Beyond Evergrande, China’s Property Market Faces a $5 Trillion Reckoning

As many economists say China enters what is now the final phase of one of the biggest real-estate booms in history, it is facing a staggering bill: According to economists at Nomura, $ 5 trillion plus loans that developers had taken at a good time. Holdings Inc.

The debt is almost double that at the end of 2016 and last year exceeded the overall economic output of Japan, the world’s third-largest economy.

With warning signs on the debt of nearly two-fifths of growth companies borrowed from international bond investors, global markets are poised for a potential wave of defaults.

Chinese leaders are getting serious about addressing debt by taking a series of steps to curb excessive borrowing. But doing so without hurting the property market, crippling more developers and derailing the country’s economy is turning into one of the biggest economic challenges for Chinese leaders, and one that resonates globally when mismanaged. could.

Luxury Developer Fantasia Holdings Group Co. It failed to pay $206 million in dollar bonds that matured on October 4. In late September, Evergrande, which has more than $300 billion in liabilities, missed two interest-paying deadlines for the bond.

A wave of sell-offs hit Asian junk-bond markets last week. On Friday, bonds of 24 of 59 Chinese growth companies on the ICE BofA Index of Asian Corporate Dollar Bonds were trading at over 20% yields, indicating a high risk of default.

Some potential home buyers are leaning, forcing companies to cut prices to raise cash, and could potentially accelerate their slide if the trend continues.

According to data from CRIC, a research arm of property services firm e-House (China) Enterprise Holdings, overall sales among China’s 100 largest developers were down 36 per cent in September from a year earlier. Ltd.

It revealed that the 10 largest developers, including China Evergrande, Country Garden Holdings Co. and china wenke Co., saw a decline of 44% in sales compared to a year ago.

Economists say most Chinese developers remain relatively healthy. Beijing has the firepower and tighter control of the financial system needed to prevent the so-called Lehman moment, in which a corporate financial crisis snowballs, he says.

In late September, Businesshala reported that China had asked local governments to be prepared for potentially intensifying problems in Evergrande.

But many economists, investors and analysts agree that even for healthy enterprises, the underlying business model—in which developers use credit to fund steady churn of new construction despite the demographic less favorable for new housing—is likely to change. Chances are. Some developers can’t survive the transition, he says.

Of particular concern is some developers’ practice of relying heavily on “presales”, in which buyers pay upfront for still-unfinished apartments.

The practice, more common in China than in the US, means developers are borrowing interest-free from millions of homes, making it easier to continue expanding but potentially leaving buyers without ready-made apartments for developers to fail. needed.

According to China’s National Bureau of Statistics, pre-sales and similar deals were the region’s biggest funding sources since August this year.

“There is no return to the previous growth model for China’s real-estate market,” said Hous Song, a research fellow at the Paulson Institute, a Chicago think tank focused on US-China relations. China is likely to put a set of limits on corporate lending, known as the “three red lines” imposed last year, which helped trigger the recent crisis on some developers, he added. That China can ease some other restrictions.

While Beijing has avoided explicit public statements on its plans to deal with the most indebted developers, many economists believe leaders have no choice but to keep the pressure on them.

Policymakers are determined to reform a model fueled by debt and speculation as part of President Xi Jinping’s broader efforts to mitigate the hidden risks that could destabilize society, especially at key Communist Party meetings next year. before. Mr. Xi is widely expected to break the precedent and extend his rule to a third term.

Economists say Beijing is concerned that after years of rapid home price gains, some may be unable to climb the housing ladder, potentially fueling social discontent, as economists say. The cost of young couples is starting to drop in large cities, making it difficult for them to start a family. According to JPMorgan Asset Management, the median apartment in Beijing or Shenzhen now accounts for more than 40 times the average family’s annual disposable income.

Officials have said they are concerned about the risk posed by the asset market to the financial system. Reinforcing developers’ business models and limiting debt, however, is almost certain to slow investment and cause at least some slowdown in the property market, one of the biggest drivers of China’s growth.

The real estate and construction industries account for a large portion of China’s economy. Researchers Kenneth S. A 2020 paper by Rogoff and Yuanchen Yang estimated that industries, roughly, account for 29% of China’s economic activity, far more than in many other countries. Slow housing growth could spread to other parts of the economy, affecting consumer spending and employment.

Government figures show that about 1.6 million acres of residential floor space were under construction at the end of last year. This was roughly equivalent to 21,000 towers with the floor area of ​​the Burj Khalifa in Dubai, the tallest building in the world.

