Bitcoin Starts Corrective Decrease But Bulls Not Out Of Woods Yet – newsBTC

Bitcoin price started a downside correction after rallying to a new 2020 high near $8,460 against the US Dollar. BTC corrected $500, but the price is still above many key supports.

This week, we saw a strong rise in bitcoin price above the $8,000 resistance against the US Dollar. BTC traded to a new 2020 high near $8,460 before it started a downside correction.

The bears were able to push the price below the $8,300 and $8,200 levels. During the decline, there was a break below a key bullish trend line with support near $8,040 on the hourly chart.

Besides, the price failed to stay above the $8,000 support area. Finally, it traded as low as $7,867 and is currently consolidating in a range. On the upside, there are initial hurdles near $8,000, and the 23.6% Fib retracement level of the recent decline from the $8,426 high to $7,867 low.

The first key resistance for bitcoin is near the $8,145 level. It represents the 50% Fib retracement level of the recent decline from the $8,426 high to $7,867 low.

If there is a clear break above the $8,145 and $8,200 levels, the price is likely to resume its upward move. The next major resistance is at $8,280, above which the bulls are likely to aim a new 2020 high.

On the downside, there are a couple of key supports for bitcoin near the $7,800 level. More importantly, the 100 hourly simple moving average is near $7,800.

Therefore, a successful bearish close below $7,800 might invalidate the current bullish view. In the mentioned case, the price is likely to revisit the $7,500 support.

Looking at the chart, bitcoin price is clearly under stress below the $8,000 and $8,100 levels. In the short term, there could be a downside extension, but the price is likely to bounce back as long as it is above $7,800.

Technical indicators:

Hourly MACD The MACD is slowly reducing its bearish slope.

Hourly RSI (Relative Strength Index) The RSI for BTC/USD is currently well below the 50 level.

Major Support Levels $7,860 followed by $7,800.

Major Resistance Levels $8,000, $8,145 and $8,200.

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Bitcoin Starts Corrective Decrease But Bulls Not Out Of Woods Yet - newsBTC

Bitcoin Daily Chart Indicates It Is Going Parabolic To $9K and $10K – newsBTC

Bitcoin broke a couple of important hurdles near $7,500 and $8,000 on the daily chart against the US Dollar. BTC price action indicates a strong rise towards $9,100 or even $10,000.

Recently, there were bullish moves in bitcoin above the $7,500 resistance area against the US Dollar. More importantly, there were a couple of key bullish breaks on the daily chart.

The daily chart suggests that the price formed a strong support base near $6,560 before starting the current rally. There was a clear break above a major bearish trend line with resistance near $7,630.

As a result, bitcoin climbed above the $8,000 resistance and settled above the 100-day simple moving average. The recent rise was stalled near the 50% Fib retracement level of the downward move from the $10,564 high to $6,449 low.

However, the current price action, bullish breaks above the trend line and the 100-day SMA indicate that the bulls are aligning for the next rally above the $8,500 resistance.

The next major resistance is near the $9,000 and $9,100 levels. The 61.8% Fib retracement level of the downward move from the $10,564 high to $6,449 low is also near the $9,000 level.

If the price continues to gain momentum above $9,100, there are chances of a run towards the $10,000 resistance area.

In the short term, there could be a couple of downside corrections. In the mentioned case, an initial support is near the $8,300 level.

The main support is near the $8,000 level or the 100-day SMA, which was the recent breakout zone. Any further losses may perhaps lead the price towards the $7,500 support area in the near term.

Bitcoin Price

Looking at the chart, bitcoin price is showing a lot of positive signs above the $8,000 support and the 100-day SMA. As long as there is no daily close below the 100 SMA, there are chances of a strong rise towards the $10,000 resistance.

Technical indicators:

Daily MACD The MACD is slowly gaining pace in the bullish zone.

Daily RSI (Relative Strength Index) The RSI for BTC/USD is now well above the 50 level.

Major Support Levels $8,300 followed by $8,000.

Major Resistance Levels $8,500, $9,000 and $9,100.

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Bitcoin Daily Chart Indicates It Is Going Parabolic To $9K and $10K - newsBTC

Obama and Trump: The Present as Prologue to a History of Inequality – laprogressive.com

In 2011, I began writing The Disinformation Age: The Collapse of Liberal Democracy in the United States, which was published by Routledge in 2017, just after the Trump administration succeeded that of Obama, and now appears in this PaperBoat Press edition. The book is an historical view going back to the 17th century of how we got to Trump, whom we should not forget we, the people elected. So, to start with, lets agree that Trump is not the problem, not the cause of what I understand as our currently collapsed democracy, but a particularly virulent symptom of its collapse.

The rise of Trump has produced some strong nostalgia for his predecessor, Barack Obama. But we should remember that Obama and those before him, going most immediately back to the presidency of Ronald Reagan, set the table for Trumps gluttony. In The Disinformation Age I go back much farther to suggest a reason for the collapse of U.S. democracy from the Constitution forward, but for now, because in the mainstream press the contrast between Obama and Trump appears as stark as that between antagonists in a medieval morality play, representing the two poles of U.S. democracy, I want to look only at the two to suggest the ways the contrast blurs on close inspection. This is a result not of any similarities between the two menthey couldnt be more different in style and temperamentbut of what they represent: neoliberal capitalism.

