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The Theatre for the People

Catz complained to Trump during the dinner that the Pentagon's intent to award the contract to a single company made it difficult for anyone but Amazon to win the bidding process, according to Bloomberg .

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Trump has unleashed a series of attacks against Amazon on Twitter over the past few days, accusing it of "costing the United States Post Office massive amounts of money for being their Delivery Boy," not paying its fair share of taxes, and putting other companies out of business, among other criticisms.

And legislators, too, have been poking around, demanding that the Department of Defense justify awarding this contract to a single company .

But thwarting the selection of Amazon Web Services, the cloud-computing arm of Amazon, could prove difficult, even if Trump and some members of Congress wanted to.

AWS is by far the largest cloud-services provider in the US , offering the broadest range of technology services. And it already proved itself worthy of handling highly classified materials when it won a $600 million cloud contract with the CIA, which it was awarded in 2013.

Amazon Web Services claims 44% percent of the cloud market and is followed by Microsoft's Azure with 7% percent and China's Alibaba Group with 3%, according to data cited by Bloomberg from the research firm Gartner Inc.

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So, unless the Pentagon changes course and decides to use multiple cloud providers, instead of awarding the contract to a single provider, Amazon seems like a shoo-in.

That said, it is common for those who lose government bids to lodge complaints with the US Government Accountability Office, and sometimes the GOA rules in the complainer's favor. Given the battle over this contract, it would be surprising if no one protests it after it is awarded.

There has been no indication that Trump plans to interfere with the bidding process. The White House press secretary, Sarah Huckabee Sanders, reiterated on Wednesday that the president was not involved in the contest.

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NIPS 2018 Competition Track

This is the second NIPS edition on "NIPS Competitions". We received 21 competition proposals related to data-driven and live competitions on different aspects of NIPS. Proposals were reviewed by several high qualified researchers and experts in challenges organization. Eight top-scored competitions were accepted to be run and present their results during the NIPS 2018 Competition track days. Evaluation was based on the quality of data, problem interest and impact, promoting the design of new models, and a proper schedule and managing procedure. Below, you can find the eight accepted competitions. Please visit each competition webpage to read more about the competition, its schedule, and how to participate. Each competition has its own schedule defined by its organizers. The results of the competitions, including organizers and top ranked participants talks will be presented during the 2 Competition track days at NIPS 2018. Organizers and participants will be invited to submit their contribution as a book chapter to the upcoming NIPS 2018 Competition book, within Springer Series in Challenges in Machine Learning.

Eight top-scored competitions were accepted

More details below!

Competition summary: In many real-world machine learning applications, AutoML is strongly needed due to the limited machine learning expertise of developers. Moreover, batches of data in many real-world applications may be arriving daily, weekly, monthly, or yearly, for instance, and the data distributions are changing relatively slowly over time. This presents a continuous learning, or Lifelong Machine Learning challenge for an AutoML system. Typical learning problems of this kind include customer relationship management, on-line advertising, recommendation, sentiment analysis, fraud detection, spam filtering, transportation monitoring, econometrics, patient monitoring, climate monitoring, and manufacturing and so on. In this competition, which we are calling AutoML for Lifelong Machine Learning , large scale datasets collected from some of these real-world applications will be used. Compared with previous AutoML competitions( Allen EdmondsFifth Avenue PkGYUsltes
), the focus of this competition is on drifting concepts, getting away from the simpler i.i.d. cases. Participants are invited to design a computer program capable of autonomously (without any human intervention) developing predictive models that are trained and evaluated in a in lifelong machine learning setting.

Competition summary:

Organizers :

Organizers
Wei-Wei Tu, 4Paradigm Inc., China, tuww.cn@gmail.com
Hugo Jair Escalante, INAOE (Mexico), ChaLearn (USA), Me Too Adam Tucker Malena AQKaOX
Isabelle Guyon, UPSud/INRIA Univ. Paris-Saclay, France ChaLearn, USA, guyon@clopinet.com
Daniel L. Silver, Acadia University, Canada, danny.silver@acadiau.ca
Evelyne Viegas, Microsoft, USA, evelynev@microsoft.com
Yuqiang Chen, 4Paradigm Inc., China, Adrianna PapellHallie plXoTCA
Qiang Yang, 4Paradigm Inc., China, Two24 by AriatJubilee s5yc13

Webpage : https://www.4paradigm.com/competition/nips2018

There are a number of broad arguments creationists/anti-evolutionists make. Specific claims are examined at our Frye Sienna Buckle Ballet Flat XiRRD9zo5
page. They're mostly arguments born of a lack of understanding what evolution by mutation and natural selection actually is, though rarely they're advanced by more savvy creationists as direct misrepresentations and distortions of the theory of evolution.

See the main articles on this topic: Random chance and Melissa Diane Jason Wu Slide Sandal uZiRMHc

Often creationists ask how likely it is that all this complex life could have come about by random chance. They suggest that since individual events, such as the abiogenetic formation of proteins, emergence of RNA, organization of unicellular into multicellular organisms, etc., are purportedly so highly improbable that the entire chain events culminating in the existence of even a single complex organism could not have happened as described. Therefore, God did it . As creationism is largely a program of negative apologetics (e.g. an attempt to show a claim that is viewed as contrary to Christian faith is internally inconsistent or irrational according to the Christian perspective), arguments such as this are in essence Kenneth Cole New York Cara tGFFlWeR
with the proponent denying a fact (in this case the statistical probability that such and such essential event will have occurred ) in order to draw the unsupported conclusion that some other cause (the Christian God) was at work.

The implied argument that a god or "designer" was at work is itself fraught with more untenable problems. Putting aside that the illusion of design is itself problematic, and assuming for the sake of argument that "design" is even identifiable in biological systems, if "random chance" is inadequate to account for some outcome, one is simply making Steve Madden Creamer FMvxjNN4
to contend that it is more probable that a designer was at work. If the causes are "designers" about which nothing is known, if they are capable of doing anything, if it is not known how or why they act, if it is not known when they acted (or will act), or if it is not known what they did (or did not, or could, or would), the causes are not enough to account for the results. If so, "design" in this sense is indistinguishable from random chance.

Nonetheless, evolution by natural selection isn't a random process. While TOMS Alpargata Crepe Womens oE8P3
may appear randomly, the natural selection of specific traits to produce a statistically significant Schoolmates SM512 Casual Shoe Womens wJHe9n0jN
(gene variation) frequency in a discrete population of organisms is highly deterministic. If a gene aids survival with respect to any particular environmental stressor, then it is selected by means of the survival and reproduction of the individuals carrying that gene and perpetuates in the population of organisms. If the trait is detrimental to survival, it will leave organisms vulnerable to a particular environmental stressor and through attrition lower the frequency of the allele(s) contributing to that trait in the subject population.

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