Housing construction fell by 13.6% in August below its pre-pandemic level, as restrictions on borrowing were imposed last year, calculations by Oxford Economics show.

Local governments’ income from selling land to developers declined by 17.5% in August from a year earlier. Local governments, which are heavily indebted, rely on the sale of land for most of their revenue.

Another slowdown will also risk exposing banks to more bad loans. According to Moody’s Analytics, outstanding property loans—mainly mortgages, but also loans to developers—accounted for 27% of China’s total of $28.8 trillion in bank loans at the end of June.

As pressure on housing mounts, many research houses and banks have cut China’s growth outlook. Oxford Economics on Wednesday lowered its forecast for China’s third-quarter year-on-year GDP growth from 5% to 3.6%. It lowered its 2022 growth forecast for China from 5.8% to 5.4%.

As recently as the 1990s, most city residents in China lived in monotonous residences provided by state-owned employers. When market reforms began to transform the country and more people moved to cities, China needed a massive supply of high-quality apartments. Private developers stepped in.

Over the years, he added millions of new units to modern, streamlined high-rise buildings. In 2019, new homes made up more than three-quarters of home sales in China, less than 12% in the US, according to data cited by Chinese property broker Kei Holdings Inc. in a listing prospectus last year.

In the process, developers grew to be much bigger than anything seen in the US, the largest US home builder by revenue, DR Horton. Inc.,

Reported assets of $21.8 billion at the end of June. Evergrande had about $369 billion. Its assets included vast land reserves and 345,000 unsold parking spaces.

For most of the boom, developers were filling a need. In recent years, policymakers and economists began to worry that much of the market was driven by speculation.

Chinese households are prohibited from investing abroad, and domestic bank deposits provide low returns. Many people are wary of the country’s booming stock markets. So some have poured money into housing, in some cases buying three or four units without the intention of buying or renting them out.

As developers bought more places to build, land sales boosted the national growth figures. Dozens of entrepreneurs who founded growth companies are featured on the list of Chinese billionaires. Ten of the 16 soccer clubs of the Chinese Super League are wholly or partially owned by the developers.

Real-estate giants borrow not only from banks but also from shadow-banking organizations known as trust companies and individuals who invest their savings in investments called wealth-management products. Overseas, they became a mainstay of international junk-bond markets, offering juicy produce to snag deals.

A builder, Kaisa Group Holdings Ltd. , defaulted on its debt in 2015, was still able to borrow and later expand. Two years later it spent the equivalent of $2.1 billion to buy 25 land parcels, and $7.3 billion for land in 2020. This summer, Cassa sold $200 million of short-term bonds with a yield of 8.65%.

By: Quentin Webb & Stella Yifan Xie 

Source: Beyond Evergrande, China’s Property Market Faces a $5 Trillion Reckoning – WSJ

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AI Can Write Code Like Humans Bugs and All

Some software developers are now letting artificial intelligence help write their code. They’re finding that AI is just as flawed as humans.

Last June, GitHub, a subsidiary of Microsoft that provides tools for hosting and collaborating on code, released a beta version of a program that uses AI to assist programmers. Start typing a command, a database query, or a request to an API, and the program, called Copilot, will guess your intent and write the rest.

Alex Naka, a data scientist at a biotech firm who signed up to test Copilot, says the program can be very helpful, and it has changed the way he works. “It lets me spend less time jumping to the browser to look up API docs or examples on Stack Overflow,” he says. “It does feel a little like my work has shifted from being a generator of code to being a discriminator of it.”

But Naka has found that errors can creep into his code in different ways. “There have been times where I’ve missed some kind of subtle error when I accept one of its proposals,” he says. “And it can be really hard to track this down, perhaps because it seems like it makes errors that have a different flavor than the kind I would make.”

The risks of AI generating faulty code may be surprisingly high. Researchers at NYU recently analyzed code generated by Copilot and found that, for certain tasks where security is crucial, the code contains security flaws around 40 percent of the time.

The figure “is a little bit higher than I would have expected,” says Brendan Dolan-Gavitt, a professor at NYU involved with the analysis. “But the way Copilot was trained wasn’t actually to write good code—it was just to produce the kind of text that would follow a given prompt.”

Despite such flaws, Copilot and similar AI-powered tools may herald a sea change in the way software developers write code. There’s growing interest in using AI to help automate more mundane work. But Copilot also highlights some of the pitfalls of today’s AI techniques.

While analyzing the code made available for a Copilot plugin, Dolan-Gavitt found that it included a list of restricted phrases. These were apparently introduced to prevent the system from blurting out offensive messages or copying well-known code written by someone else.