The rise of Trump has produced some strong nostalgia for his predecessor, Barack Obama. But we should remember that Obama and those before him, going most immediately back to the presidency of Ronald Reagan, set the table for Trumps gluttony.

Obamas economic advisers Larry Summers, Timothy Geithner, Robert Rubin and company were the very same people who engineered the Great Recession of 2008. After the Recession, with their advice, Obama invested largely in the big banks (Rubin and Geithner were two of the biggest bankers) that caused the economic collapse, not, by and large, in the millions of people who lost their homes and jobs because of it. Income inequality increased during the Obama administration as it continues to do under Trump, whose tax policy siphons tax dollars to the rich and corporationsnot that they werent already getting an abundance under the Democrats.

Under Obama, in 2015, the U.S. military budget was $598.5 billion, 54% of federal discretionary spending. Trump has added to that budget while Democrats in Congress voted overwhelmingly for the increase, passing a $716 billion military budget in 2018. Obama proposed a trillion dollars over thirty years to modernize the U.S. nuclear weapons program. Trump supports this increase and more and has increased the danger of nuclear proliferation with his withdrawal from the Iran nuclear agreement. Obama signed a memorandum of understanding with Prime Minister Benjamin Netanyahu of Israel to increase by eight billion dollars over a ten-year period our military support for the apartheid regime in Israel, bringing the total to $38 billion dollars. Trump supports this increase and has doubled down on U.S. support for Israel with his approval of moving the U.S. embassy in Israel to Jerusalem. Obama increased drone warfare initiated by the Bush administration. Trump has expanded the use of drones in Syria, Iraq, Pakistan, Yemen, and Somalia.

However, Obama began to open relations with Cuba, while Trump is intent on closing them.

Obama deported close to three million immigrants. At the same time, he instituted the Deferred Action for Childhood Arrivals Act (DACA), giving qualified relief from deportation to some of the children of undocumented immigrants. Trump, who is making war on immigrants from Latin American and the Middle East, began the phase-out of DACA in 2017. That phase-out is now in limbo due to court intervention. The Republican Congress failed to enact any version of the Dream Act, which would give these children, many now adults, who were brought here without agency of their own, a path to permanent residency. As of November 2018, the Democrats control the House; the Republicans remain in control of the Senate. And Trump remains in the White House so the possibilities for a stalemate on immigration are endless.

As for the Affordable Care Act, The Disinformation Age looks at how unaffordable this law has been for millions of people who live between expanded Medicaid (in the states where it exists) and Medicare. The Republicans want to eliminate the Act, so what seemed at best a half measure (instead of Medicare-For-All) at least protecting people with preexisting conditions, seems a full measure now, obscuring the need for universal, single-payer, affordable health care. In the 2018 midterm elections, the Democrats made health care the number one issue. But the party cant agree on what kind of health care there should be with the exception that preexisting conditions should be protected.

While Trump demonizes the presshis unsuccessful attempt to remove the press credentials of CNN reporter Jim Acosta resonatesthe Obama administration prosecuted whistleblowers, including sending the very visible Chelsea Manning and Edward Snowden, who sought to inform Americans of autocracy-creep in the federal government, to prison and exile. Following the April 2019, arrest of Julian Assange, the founder of WikiLeaks, Paul Waldman notes in his online April 11, 2019, opinion column in The Washington Post: The Obama administration, while critical of Assange, decided that the First Amendment implications of charging him with a crime were too troubling, so they declined to do so. Following suit in a way, the Trump administration at first charged Assange, if the British ever succeed in extraditing him, not with publishing documents obtained illegally, which would constitute a violation of press freedom, but with aiding Chelsea Manning in obtaining those documents by hacking U.S. government computers, even though the specific attempt charged was unsuccessful. But as of the end of May, 2019, the administration has changed those charges to espionage, thus threatening the basis of the First Amendment.

Under Trump, we now talk about fascism in the U.S.; but the militarized, corporate, surveillance state was already being put in place when Trump took office and added the singularly fascist component of scapegoatingdemonizing difference from the white, male, Protestant, heterosexual model.

While the Democrats are relatively strong in a generally conservative U.S. matrix on social issues of race and gender, and want to protect, by and large, Social Security and Medicare, the Republicans and Trump hate difference (demonized as deviance) from the white, male, Protestant, heterosexual modelhence their war on Muslim and Latinx immigrants. If we imagine a strong, government-supported network of basic social institutions in the areas of health, education, and welfare, think of the Republicans as the neoliberal wrecking crew without a plan for reconstruction except privatization to which the Democrats offer relatively little resistance (in comparison with the social programs of other Western European democracies): the economic condition of African Americans and other minorities deteriorated during the Obama administration as the entire U.S. middle-class continued to disappear. In his 2013 budget proposal Obama himself proposed cuts to Social Security and Medicare in order to compromise with the Republicans and reduce the deficit, something that the Congressional Republicans as of 2018 were proposing, while simultaneously increasing the deficit with Trump tax cuts.

