Machine learning 'causing science crisis'


Machine-learning techniques used by thousands of scientists to analyse data are producing results that are misleading and often completely wrong. Dr Genevera Allen from Rice University in Houston said that the increased use of such systems was contributing to a "crisis in science". She warned scientists that if they didn't improve their techniques they would be wasting both time and money. Her research was presented at the American Association for the Advancement of Science in Washington. A growing amount of scientific research involves using machine learning software to analyse data that has already been collected.

Rebuilding a Smarter City: Lessons from Houston


Smart Cities are the future. So when Houston, Texas faced rebuilding in the aftermath of Hurricane Harvey in 2017, it seized the opportunity to transform itself as a tech-centric, smart city by incorporating emerging technologies including Artificial Intelligence, IoT, Machine Learning and data analytics. Houston is being extremely planful in building multiple innovative solutions across departments at the same time that communicate with one another which is significantly increasing the positive impact it's bringing to its citizens. As a result, Houston has come to serve as a model for Smart City initiatives. We will hear from those responsible for Houston's transformation and examine what others - from policymakers to city officials to business leaders - can learn from their experience.

Looking for a Job? Meet Your Machine Learning Interviewer JPMorgan Chase & Co.


This article was originally published by Ozy. In 2016, Houston's petrochemical industry had countless job positions that were unfilled. And at the same time, a number of the city's residents were looking for work. So, how was Houston going to fix this? In an effort to help match eligible candidates with open positions, private companies began to step in.

How an Anonymous 4chan Post Helped Solve a 25-Year-Old Math Puzzle


In September 16, 2011, an anime fan posted a math question to the online bulletin board 4chan about the cult classic television series The Melancholy of Haruhi Suzumiya. Season one of the show, which involves time travel, had originally aired in nonchronological order, and a re-broadcast and a DVD version had each further rearranged the episodes. Fans were arguing online about the best order to watch the episodes, and the 4chan poster wondered: If viewers wanted to see the series in every possible order, what is the shortest list of episodes they'd have to watch? Original story reprinted with permission from Quanta Magazine, an editorially independent publication of the Simons Foundation whose mission is to enhance public understanding of science by covering research developments and trends in mathematics and the physical and life sciences. In less than an hour, an anonymous person offered an answer -- not a complete solution, but a lower bound on the number of episodes required.

New algorithm can more quickly predict LED materials


Researchers from the University of Houston have devised a new machine learning algorithm that is efficient enough to run on a personal computer and predict the properties of more than 100,000 compounds in search of those most likely to be efficient phosphors for LED lighting. Jakoah Brgoch, assistant professor of chemistry, and members of his lab describe the work a paper published Oct. 22 in Nature Communications. The researchers used machine learning to quickly scan huge numbers of compounds for key attributes, including Debye temperature and chemical compatibility. Brgoch previously demonstrated that Debye temperature is correlated with efficiency. LED, or light-emitting diode, based bulbs work by using small amounts of rare earth elements, usually europium or cerium, substituted within a ceramic or oxide host--the interaction between the two materials determines the performance.

Looks like the first U.S. robot brothel isn't happening ... yet


The U.S. won't get its very first "robot brothel" after all. The Houston City Council amended an ordinance to prevent a company called KinkySdollS from opening a showroom where people could have, um, intimate relations with realistic sex dolls. The dolls sell for anywhere from $2,500 to $10,000, with optional "body heat" and AI voice options. The amendment -- which doesn't make it illegal to sell the dolls, only to "test" them (oh god why) at the showroom -- was passed unanimously Wednesday by city council members, including Greg Travis, who, reports the AP, called the brothel "weird" and "gross." Regular Houston citizens also spoke out against the business.

Houston City Council short circuits proposed robot brothel

Daily Mail

A company's plan to open a so-called sex robot brothel in Houston has been short circuited by city leaders. Houston's City Council on Wednesday updated one local ordinance to specifically ban individuals from having sex with an'anthropomorphic device,' a device that resembles a human being, at a sexually-oriented business. The company, Canada-based KinkySdollS, had wanted to open a'love dolls brothel' in Houston in which people would be able to use its human-like dolls - a concept that that has drawn comparisons to the science fiction series'Westworld.' KinkySdollS says its human-like dolls (above), which can speak and feel warm to the touch, are available for sale or rent. It would have been the company's second location. The first location opened in 2017 in Toronto.

Houston officials temporarily prevent robot brothel from opening


A robot brothel expected to open in Houston this month has been temporarily stymied by building inspectors, according to local media. The temporary halt comes after a spirited wave of opposition following a social media announcement by Canadian company KinkySDollS that the company was planning to import its robot brothel concept to Houston. The store would be KinkySDollS' second location. The company currently operates a showroom in Toronto where customers can buy lifelike talking robot sex dolls. The dolls are also available for on-site rental by the hour or half-hour.

Why use Machine Learning in DevOps?


Machine Learning (ML): is an application of Artificial Intelligence which allows systems to learn and improve from experience, rather than being manually programmed for each instance. DevOps: is a software engineering practice that aims to unify software development and software operation. Whilst DevOps has improved software development exponentially, from increasing both qualities to productivity, there are still limitations. The relationship between ML and DevOps is evident, and it is capable of enhancing organisations' ability to manipulate and analyse large amounts of data far more accurately and rapidly than a human engineer. ML is able to handle the volume, amount and variety of data through its agile capabilities to learn from and process data far quicker and more accurately than its human counterparts.

Houston's 'robot sex brothel' faces city hurdle: report

FOX News

Canadian company KinySdollS says the Houston showroom is set to be the first in the U.S. to rent or sell its real-life looking sex robots. The Canadian company looking to open a so-called "robot sex brothel" in Houston reportedly hit a snag during its construction. The Houston Chronicle reported Sunday that city workers noticed that builders did not have certain permits and ordered the project to stop work. Mayor Sylvester Turner said he's not trying to be the "moral police" but this is not the type of business he wants opening in the city. A spokesperson from his office said KinkySDollS must "apply for a demolition permit and submit plans."