Oege de Moor, vice president of research at GitHub and one of the developers of Copilot, says security has been a concern from the start. He says the percentage of flawed code cited by the NYU researchers is only relevant for a subset of code where security flaws are more likely.

De Moor invented CodeQL, a tool used by the NYU researchers that automatically identifies bugs in code. He says GitHub recommends that developers use Copilot together with CodeQL to ensure their work is safe.

The GitHub program is built on top of an AI model developed by OpenAI, a prominent AI company doing cutting-edge work in machine learning. That model, called Codex, consists of a large artificial neural network trained to predict the next characters in both text and computer code. The algorithm ingested billions of lines of code stored on GitHub—not all of it perfect—in order to learn how to write code.

OpenAI has built its own AI coding tool on top of Codex that can perform some stunning coding tricks. It can turn a typed instruction, such as “Create an array of random variables between 1 and 100 and then return the largest of them,” into working code in several programming languages.

Another version of the same OpenAI program, called GPT-3, can generate coherent text on a given subject, but it can also regurgitate offensive or biased language learned from the darker corners of the web.

Copilot and Codex have led some developers to wonder if AI might automate them out of work. In fact, as Naka’s experience shows, developers need considerable skill to use the program, as they often must vet or tweak its suggestions.

Hammond Pearce, a postdoctoral researcher at NYU involved with the analysis of Copilot code, says the program sometimes produces problematic code because it doesn’t fully understand what a piece of code is trying to do. “Vulnerabilities are often caused by a lack of context that a developer needs to know,” he says.

Some developers worry that AI is already picking up bad habits. “We have worked hard as an industry to get away from copy-pasting solutions, and now Copilot has created a supercharged version of that,” says Maxim Khailo, a software developer who has experimented with using AI to generate code but has not tried Copilot.

Khailo says it might be possible for hackers to mess with a program like Copilot. “If I was a bad actor, what I would do would be to create vulnerable code projects on GitHub, artificially boost their popularity by buying GitHub stars on the black market, and hope that it will become part of the corpus for the next training round.”

Both GitHub and OpenAI say that, on the contrary, their AI coding tools are only likely to become less error prone. OpenAI says it vets projects and code both manually and using automated tools.

De Moor at GitHub says recent updates to Copilot should have reduced the frequency of security vulnerabilities. But he adds that his team is exploring other ways of improving the output of Copilot. One is to remove bad examples that the underlying AI model learns from. Another may be to use reinforcement learning, an AI technique that has produced some impressive results in games and other areas, to automatically spot bad output, including previously unseen examples. “Enormous improvements are happening,” he says. “It’s almost unimaginable what it will look like in a year.”

Source: AI Can Write Code Like Humans—Bugs and All | WIRED

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The Online Data That’s Being Deleted

For years, we were encouraged to store our data online. But it’s become increasingly clear that this won’t last forever – and now the race is on to stop our memories being deleted. How would you adjust your efforts to preserve digital data that belongs to you – emails, text messages, photos and documents – if you knew it would soon get wiped in a series of devastating electrical storms?

That’s the future catastrophe imagined by Susan Donovan, a high school teacher and science fiction writer based in New York. In her self-published story New York Hypogeographies, she describes a future in which vast amounts of data get deleted thanks to electrical disturbances in the year 2250.

In the years afterwards, archaeologists comb through ruined city apartments looking for artefacts from the past – the early 2000s.

“I was thinking about, ‘How would it change people going through an event where all of your digital stuff is just gone?’” she says.

In her story, the catastrophic data loss is not a world-ending event. But it is a hugely disruptive one. And it prompts a change in how people preserve important data. The storms bring a renaissance of printing, Donovan writes. But people are also left wondering how to store things that can’t be printed – augmented reality games, for instance.

Data has never been completely safe from obliteration. Just consider the burning of the Great Library of Alexandria – its very destruction is possibly the only reason you’ve heard about it. Digital data does not disappear in huge conflagrations, but rather with a single click or the silent, insidious degradation of storage media over time.

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Today, we’re becoming accustomed to such deletions. There are lots of examples – the MySpace profiles that famously vanished in 2019. Or the many Google services that have shut down over the years. And then there are the online data storage companies that have offered to keep people’s data safe for them. Ironically, they have sometimes ended up earmarking it for deletion.

In other cases, these services actually keep running for long periods. But users might lose their login details. Or forget, even, that they had an account in the first place. They’ll probably never find the data stored there again, like they might find a shoebox of old letters in the attic.