Obama, who was certainly rhetorically strong on the environment, implemented some modest measures in that area along the lines of reducing coal and carbon emissions and at the end of his administration in 2016 instituted a substantial ban on drilling offshore in the Atlantic and Arctic, which Trump may be able to overturn. As Marianne Lavelle notes: By relying on executive orders and regulations after his legislative majority disappeared, President Obama leaves his climate policies at risk under Donald Trump. For it was only in his second term, as Lavelle documents, long after his Congressional majority disappeared, that Obama began to get serious about the environment, having concentrated in his first term on rebuilding the collapsed corporate economy, including increasing fossil fuel production. After waffling in his first term on implementation of the Keystone XL pipeline with its deadly load of tar sands oil, Obama rejected it in his second. Before leaving office Obama also put a check on the Dakota Access Pipeline (DAPL), set to run under the Missouri river at a place immediately threatening the water supply of the Standing Rock Sioux tribe. As expected, Trump has issued executive orders approving both pipelines. Both orders are being contested in the courts. But while the legal process has so far stopped the implementation of the Keystone XL, oil is flowing through the DAPL.

Obama signed the Paris Climate Accords, while Trump understands the environment only as a commodity to be traded for profit and signaled as much by planning to withdraw from the Accords. But many advocates of environmental justice have noted that the Accords, voluntary in the first place, are too little too late. This is no reason to shred but a reason to strengthen them and certainly not Trumps reason for opting outhe is in denial about climate collapsebut only to note that the recent Intergovernmental Panel on Climate Change (IPCC) report tells us that if we do not reduce global warming by 2.7 degrees Fahrenheit by 2040 we are facing a catastrophic situation. The report describes a world of worsening food shortages and wildfires, and a mass die-off of coral reefs as soon as 2040 a period well within the lifetime of much of the global population. In many ways, the catastrophes the IPCC describes resemble the world we are living in right now.

Overall, in a catastrophically unbalanced world, the Democrats are marginally preferable to the Republicans. But as The Disinformation Age argues, neither party, under the control of militarized, neoliberalist capitalism, has a demonstrable agenda to bring the world into economic, social, political, and environmental balance, which is a necessity if the human race is to survive. The world has already ended for millions of people and ends every year for millions more due to poverty, which is intensified by climate change. In the last chapter of The Disinformation Age, I ask us to think about how to achieve balance from an Indigenous perspective.

Although Barack Obama figures prominently in The Disinformation Age, the book is not about himhe mattered and yet matters little in the catastrophic global scheme of endless war and climate collapse. The same could be said for Trump, for that matter, or for any single leader. The book is, rather, an analysis of a destructive system, capitalism, for which Obama as the leader of the Democratic Party provided the principal, charming, hopeful mask at the time I was writing. Other presidents have worn the same mask. However unintentionally, Trump has ripped the mask off. The Disinformation Age focuses on the mask and what is beneath it, not the man.

Obama talked progressive and walked regressive, maintaining the neoliberal agenda (hegemony of privatization) at home and the neocon agenda (military expansion) at home and abroad. Trump marks the line where neoliberalism and neoconservatism begin to shade into fascism. On the level of style, Trump is the anti-Obama. He operates without Obamas charm or cosmopolitan intelligence and with a vicious political cunning that plays to the racism and misogyny of his base in contrast to the Hope Obama proffered but inevitably failed to realize because it cant be realized within the current system.

This failure, or more specifically, the failure of the Democratic Party as exemplified in the disastrous Hillary Clinton campaign offering more of the same, gave Trump his opening.

Eric Cheyfitz

Eric Cheyfitz is the Ernest I. White Professor of American Studies and Humane Letters at Cornell University, where he has served as director of the American Indian and Indigenous Studies Program, the faculty coordinator of the Mellon-Mays Undergraduate Fellowship Program, and the director of the Mellon Post-doctoral Diversity Seminar.

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Obama and Trump: The Present as Prologue to a History of Inequality - laprogressive.com

The big good things we got in the decade gone by – Echonetdaily

Phillip Frazer1. We got planetary awareness

When Galileo said that the Earth went around the Sun, not the other way around, priests tortured him.

Even now, its still hard to get that this big old world is a speck of dust in the universe, and its just as hard to get that eight billion of us living our tiny lives on Earths surface could have collectively changed the behaviour of the entire planet, dramatically, over the course of a couple of hundred years.

But we have. We didnt mean to fuck it up, but thats exactly what we did. We invented machines that converted energy that was lying around doing nothing into energy we found useful; for example burning petrol to keep 1,200,000,000 vehicles in motion as of this year.

And we made chemicals that kill bugs and weeds, and others that help plants grow, and we have sprayed these chemicals over vast areas of land to grow crops to feed animals so we can eat them.

Only a very few people understood 200 years ago that these fuels and (later) fertilisers, once they pass through a car or a cow, become airborne in the form of carbon dioxide and/or methane. And all those carbon molecules in the atmosphere enlarge a blanket of gas that every year allows less of the suns heat to bounce off the Earth and back into space.

The heat accumulating under the carbon blanket is now creating disasters all over the globe, and it will get worse every day unless we can stop it.

An awareness that we are members of an ecosystem on a relatively small planet has been beyond our collective consciousness until now. But now that houses are burning down and coastlines are eroding all over the planet, that awareness is spreading like, well, like wildfire.

