree-based model is limited to the maximum number of training observations considering each observation to be a terminal node itself. Such a condition is an overfit model. This paper discusses the use of a hybrid approach of using two intuitive and explainable algorithms, CART2 and k-NN3 regression to improve the generalizations and sometimes the runtime for regression-based problems. The paper proposes first, the use of using a shallow CART algorithm (Tree depth lesser than optimal depth post pruning). Following the initial CART, a KNN Regression is performed at the terminal node to which the observation for prediction generation belongs to. This leads to a better variation as well as more accurate prediction than by just the use of a CART or a KNN regressor as well as another level of depth over an OLS regression1.
Category: Artificial Intelligence
[5] viXra:2001.0065 [pdf] submitted on 2020-01-05 05:13:08
Authors: Jeff Linahan
Comments: 8 Pages. originally written in 2015, code is available at https://github.com/jeffythedragonslayer/maglisp
Magic: The Gathering is the world's most popular trading card game. So far, attempts to program its 210-page rulebook in order to create an AI for the game have resulted in systems that are very complex, and still not able to compete with humans. I believe one of the main causes of this is the choice of programming language. Most implementations are done in languages which emphasize execution speed or portability rather than development speed or flexibility. Common Lisp was classically the lingua franca for AI research, and its following features mesh well with the challenges of programming Magic: a read-eval-print loop, macros, dynamic typing, scripting, multiple inheritance, and symbolic computation. In this project I present a proof of concept implementation consisting of a command line interface for two humans playing Magic with two hardcoded decks. I will discuss what I have learned from tackling the challenges of the project and how I would proceed if I had years to complete it.
Category: Artificial Intelligence
[4] viXra:2001.0040 [pdf] submitted on 2020-01-04 09:21:59
Authors: Ranjan Akarsh
Comments: 9 Pages. Kindly reach out to me for any queries. I'd be happy comply.
This paper depicts a network called LeGuess (LeG) which, using
computer vision, is able to precisely predict the future scenes given
sequence of images. The network is able to automatically learn the
features and representations of the objects present in the sequence of
images fed as input. Furthermore, this network learns the movements of
the objects and predicts very well.
The network is mainly designed for the domain of Autonomous Vehicles,
which contains plenty of applications alone. Taking this in note, LeG can
be applied to predict the steering angles, predicting the future positions of
cars, trucks, cyclists, etc., ready a generative model to generate images
along with steering angles, which could be used to train vehicles to drive,
as well as generate images of road with/without lane to train segmentation
for better autonomous driving.
The network is designed to make predictions (local) of up to given number
of time-steps ahead.
Category: Artificial Intelligence
[3] viXra:2001.0027 [pdf] submitted on 2020-01-03 06:13:06
Authors: George Rajna
Comments: 45 Pages.
This question is important for optimizing the properties of the carbon material in real-world applications, and researchers at CSIRO in Australia have now tried to answer it using machine learning. [27] Reporting their findings in the open-access journal npj Computational Materials, the researchers show that their ML method, involving "transfer learning," enables the discovery of materials with desired properties even from an exceeding small data set. [26] The analysis of sensor data of machines, plants or buildings makes it possible to detect anomalous states early and thus to avoid further damage. [25] Physicists in the US have used machine learning to determine the phase diagram of a system of 12 idealized quantum particles to a higher precision than ever before. [24] The research group took advantage of a system at SLAC's Stanford Synchrotron Radiation Lightsource (SSRL) that combines machine learning-a form of artificial intelligence where computer algorithms glean knowledge from enormous amounts of data-with experiments that quickly make and screen hundreds of sample materials at a time. [23] Researchers at the UCLA Samueli School of Engineering have demonstrated that deep learning, a powerful form of artificial intelligence, can discern and enhance microscopic details in photos taken by smartphones. [22] Such are the big questions behind one of the new projects underway at the MIT-IBM Watson AI Laboratory, a collaboration for research on the frontiers of artificial intelligence. [21]
Category: Artificial Intelligence
[2] viXra:2001.0015 [pdf] submitted on 2020-01-02 02:15:05
Authors: Nirmal Tej Kumar
Comments: 3 Pages. Short Communication & Technical Notes
Scala based Image Processing Using Gröbner Bases/Wavelets/Deep Learning - An Insight & Short Technical Notes.
[ Glimpsing into the Future of AI + Interesting Applications ]
Category: Artificial Intelligence
[1] viXra:2001.0012 [pdf] submitted on 2020-01-02 06:29:34
Authors: Dimiter Dobrev
Comments: 10 Pages. short summary in Bulgarian
The program Artificial Intelligence has to be able to understand the world. To do this, it has to build a model of the world. The language (format) in which this model will be described is very important. Could this format be Turing Machine or Markov decision process? Yes, it can, but only if we have an infinitely fast computer and an infinitely long training time. Can we offer a description format in which the world description is simple enough to be found automatically. Yes, Event-Driven models are such a format. We will demonstrate how the rules of the game of chess can be described by Event-Driven models and the resulting description will be simple enough.
Category: Artificial Intelligence
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