Donovan’s interest in the ephemerality of digital data stems from her personal experiences. She studied maths at university and has copies of her handwritten notes. “There’s a point when I started taking digital notes and I can’t find them,” she says with a laugh.

She also had an online diary that she kept in the late 1990s. It’s completely lost now. And she worked on creative projects that no longer survive intact online. When she made them, it felt like she was creating something solid. A film that could be replayed endlessly, for instance. But now her understanding of what digital data is, and how long it might last, has changed.

“It was more like I produced a play, and you got to watch it, and then you just have your memories,” she says.

Thanks to the permanence of stone tablets, ancient books and messages carved into the very walls of buildings by our ancestors, there’s a bias in our culture towards assuming that the written word is by definition enduring. We quote remarks made centuries ago often because someone wrote them down – and kept the copies safe. But in digital form, the written word is little more than a projection of light onto a screen. As soon as the light goes out, it might not come back.

That said, some online data lasts a very long time. There are several examples of websites that are 30 years old or more. And now and again data hangs around even when we don’t want it to. Hence the emergence of the “right to be forgotten”. As tech writer and BBC web product manager Simon Pitt writes in the technology and science publication OneZero, “The reality is that things you want will disappear and things you don’t will be around for forever.”

Someone who aims to redress this balance is Jason Scott. He runs Archive Team, a group dedicated to preserving data, especially from websites that get shut down.

He has presided over dozens of efforts to capture and store information in the nick of time. But often it’s not possible to save everything. When MySpace accidentally deleted an estimated 50 million songs that were once held by the social network, an anonymous academic group gave Archive Team a collection of nearly half a million tracks they had previously backed up.

“What are my children or any potential grandchildren […] going to do with the 400 pictures of my pet that are on my phone?” – Paul Royster

“There were bands for whom MySpace was their only presence,” says Scott. “This entire cultural library got wiped out.”

MySpace apologised for the data loss at the time.

“Once you delete the stuff it just disappears utterly,” says Scott, explaining the significance of proactive efforts to preserve data. He also argues that society has, to an extent, sleepwalked into this situation: “We did not expect the online world was going to be as important as it was.”

It should be clear by now that digital data is, at best, slippery. But how to curb its habit of disappearing?

Scott says he thinks there should be legal or regulatory requirements on companies that give people the option to retrieve their data, for a certain period – say, five years – after an online service is due to shut down. Within that time, anyone who wants their information could download it, or at least pay for a CD copy of it to be sent to them.

Not all of the data we accumulate each day will be worth preserving forever (Credit: Alamy)

Not all of the data we accumulate each day will be worth preserving forever (Credit: Alamy)

A small number of companies have set a good example, he adds. Scott points to Glitch, a 2D online multiplayer game that was removed from the web in 2012, just over a year after it was launched. Its liquidation, in data terms, was “basically perfect”, says Scott. Others, too, have praised the fact that the game’s developers acknowledged players’ frustrations and gave them ample opportunity to download their data from the company’s servers before they were switched off.

Some of the game’s code was even made public and multiple remakes of Glitch, developed by fans, have emerged in the years since. Should this approach be mandatory, though?

“We should have real-time rights, for example to ask for data deletion, data download, or data portability – to take the data from one source to another,” argues Teemu Ropponen at MyData.

He and his colleagues are working on systems designed to make it easier for people to transfer important data about themselves, such as their family history or CV, between services or institutions.

Ropponen argues that there are efforts within the European Union to enshrine this sort of data portability in law. But there is a long way to go.

Even if the technology and regulations were in place, that doesn’t mean that preserving data would become easy overnight. We have so much of it that it is actually quite hard to fathom.

“We should set aside one day of the year when we all go through our data – data preservation day,” – Paul Royster

Around 150 years ago, making a photograph of a family member was a luxury available only to the wealthiest in society. For decades, this more or less remained the case. Even when the technology became more broadly available, it wasn’t cheap to take lots of snaps at once. Photographs became treasured items as a result. Today, smartphone cameras mean it feels like second nature to take literally hundreds or even thousands of photographs every year.

“What are my children or any potential grandchildren […] going to do with the 400 pictures of my pet that are on my phone?” says Paul Royster at the University of Nebraska-Lincoln. “What’s that going to mean to them?”

Royster argues that saving all of our data won’t necessarily be very useful to our descendants. And he disagrees with Scott and Ropponen that laws are the answer. Governments and legislators are often behind the curve on technology issues and sometimes don’t understand the systems they intend to regulate, he says.