Thats the good news, being spread most effectively by teenagers. The bad is that we have just a few decades to think together, and act together to save our species, which will require some huge failed projects to be abandoned; such as most religion, wars, private property, profit-hoarding, and male domination, for starters.

In 2010, WikiLeaks published documents and videos they had received from secret sources inside the US government. These words and images showed us what a million privileged people already knew from their libraries and billions of others knew in their gut: that the American military, shielded by propaganda dressing invasions up as democracy, had routinely committed appalling crimes against humanity including its own citizens in pursuit of its real agenda, which was the spread of raw and rampant capitalism.

Africans for example, knew that dictators had half of their countries wealth hidden in banks in Switzerland, but WikiLeaks showed them the bank statements, the receipts, and the contempt with which those dictators viewed their people.

We all knew that emperors and warlords were just men, but Julian Assange pulled their pants down in the new global public arena, the Internet, which is why the American elite will kill him or imprison him for life for the crime of saying the unspeakable.

The people who leaked the secrets, primarily Chelsea Manning (previously Bradley Manning), were themselves Americans, but it was perhaps necessary that an almost-American outsider like Julian would be the one to pull down Uncle Sams pants.

The womens movement, the gay and lesbian movement, the peace movement, environmentalism, and the rest of the movements seeking to replace the exhausted cultures of the post Second World War world, all knew that the patriarchy and its rules were a plague on the planet.

Tarana Banks started the #MeToo movement in 2006 and it reached another tipping point in 2017. What #MeToo did was call out men who were pulling down their own pants and using their patriarchal power and privilege to violate women physically and in every other way.

When he saw 2017 Golden Globe award-winning women espousing #MeToo-ism from the podium, Stephen Bannon the brain behind Trumps rise to power saw #MeToos true meaning. Women are gonna take charge the anti-patriarchy movement is going to undo ten thousand years of recorded history, he screamed at the television, and for good measure If you rolled out a guillotine, theyd chop off every set of balls in the room. This is Steves worst nightmare, and so it is for Trump, Boris Johnson, Scott Morrison, and all their truck nuts mates (https://tinyurl.com/trucknuts-com).

Putting men in charge of everything has achieved many great things, and, ultimately and spectacularly, it also has failed.

When Europeans invaded Australia 230 years ago, armed with the latest deadly weapons, they ignored the rights of the people who had been on this continent for 60,000 years or more. In fact, they enslaved them and killed them in numbers only now being counted.

As the 2010s have staggered to the finish line, the tipping point has been reached, such that Indigenous Australians can no longer be ignored or killed at the whim of the Anglo-Saxon-Celtic branch of the patriarchy.

The Aboriginal community has had resistors who fought the Euro-Australians with weapons, some who pleaded with them for mercy, some who argued and even won an argument or two in court. And some white fellas saw the injustice and called it out.

But in 2017 the Uluru statement from the heart emerged as a definitive challenge, asking white fellas to walk with them, the black fellas. This time theyre not gonna take No for an answer, and they will get a voice, recognition, and compensation perhaps, even atonement, whatever todays rump of the patriarchy does or says.

Somewhere in all of the above are flickering fires of positive change and yes thats a terrible metaphor to use when half the country is on fire, but thats the kind of world we are in right now. Time is no longer on anyones side.

Tomorrow we start another spin around the Sun and another decade. Every day, more kids get it, that they cant allow the big Boys Club to own the Big Stuff one more decade.

Phillip Frazer does existential accounting at coorabellridge.com.

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The big good things we got in the decade gone by - Echonetdaily

Machine Learning to Predict the 1-Year Mortality Rate After Acute Ante | TCRM – Dove Medical Press

Yi-ming Li,1,* Li-cheng Jiang,2,* Jing-jing He,1 Kai-yu Jia,1 Yong Peng,1 Mao Chen1

1Department of Cardiology, West China Hospital, Sichuan University, Chengdu, Peoples Republic of China; 2Department of Cardiology, The First Affiliated Hospital, Chengdu Medical College, Chengdu, Peoples Republic of China

*These authors contributed equally to this work

Correspondence: Yong Peng; Mao ChenDepartment of Cardiology, West China Hospital, Sichuan University, 37 Guoxue Street, Chengdu 610041, Peoples Republic of ChinaEmail pengyongcd@126.com; hmaochen@vip.sina.com

Abstract: A formal risk assessment for identifying high-risk patients is essential in clinical practice and promoted in guidelines for the management of anterior acute myocardial infarction. In this study, we sought to evaluate the performance of different machine learning models in predicting the 1-year mortality rate of anterior ST-segment elevation myocardial infarction (STEMI) patients and to compare the utility of these models to the conventional Global Registry of Acute Coronary Events (GRACE) risk scores. We enrolled all of the patients aged >18 years with discharge diagnoses of anterior STEMI in the Western China Hospital, Sichuan University, from January 2011 to January 2017. A total of 1244 patients were included in this study. The mean patient age was 63.812.9 years, and the proportion of males was 78.4%. The majority (75.18%) received revascularization therapy. In the prediction of the 1-year mortality rate, the areas under the curve (AUCs) of the receiver operating characteristic curves (ROCs) of the six models ranged from 0.709 to 0.942. Among all models, XGBoost achieved the highest accuracy (92%), specificity (99%) and f1 score (0.72) for predictions with the full variable model. After feature selection, XGBoost still obtained the highest accuracy (93%), specificity (99%) and f1 score (0.73). In conclusion, machine learning algorithms can accurately predict the rate of death after a 1-year follow-up of anterior STEMI, especially the XGBoost model.