Instead, people ought to get into the habit of selecting and preserving the data that is most important to them. “We should set aside one day of the year when we all go through our data – data preservation day,” he says.

Unlike old letters, which are often rediscovered years after being forgotten, online memories are unlikely to last unless you take active steps to preserve them (Credit: Alamy)

Unlike old letters, which are often rediscovered years after being forgotten, online memories are unlikely to last unless you take active steps to preserve them (Credit: Alamy) . Scott also suggests that we should think about what we really want to keep, just in case it gets deleted. “Nobody is thinking of it as the stuff that we have to preserve at all costs, it’s just more data,” he says. “If it’s written, I would print it out.”

There is another option, though. Miia Kosonen at South-Eastern Finland University of Applied Sciences and her colleagues have been working on solutions for storing digital data in archives and national institutions.

“We converted more than 200,000 old emails from former chief editors of Helsingin Sanomat – the largest newspaper in Finland,” she says, referring to a pilot project by Digitalia, a digital data preservation project. The converted emails were later stored in a digital archive.

The US Library of Congress famously keeps a digital archive of tweets, though it has stopped recording every single public tweet and is now preserving them “on a very selective basis” instead.

Could public institutions do some digital data curation and preservation on our behalf? If so, we could potentially submit information to them such as family history and photographs for storage and subsequent access in the future.

Kosonen says that such projects would naturally require funding, probably from the public. Institutions would also be more inclined to retain information that is considered of significant cultural or historical interest.

At the heart of this discussion lies a simple fact: it’s hard for us to know – here in the present – what we, or our descendants, will actually value in the future.

Archival or regulatory interventions could go some way to addressing the ephemerality of data. But that ephemerality is something we will probably always live with, to some extent. Digital data is just too convenient for everyday purposes and there’s little rationale for trying to store everything.

The question has become, at best, one of personal motivation. Today, we decide either to make or not make the effort to save things. Really save them. Not just on the nearest hard-drive or cloud storage device. But also to backup drives or more permanent media, with instructions for how to maintain the storage over time.

This might sound like an exceptionally dry endeavour, but it need not be. A cultural movement might be all it takes to spur us on.

Many audiophiles insist on buying vinyl in an age of music streaming. Booklovers still make the effort to acquire physical copies of their favourite author’s new work. Perhaps we need an analogue-cool movement for preservationists. People who devote themselves to making physical photo albums again. Who go out of their way to write handwritten notes or letters.

These things might just end up being far easier to keep than anything digital, which will likely always require you to trust a system you haven’t built, or a service you don’t own. As Donovan says, “If something is precious, it’s dangerous, I think, to leave it in someone else’s hands.”

By Chris Baraniuk

Source: The online data that’s being deleted – BBC Future

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Chinese Developer Woes Are Weighing on Asia’s Junk Bond Market

https://images.wsj.net/im-189934?width=620&size=1.5

Financial strains among Chinese property developers are hurting the Asian high-yield debt market, where the companies account for a large chunk of bond sales.

That’s widening a gulf with the region’s investment-grade securities, which have been doing well amid continued stimulus support.

Yields for Asia’s speculative-grade dollar bonds rose 41 basis points in the second quarter, according to a Bloomberg Barclays index, versus a 5 basis-point decline for investment-grade debt. They’ve increased for six straight weeks, the longest stretch since 2018, driven by a roughly 150 basis-point increase for Chinese notes.

China’s government has been pursuing a campaign to cut leverage and toughen up its corporate sector. Uncertainty surrounding big Chinese borrowers including China Evergrande Group, the largest issuer of dollar junk bonds in Asia, and investment-grade firm China Huarong Asset Management Co. have also weighed on the broader Asian market for riskier credit.

“Diverging borrowing costs have been mainly driven by waning investor sentiment in the high-yield primary markets, particularly relating to the China real estate sector,” said Conan Tam, head of Asia Pacific debt capital markets at Bank of America. “This is expected to continue until we see a significant sentiment shift here.”

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Such a shift would be unlikely to come without a turnaround in views toward the Chinese property industry, which has been leading a record pace in onshore bond defaults this year.

But there have been some more positive signs recently. Evergrande told Bloomberg News that as of June 30 it met one of the “three red lines” imposed to curb debt growth for many sector heavyweights. “By year-end, the reduction in leverage will help bring down borrowing costs” for the industry, said Francis Woo, head of fixed income syndicate Asia ex-Japan at Credit Agricole CIB.

Spreads have been widening for Asian dollar bonds this year while they’ve been narrowing in the U.S. for both high-yield and investment grade amid that country’s economic rebound, said Anne Zhang, co-head of asset class strategy, FICC in Asia at JPMorgan Private Bank. She expects Asia’s underperformance to persist this quarter, led by Chinese credits as investors remain cautious about policies there.

“However, as the relative yield differential between Asia and the U.S. becomes more pronounced there will be demand for yield that could help narrow the gap,” said Zhang.

Asia

A handful of issuers mandated on Monday for potential dollar bond deals including Hongkong Land Co., China Modern Dairy Holdings Ltd. and India’s REC Ltd., though there were no debt offerings scheduled to price with U.S. markets closed for the July 4 Independence Day holiday.

  • Spreads on Asian investment-grade dollar bonds were little changed to 1 basis point wider, according to credit traders. Yield premiums on the notes widened by almost 2 basis points last week, in their first weekly increase in six, according to a Bloomberg Barclays index
  • Among speculative-grade issuers, dollar bonds of China Evergrande Group lagged a 0.25 cent gain in the broader China high-yield market on Monday. The developer’s 12% note due in October 2023 sank 1.8 cents on the dollar to 74.6 cents, set for its lowest price since April last year

U.S.

The U.S. high-grade corporate bond market turned quiet at the end of last week before the holiday, but with spreads on the notes at their tightest in more than a decade companies have a growing incentive to issue debt over the rest of the summer rather than waiting until later this year.

  • The U.S. investment-grade loan market has surged back from pandemic disruptions, with volumes jumping 75% in the second quarter from a year earlier to $420.8 billion, according to preliminary Bloomberg league table data
  • For deal updates, click here for the New Issue Monitor

Europe

Sales of ethical bonds in Europe have surged past 250 billion euros ($296 billion) this year, smashing previous full-year records. The booming market for environmental, social and governance debt attracted issuers including the European Union, Repsol SA and Kellogg Co. in the first half of 2021.

  • The European Union has sent an RfP to raise further funding via a sale to be executed in the coming weeks, it said in an e-mailed statement
  • German property company Vivion Investments Sarl raised 340 million euros in a privately placed transaction in a bid to boost its real estate portfolio, according to people familiar with the matter

By:

Source: Chinese Developer Woes Are Weighing on Asia’s Junk Bond Market – Bloomberg

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Critics:

The Chinese property bubble was a real estate bubble in residential and/or commercial real estate in China. The phenomenon has seen average housing prices in the country triple from 2005 to 2009, possibly driven by both government policies and Chinese cultural attitudes.

Tianjin High price-to-income and price-to-rent ratios for property and the high number of unoccupied residential and commercial units have been held up as evidence of a bubble. Critics of the bubble theory point to China’s relatively conservative mortgage lending standards and trends of increasing urbanization and rising incomes as proof that property prices can remain supported.

The growth of the housing bubble ended in late 2011 when housing prices began to fall, following policies responding to complaints that members of the middle-class were unable to afford homes in large cities. The deflation of the property bubble is seen as one of the primary causes for China’s declining economic growth in 2012.

2011 estimates by property analysts state that there are some 64 million empty properties and apartments in China and that housing development in China is massively oversupplied and overvalued, and is a bubble waiting to burst with serious consequences in the future. The BBC cites Ordos in Inner Mongolia as the largest ghost town in China, full of empty shopping malls and apartment complexes. A large, and largely uninhabited, urban real estate development has been constructed 25 km from Dongsheng District in the Kangbashi New Area. Intended to house a million people, it remains largely uninhabited.

Intended to have 300,000 residents by 2010, government figures stated it had 28,000. In Beijing residential rent prices rose 32% between 2001 and 2003; the overall inflation rate in China was 16% over the same period (Huang, 2003). To avoid sinking into the economic downturn, in 2008, the Chinese government immediately altered China’s monetary policy from a conservative stance to a progressive attitude by means of suddenly increasing the money supply and largely relaxing credit conditions.

Under such circumstances, the main concern is whether this expansionary monetary policy has acted to simulate the property bubble (Chiang, 2016). Land supply has a significant impact on house price fluctuations while demand factors such as user costs, income and residential mortgage loan have greater influences.

References

Big Ethical Questions about the Future of AI

Artificial intelligence is already changing the way we live our daily lives and interact with machines. From optimizing supply chains to chatting with Amazon Alexa, artificial intelligence already has a profound impact on our society and economy. Over the coming years, that impact will only grow as the capabilities and applications of AI continue to expand.