Keywords: machine learning, prediction model, acute anterior myocardial infarction

This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution - Non Commercial (unported, v3.0) License.By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms.

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Machine Learning to Predict the 1-Year Mortality Rate After Acute Ante | TCRM - Dove Medical Press

Forget Machine Learning, Constraint Solvers are What the Enterprise Needs – – RTInsights

Constraint solvers take a set of hard and soft constraints in an organization and formulate the most effective plan, taking into account real-time problems.

When a business looks to implement an artificial intelligence strategy, even proper expertise can be too narrow. Its what has led many businesses to deploy machine learning or neural networks to solve problems that require other forms of AI, like constraint solvers.

Constraint solvers take a set of hard and soft constraints in an organization and formulate the most effective plan, taking into account real-time problems. It is the best solution for businesses that have timetabling, assignment or efficiency issues.

In a RedHat webinar, principal software engineer, Geoffrey De Smet, ran through three use cases for constraint solvers.

Vehicle Routing

Efficient delivery management is something Amazon has seemingly perfected, so much so its now an annoyance to have to wait 3-5 days for an item to be delivered. Using RedHats OptaPlanner, businesses can improve vehicle routing by 9 to 18 percent, by optimizing routes and ensuring drivers are able to deliver an optimal amount of goods.

To start, OptaPlanner takes in all the necessary constraints, like truck capacity and driver specialization. It also takes into account regional laws, like the amount of time a driver is legally allowed to drive per day and creates a route for all drivers in the organization.

SEE ALSO: Machine Learning Algorithms Help Couples Conceive

In a practical case, De Smet said RedHat saved a technical vehicle routing company over $100 million in savings per year with the constraint solver. Driving time was reduced by 25 percent and the business was able to reduce its headcount by 10,000.

The benefits [of OptaPlanner] are to reduce cost, improve customer satisfaction, employee well-being and save the planet, said De Smet. The nice thing about some of these are theyre complementary, for example reducing travel time also reduces fuel consumption.

Employee timetabling

Knowing who is covering what shift can be an infuriating task for managers, with all the requests for time off, illness and mandatory days off. In a place where 9 to 5 isnt regular, it can be even harder to keep track of it all.

RedHats OptaPlanner is able to take all of the hard constraints (two days off per week, no more than eight-hour shifts) and soft constraints (should have up to 10 hours rest between shifts) and can formulate a timetable that takes all that into account. When someone asks for a day off, OptaPlanner is able to reassign workers in real-time.

De Smet said this is useful for jobs that need to run 24/7, like hospitals, the police force, security firms, and international call centers. According to RedHats simulation, it should improve employee well-being by 19 to 85 percent, alongside improvements in retention and customer satisfaction.

Task assignment

Even within a single business department, there are skills only a few employees have. For instance, in a call center, only a few will be able to speak fluently in both English and French. To avoid customer annoyance, it is imperative for employees with the right skill-set to be assigned correctly.

With OptaPlanner, managers are able to add employee skills and have the AI assign employees correctly. Using the call center example again, a bilingual advisor may take all calls in French for one day when theres a high demand for it, but on others have a mix of French and English.

For customer support, the constraint solver would be able to assign a problem to the correct advisor, or to the next best thing, before the customer is connected, thus avoiding giving out the wrong advice or having to pass the customer on to another advisor.

In the webinar, De Smet said that while the constraint solver is a valuable asset for businesses looking to reduce costs, this shouldnt be their only aim.

Without having all stakeholders involved in the implementation, the AI could end up harming other areas of the business, like customer satisfaction or employee retention. This is a similar warning given from all analysts on AI implementation it needs to come from a genuine desire to improve the business to get the best outcome.

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Forget Machine Learning, Constraint Solvers are What the Enterprise Needs - - RTInsights

How Will Your Hotel Property Use Machine Learning in 2020 and Beyond? | – Hotel Technology News

Every hotel should ask the same question. How will our property use machine learning? Its not just a matter of gaining a competitive advantage; its imperative in order to stay in business.By Jason G. Bryant, Founder and CEO, Nor1 - 1.9.2020

Artificial intelligence (AI) implementation has grown 270% over the past four years and 37% in the past year alone, according to Gartners 2019 CIO Survey of more than 3,000 executives. About the ubiquity of AI and machine learning (ML) Gartner VP Chris Howard notes, If you are a CIO and your organization doesnt use AI, chances are high that your competitors do and this should be a concern, (VentureBeat). Hotels may not have CIOs, but any business not seriously considering the implications of ML throughout the organization will find itself in multiple binds, from the inability to offer next-level guest service to operational inefficiencies.

Amazon is the poster child for a sophisticated company that is committed to machine learning both in offers (personalized commerce) as well as behind the scenes in their facilities. Amazon Founder & CEO Jeff Bezos attributes much of Amazons ongoing financial success and competitive dominance to machine learning. Further, he has suggested that the entire future of the company rests on how well it uses AI. However, as Forbes contributor Kathleen Walsh notes, There is no single AI group at Amazon. Rather, every team is responsible for finding ways to utilize AI and ML in their work. It is common knowledge that all senior executives at Amazon plan, write, and adhere to a six-page business plan. A piece of every business plan for every business function is devoted to answering the question: How will you utilize machine learning this year?

Every hotel should ask the same question. How will our property use machine learning? Its not just a matter of gaining a competitive advantage; its imperative in order to stay in business. In the 2017 Deloitte State of Cognitive Survey, which canvassed 1,500 mostly C-level executives, not a single survey respondent believed that cognitive technologies would not drive substantive change. Put more simply: every executive in every industry knows that AI is fundamentally changing the way we do business, both in services/products as well as operations. Further, 94% reported that artificial intelligence would substantially transform their companies within five years, most believing the transformation would occur by 2020.

Playing catch-up with this technology can be competitively dangerous as there is significant time between outward-facing results (when you realize your competition is outperforming you) and how long it will take you to achieve similar results and employ a productive, successful strategy. Certainly, revenue management and pricing will be optimized by ML, but operations, guest service, maintenance, loyalty, development, energy usage, and almost every single aspect of the hospitality enterprise will be impacted as well. Any facility where the speed and precision of tactical decision making can be improved will be positively impacted.

Hotels are quick to think that when ML means robotic housekeepers and facial recognition kiosks. While these are possibilities, ML can do so much more. Here are just a few of the ways hotels are using AI to save money, improve service, and become more efficient.

Hiltons Energy Program

The LightStay program at Hilton predicts energy, water, and waste usage and costs. The company can track actual consumption against predictive models, which allows them to manage year-over-year performance as well as performance against competitors. Further, some hotel brands can link in-room energy to the PMS so that when a room is empty, the air conditioner automatically turns off. The future of sustainability in the hospitality industry relies on ML to shave every bit off of energy usage and budget. For brands with hundreds and thousands of properties, every dollar saved on energy can affect the bottom line in a big way.

IHG & Human Resources

IHG employs 400,000 people across 5,723 hotels. Holding fast to the idea that the ideal guest experience begins with staff, IHG implemented AI strategies tofind the right team member who would best align and fit with each of the distinct brand personalities, notes Hazel Hogben, Head of HR, Hotel Operations, IHG Europe. To create brand personas and algorithms, IHG assessed its top customer-facing senior managers across brands using cognitive, emotional, and personality assessments. They then correlated this with KPI and customer data. Finally, this was cross-referenced with values at the different brands. The algorithms are used to create assessments to test candidates for hire against the personas using gamification-based tools, according to The People Space. Hogben notes that in addition to improving the candidate experience (they like the gamification of the experience), it has also helped in eliminating personal or preconceived bias among recruiters. Regarding ML uses for hiring, Harvard Business Review says in addition to combatting human bias by automatically flagging biased language in job descriptions, ML also identifies highly qualified candidates who might have been overlooked because they didnt fit traditional expectations.

Accor Hotels Upgrades

A 2018 study showed that 70% of hotels say they never or only sometimes promote upgrades or upsells at check-in (PhocusWire). In an effort to maximize the value of premium inventory and increase guest satisfaction, Accor Hotels partnered with Nor1 to implement eStandby Upgrade. With the ML-powered technology, Accor Hotels offers guests personalized upgrades based on previous guest behavior at a price that the guest has shown a demonstrated willingness to pay at booking and during the pre-arrival period, up to 24 hours before check-in. This allows the brand to monetize and leverage room features that cant otherwise be captured by standard room category definitions and to optimize the allocation of inventory available on the day of arrival. ML technology can create offers at any point during the guest pathway, including the front desk. Rather than replacing agents as some hotels fear, it helps them make better, quicker decisions about what to offer guests.

Understanding Travel Reviews

The luxury Dorchester Collection wanted to understand what makes their high-end guests tick. Instead of using the traditional secret shopper methods, which dont tell hotels everything they need to know about their experience, Dorchester Collection opted to analyze traveler feedback from across major review sites using ML. Much to their surprise, they discovered Dorchesters guests care a great deal more about breakfast than they thought. They also learned that guests want to customize breakfast, so they removed the breakfast menu and allowed guests to order whatever they like. As it turns out, guests love this.

In his May 2019 Google I/O Address, Google CEO Sundar Pichai said, Thanks to advances in AI, Google is moving beyond its core mission of organizing the worlds information. We are moving from a company that helps you find answers to a company that helps you get things done (ZDNet). Pichai has long held that we no longer live in a mobile-first world; we now inhabit an AI-first world. Businesses must necessarily pivot with this shift, evolving processes and products, sometimes evolving the business model, as in Googles case.

Hotels that embrace ML across operations will find that the technologies improve processes in substantive ways. ML improves the guest experience and increases revenue with precision decisioning and analysis across finance, human resources, marketing, pricing and merchandising, and guest services. Though the Hiltons, Marriotts, and IHGs of the hotel world are at the forefront of adoption, ML technologies are accessibleboth in price and implementationfor the full range of properties. The time has come to ask every hotel department: How will you use AI this year?