AI promises to make our lives easier and more connected than ever. However, there are serious ethical considerations to any technology that affects society so profoundly. This is especially true in the case of designing and creating intelligence that humans will interact with and trust. Experts have warned about the serious ethical dangers involved in developing AI too quickly or without proper forethought. These are the top issues keeping AI researchers up at night.

Bias: Is AI fair

Bias is a well-established facet of AI (or of human intelligence, for that matter). AI takes on the biases of the dataset it learns from. This means that if researchers train an AI on data that are skewed for race, gender, education, wealth, or any other point of bias, the AI will learn that bias. For instance, an artificial intelligence application used to predict future criminals in the United States showed higher risk scores and recommended harsher actions for black people than white based on the racial bias in America’s criminal incarceration data.

Of course, the challenge with AI training is there’s no such thing as a perfect dataset. There will always be under- and overrepresentation in any sample. These are not problems that can be addressed quickly. Mitigating bias in training data and providing equal treatment from AI is a major key to developing ethical artificial intelligence.

Liability: Who is responsible for AI?

Last month when an Uber autonomous vehicle killed a pedestrian, it raised many ethical questions. Chief among them is “Who is responsible, and who’s to blame when something goes wrong?” One could blame the developer who wrote the code, the sensor hardware manufacturer, Uber itself, the Uber supervisor sitting in the car, or the pedestrian for crossing outside a crosswalk.

Developing AI will have errors, long-term changes, and unforeseen consequences of the technology. Since AI is so complex, determining liability isn’t trivial. This is especially true when AI has serious implications on human lives, like piloting vehicles, determining prison sentences, or automating university admissions. These decisions will affect real people for the rest of their lives. On one hand, AI may be able to handle these situations more safely and efficiently than humans. On the other hand, it’s unrealistic to expect AI will never make a mistake. Should we write that off as the cost of switching to AI systems, or should we prosecute AI developers when their models inevitably make mistakes?

Security: How do we protect access to AI from bad actors?

As AI becomes more powerful across our society, it will also become more dangerous as a weapon. It’s possible to imagine a scary scenario where a bad actor takes over the AI model that controls a city’s water supply, power grid, or traffic signals. More scary is the militarization of AI, where robots learn to fight and drones can fly themselves into combat.

Cybersecurity will become more important than ever. Controlling access to the power of AI is a huge challenge and a difficult tightrope to walk. We shouldn’t centralise the benefits of AI, but we also don’t want the dangers of AI to spread. This becomes especially challenging in the coming years as AI becomes more intelligent and faster than our brains by an order of magnitude.

Human Interaction: Will we stop talking to one another?

An interesting ethical dilemma of AI is the decline in human interaction. Now more than any time in history it’s possible to entertain yourself at home, alone. Online shopping means you don’t ever have to go out if you don’t want to.

While most of us still have a social life, the amount of in-person interactions we have has diminished. Now, we’re content to maintain relationships via text messages and Facebook posts. In the future, AI could be a better friend to you than your closest friends. It could learn what you like and tell you what you want to hear. Many have worried that this digitization (and perhaps eventual replacement) of human relationships is sacrificing an essential, social part of our humanity.

Employment: Is AI getting rid of jobs?

This is a concern that repeatedly appears in the press. It’s true that AI will be able to do some of today’s jobs better than humans. Inevitably, those people will lose their jobs, and it will take a major societal initiative to retrain those employees for new work. However, it’s likely that AI will replace jobs that were boring, menial, or unfulfilling. Individuals will be able to spend their time on more creative pursuits, and higher-level tasks. While jobs will go away, AI will also create new markets, industries, and jobs for future generations.

Wealth Inequality: Who benefits from AI?

The companies who are spending the most on AI development today are companies that have a lot of money to spend. A major ethical concern is AI will only serve to centralizecoro wealth further. If an employer can lay off workers and replace them with unpaid AI, then it can generate the same amount of profit without the need to pay for employees.

Machines will create wealth more than ever in the economy of the future. Governments and corporations should start thinking now about how we redistribute that wealth so that everyone can participate in the AI-powered economy.

Power & Control: Who decides how to deploy AI?

Along with the centralization of wealth comes the centralization of power and control. The companies that control AI will have tremendous influence over how our society thinks and acts each day. Regulating the development and operation of AI applications will be critical for governments and consumers. Just as we’ve recently seen Facebook get in trouble for the influence its technology and advertising has had on society, we might also see AI regulations that codify equal opportunity for everyone and consumer data privacy.

Robot Rights: Can AI suffer?