For more about Machine Learning and the impact on the hotel industry, download NOR1s ebook The Hospitality Executives Guide to Machine Learning: Will You Be a Leader, Follower, or Dinosaur?

Jason G. Bryant, Nor1 Founder and CEO, oversees day-to-day operations, provides visionary leadership and strategic direction for the upsell technology company. With Jason at the helm, Nor1 has matured into the technology leader in upsell solutions. Headquartered in Silicon Valley, Nor1 provides innovative revenue enhancement solutions to the hospitality industry that focus on the intersection of machine learning, guest engagement and operational efficiency. A seasoned entrepreneur, Jason has over 25 years experience building and leading international software development and operations organizations.

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How Will Your Hotel Property Use Machine Learning in 2020 and Beyond? | - Hotel Technology News

Limits of machine learning – Deccan Herald

Suppose you are driving a hybrid car with a personalised Alexa prototype and happen to witness a road accident. Will your Alexa automatically stop the car to help the victim or call an ambulance? Probably,it would act according tothe algorithmprogrammed into itthat demands the users command.

But as a fellow traveller with Alexa, what would you do? If you areanempathetic human being, you would try to administer first aid and take the victim to a nearby hospital in your car. This empathy is what is missing in the machines, largely in the technocratic conquered education which parents are banking upon these days.

Tech-buddies

With the advancement of bots or robots teaching in our classrooms, theteachersof millennials are worried. Recently, a WhatsApp video of AI-teacher engaging class in one of the schools of Bengaluru went viral. Maybe in a decade or two, academic robots in our classrooms would teach mathematics. Or perhaps they will teach children the algorithmsthatbrings them to life and togetherthey can create another generation of tech-buddies.

I was informed by a friend that coding is taught atprimary level now which was indeed a surprise for me. Then what about other skills? Maybe life skills like swimming, cooking could also be taught by a combination of YouTube and personal robots. However, we have the edge over the machines in at least one area and thats basic human values. This is where human intervention cant be eliminated at all.

The values are not taught; rather they are ingrained at every phase of life by various people who we meet including parents, teachers, peers, and anyone around us alongside practising them. Say for example, how does one teach kids to care for the elderly at home?

Unless one feels the same emotional turmoilas the elderly before them as they are raised and apply the compassionate values, they wouldnt be motivated to take care of them.

The missing link in academia

The discussions on trans-disciplinary or interdisciplinary courses often put forward multiple subjects as well as unconventional subjects to study together. Like engineering and terracotta designs or literature and agriculture. However, the objection comes within academia citing a lack of career prospects.

We tend to forget the fact that the best mathematicians were also musicians and the best medicinal practitioners were botanists or farmers too. Interest in one subject might trigger gaining expertise in others and connect the discreet dots to create a completely new concept.

Life skills like agriculture, pottery, animal care, gardening, andhousing are essentialskills that have many benefits.Every rural person is equipped with these skills through surrounding experiences. Rather than in a classroom session, these learning takes place by seeing, interacting as well as making mistakes.

A friend who homeschooled both her kids had similar concerns. She was firmly against the formalised education which teaches a limited amount of information mostly based on memorisation taking out the natural interest of the child. Several such institutes are functioning to serve the same goals of lifelong learning. Such schools aiming at understanding human-nature, emotional wellbeing, artistic and critical thinking are fundamentally guided on the idea of learning in a fear-free environment.

When scrolling on the admissions page in these schools, I was surprised that the admissions for the 2021 academic year were already completed.This reflects the eagerness of many parents looking for such alternative education systems.

These analogies bring back the basic question of why education? If it is merely for technology-driven jobs, probably by the time your kids grow there wouldnt be many jobs as themachines would have snatched them.

Also, the country is moving towards a technology-driven economy and may not need many skilled labourers. Surely, a few post-millennials would survive in any condition if they are extremely smart and adoptive butthey may need to stop and reboot if theireducation has not prepared them for uncertainties to come.

(The writer is with Christ, Bengaluru)

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Limits of machine learning - Deccan Herald

Dell’s Latitude 9510 shakes up corporate laptops with 5G, machine learning, and thin bezels – PCWorld

Dell's Latitude 9510 shakes up corporate laptops with 5G, machine learning, and thin bezels | PCWorld ');consent.ads.queue.push(function(){ try { IDG.GPT.addDisplayedAd("gpt-superstitial", "true"); $('#gpt-superstitial').responsiveAd({screenSize:'971 1115', scriptTags: []}); IDG.GPT.log("Creating ad: gpt-superstitial [971 1115]"); }catch (exception) {console.log("Error with IDG.GPT: " + exception);} }); This business workhorse has a lot to like.

Dell Latitude 9510 hands-on: The three best features

Dell's Latitude 9510 has three features we especially love: The integrated 5G, the Dell Optimizer Utility that tunes the laptop to your preferences, and the thin bezels around the huge display.

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The Dell Latitude 9510 is a new breed of corporate laptop. Inspired in part by the companys powerful and much-loved Dell XPS 15, its the first model in an ultra-premium business line packed with the best of the best, tuned for business users.

Announced January 2 and unveiled Monday at CES in Las Vegas, the Latitude 9510 weighs just 3.2 pounds and promises up to 30 hours of battery life.PCWorld had a chance to delve into the guts of the Latitude 9510, learning more about whats in it and how it was built. Here are the coolest things we saw:

The Dell Latitude 9510 is shown disassembled, with (top, left to right) the magnesium bottom panel, the aluminum display lid, and the internals; and (bottom) the array of ports, speaker chambers, keyboard, and other small parts.

The thin bezels around the 15.6-inch screen (see top of story) are the biggest hint that the Latitude 9510 took inspiration from its cousin, the XPS 15. Despite the size of the screen, the Latitude 9510 is amazingly compact. And yet, Dell managed to squeeze in a camera above the displaythanks to a teeny, tiny sliver of a module.

A closer look at the motherboard of the Dell Latitude 9510 shows the 52Wh battery and the areas around the periphery where Dell put the 5G antennas.

The Latitude 9510 is one of the first laptops weve seen with integrated 5G networking. The challenge of 5G in laptops is integrating all the antennas you need within a metal chassis thats decidedly radio-unfriendly.

Dell made some careful choices, arraying the antennas around the edges of the laptop and inserting plastic pieces strategically to improve reception. Two of the antennas, for instance, are placed underneath the plastic speaker components and plastic speaker grille.

The Dell Latitude 9510 incorporated plastic speaker panels to allow reception for the 5G antennas underneath.

Not ready for 5G? No worries. Dell also offers the Latitude 9510 with Wi-Fi 6, the latest wireless networking standard.

You are constantly asking your PC to do things for you, usually the same things, over and over. Dells Optimizer software, which debuts on the Latitude 9510, analyzes your usage patterns and tries to save you time with routine tasks.

For instance, the Express SignIn feature logs you in faster. The ExpressResponse feature learns which applications you fire up first and loads them faster for you. Express Charge watches your battery usage and will adjust settings to save bettery, or step in with faster charging when you need some juice, pronto. Intelligent Audio will try to block out background noise so you can videoconference with less distraction.

The Dell Latitude 9510s advanced features and great looks should elevate corporate laptops in performance as well as style.It will come in clamshell and 2-in-1 versions, and is due to ship March 26. Pricing is not yet available.

Melissa Riofrio spent her formative journalistic years reviewing some of the biggest iron at PCWorld--desktops, laptops, storage, printers. As PCWorld's Executive Editor she leads PCWorlds content direction and covers productivity laptops and Chromebooks.

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Dell's Latitude 9510 shakes up corporate laptops with 5G, machine learning, and thin bezels - PCWorld

Warner Bros. signs AI startup that claims to predict film success – The Verge

Storied film company Warner Bros. has signed a deal with Cinelytic, an LA startup that uses machine learning to predict film success. A story from The Hollywood Reporter claims that Warner Bros. will use Cinelytics algorithms to guide decision-making at the greenlight stage, but a source at the studio told The Verge that the software would only be used to help with marketing and distribution decisions made by Warner Bros. Pictures International.

In an interview with THR, Cinelytics CEO Tobias Queisser stressed that AI was only an assistive tool. Artificial intelligence sounds scary. But right now, an AI cannot make any creative decisions, Queisser told the publication. What it is good at is crunching numbers and breaking down huge data sets and showing patterns that would not be visible to humans. But for creative decision-making, you still need experience and gut instinct.

Regardless of what Cinelytics technology is being used for, the deal is a step forward for Hollywoods slow embrace of machine learning. As The Verge reported last year, Cinelytic is just one of a new crop of startups leveraging AI to forecast film performance, but the film world has historically been skeptical about their ability.

Andrea Scarso, a film investor and Cinelytic customer, told The Verge that the startups software hadnt ever changed his mind, but opens up a conversation about different approaches. Said Scarso: You can see how, sometimes, just one or two different elements around the same project could have a massive impact on the commercial performance.

Cinelytics software lets customers play fantasy football with films. Users can model a pitch; inputting genre, budget, actors, and so on, and then see what happens when they tweak individual elements. Does replacing Tom Cruise with Keanu Reeves get better engagement with under-25s? Does it increase box office revenue in Europe? And so on.

Many AI experts are skeptical about the ability of algorithms to make predictions in a field as messy as filmmaking. Because machine learning applications are trained on historical data they tend to be conservative, focusing on patterns that led to past successes rather than predicting what will excite future audiences. Scientific studies also suggest algorithms only produce limited predictive gains, often repeating obvious insights (like Scarlett Johansson is a bankable film star) that can be discovered without AI.

But for those backing machine learning in filmmaking, the benefit is simply that such tools produce uncomplicated analysis faster than humans can. This can be especially useful at film festivals, notes THR, when studios can be forced into bidding wars for distribution rights, and have only a few hours to decide how much a film might be worth.

We make tough decisions every day that affect what and how we produce and deliver films to theaters around the world, and the more precise our data is, the better we will be able to engage our audiences, Warner Bros. senior vice president of distribution, Tonis Kiis, told THR.

Update January 8, 11:00AM ET: Story has been updated with additional information from a source at Warner Bros.

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Warner Bros. signs AI startup that claims to predict film success - The Verge