A more conceptual ethical concern is whether AI can or should have rights. As a piece of computer code, it’s tempting to think that artificially intelligent systems can’t have feelings. You can get angry with Siri or Alexa without hurting their feelings. However, it’s clear that consciousness and intelligence operate on a system of reward and aversion. As artificially intelligent machines become smarter than us, we’ll want them to be our partners, not our enemies. Codifying humane treatment of machines could play a big role in that.

Ethics in AI in the coming years

Artificial intelligence is one of the most promising technological innovations in human history. It could help us solve a myriad of technical, economic, and societal problems. However, it will also come with serious drawbacks and ethical challenges. It’s important that experts and consumers alike be mindful of these questions, as they’ll determine the success and fairness of AI over the coming years.

By: By Steve Kilpatrick
Co-Founder & Director
Artificial Intelligence & Machine Learning

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Solving Your Online Game Development Challenges At The Edge

The global video games market continues to grow bigger and more competitive, with billions of players who expect fast online experiences. Game development also keeps getting more resource intensive. With AWS you can focus on creating unique experiences, scale to meet new demands easily, and solve latency challenges by deploying multiplayer servers anywhere.

Below you’ll learn more about how AWS Outposts can help you deliver the next great game development and capture a new generation of demanding online players. Read on to discover:

  • Key challenges that multiplayer gaming companies encounter
  • How AWS Outposts helps
  • A use case example of reducing latency

Gaming challenges

As multiplayer game companies look for further growth opportunities, keeping a seamless customer experience is paramount. To achieve this, there are some specific key challenges to address:

Fast and smooth in-game experience

Even if game application servers are deployed in multiple AWS Regions, players in locations far from the server will not experience the same low-latency benefits.

Teams’ competing development priorities

Developers need to be able to focus on developing unique games, not porting applications to multiple internal hardware stacks or managing hardware.

Growing developer demands

As games get bigger and target more platforms, build processes require more compute and storage resources.

How does AWS Outposts help?

With AWS Outposts, game companies can benefit from:

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Plus… Outpost validated partner solution offerings

Protect and enrich the player experience by integrating with Outposts Partner offerings, like Veritas, Pure Storage, Sisense, CyberArk, AppDynamics, ScyllaDB and Confluent, that have been validated on AWS.

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Gaming use cases

Reduce Cloud Gaming Latency

Problem – Game servers are too far from players

You want to give players an immersive experience. But they can’t compete on a level playing field, because latency is preventing them from reacting quickly to in-game events. Players can be vocal about the problem in online communities and if play isn’t smooth and immersive your game’s success could be limited by that.

Solution – Deploy close to players on AWS Outposts

  • You choose the locations
  • Migration is easy – can be moved to Outposts quickly
  • Consistent hybrid experience
  • You can worry less about failures (AWS manages, monitors, and updates your Outposts racks)

Which type of storage do you need?

Amazon EBS

Configure an Outpost up to 55TB in storage tiers. Snapshot and restore capabilities let you increase volume size without any performance impact.

Amazon S3

Now available in an Outpost, with S3 developers can store and retrieve data in the same way they would access or use data in an AWS Region.

Discover more about AWS Outposts for multiplayer gaming

With AWS Outposts developers can deliver responsive multiplayer gaming anywhere in the world and burst through development limits and the complexity associated with existing operations. Outposts are highly suited for this use case and provide the same services, APIs, and tools as in AWS Regions. Take the next steps by reading in our in-depth eBook here.

AWS Infrastructure Solutions

AWS Infrastructure Solutions

AWS infrastructure solutions allow enterprises across all industries the opportunity to bring AWS services closer to where it’s needed, such as on-premises with AWS Outposts, in large metro areas with AWS Local Zones, or at the edge of 5G networks with AWS Wavelength. These solutions offer enterprises the capability to deliver innovative applications and immersive next-generation experiences using AWS cloud services where they need it. Millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies—are using AWS to lower costs, speed time to market, and become more dynamic. To learn more about AWS infrastructure solutions, visit aws.amazon.com.

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Al Jazeera English

The gaming industry’s labour force has had a year of reckoning. The video game industry is richer than the global movie and music industries combined. And it’s still growing. But a series of public scandals in recent years have revealed poor working conditions for the people making the games, as well as a culture that discriminates against women and minorities. Will calls for unionization in the industry take off? The newest episode of Start Here reveals what’s going on behind the gaming screen. Subscribe to our channel http://bit.ly/AJSubscribe Follow us on Twitter https://twitter.com/AJEnglish Find us on Facebook https://www.facebook.com/aljazeera Check our website: http://www.aljazeera.com/

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