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Top 3 Price Prediction Bitcoin, Ethereum, XRP: Bears take over and draw a bloody moon – FXStreet

January 24, 2020 | Author: admin

Cryptographer and computer scientist Nick Szabo, has presented in his Twitter account a study on the "risk-benefit" ratio of different assets. The study used a Sharpe Ratio over four years Hodl period.

According to this study, Bitcoin is the best positioned, maintaining an average ratio of 3 in the last four years. Behind them are the US stocks, with an average ratio of 2, and gold, which has gone from the last positions in 2016 to the third in the 2020 ratio.

The worst placed asset category is emerging currencies, which with an average ratio of -2 lags far behind the others.

The crypto board reaches the end of the week with the bears securing the market control they gained yesterday in mid-session.

The structure of the moving averages already indicated that the upward turning process that began on January 10th was going to be quite time-consuming. The magnitude of the downward movements in the second half of 2019 had separated the moving averages a lot.

ETH/BTC is trading at the price level of 0.01895and is down by -1.65%. On the 4-hour chart, the spot price is piercing the EMA50. If Ethereum loses this support, the drop will accelerate to the 0.0185 level.

Above the current price, the first resistance level is at 0.0197, then the second at 0.0200 and the third one at 0.0205.

Below the current price, the first support level is at 0.0185, then the second at 0.0185 and the third one at 0.0182.

The MACD on the 4-hour chart is supported directly by the indicator's zero levels. The moving averages are sloping downward and are moving away from it, suggesting an acceleration of the trend.

The DMI on the 4-hour chart shows the bearish-bought pair in equilibrium. Both sides of the market are above the ADX line, a setup that facilitates violent resolutions.

BTC/USD is currently trading at $8243and confirms the loss of support at $8400. The EMA50 and SMA100 averages continue to fall and forecast that the end of the downtrend could be on the first week of February.

Above the current price, the first resistance level is at $8400, then the second at $8500 and the third one at $8800.

Below the current price, the first support level is at $8200, then the second at $8000 and the third one at $7900.

The MACD on the 4-hour chart is losing its downward slope, indicating the end of the impulse phase of the movement. The terminal phase can easily take the price below $8000.

The DMI on the 4-hour chart confirms the end of the bearish momentum phase. Bears are preparing to drill down the ADX line. The bulls are very reactive to any upward movement and break the downward trend.

ETH/USD is currently trading at $156.09after finding support at the SMA100. The support point coincides with the 38.2% level of the Fibonacci retracement system and the same system indicates that the 50% level at $150 is very likely to be visited.

Above the current price, the first resistance level is at $161, then the second at $165 and the third at $170.

Below the current price, the first support level is at $155, then the second at $150 and the third one at $143 (61.8% level of the Fibonacci retracement system).

The MACD on the 4-hour chart is increasing its openness and is tilting further down, so we can expect an acceleration of the price's decline.

The DMI on the 4-hour chart shows that the bearish trend is increasing. The bulls are not reacting and continue to lose strength.

XRP/USD is currently trading at $0.215 and accelerating the downward movement that began this week. The current price coincides with the 50% level of the Fibonacci retracement system. The next support, according to this tool, is at the 0.205 price level, 61.8% of the Fibonacci retracement system.

Above the current price, the first resistance level is at $0.218, then the second at $0.223 and the third one at $0.235.

Below the current price, the first support level is at $0.205, then the second at $0.20 and the third one at $0.19.

The MACD on the 4-hour chart shows an acceleration of the downward movement. The MACD on the 4-hour chart shows an acceleration of the downward movement.

The DMI on the 4-hour chart shows that the bearish trend is increasing and the bearish momentum is strong. The bulls are not reacting and continue to lose momentum.

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Bitcoin ‘to increase 98% in value by end of year’ – Netimperative

January 24, 2020 | Author: admin

Bitcoin could nearly double in price by years end, according to a panel of fintech leaders convened by financial comparison website Finder.

The panel of 13 in Finders Cryptocurrency report suggest Bitcoin could be worth as much as USD$8,589 by March 31 and USD$14,275 by the end of the year.Key findings:

Bitcoin value to increase 19% by March 31 and 98% by years end, according to fintech panellists82% believe the halvening will boost the price of BitcoinPanel positive on Bitcoin, Ethereum and Tezos / most negative on TRON, EOS, and Litecoin77% say stable coins, such as Facebooks Libra, threaten national monetary sovereignty82% of panellists, including founder of Draper Associates, Tim Draper, believe the halvening will boost the price of Bitcoin.It [Bitcoin] becomes more valuable as the usage and costs to make it go up, he said.

Fred Schebesta, Co-founder of Finder and HiveEx, believes Bitcoin will hit $22,000 by years end.

If we see a continued consistency and no prolonged downward manipulation, I forecast Bitcoin will almost triple by the end of 2020.

Managing Director of Digital Capital Management, Ben Richie, who had the highest end-of-year price prediction ($34,500), said geopolitical and economic uncertainty will boost Bitcoins value.

investors will look to some alternative assets to shield from these events, and cryptocurrencies is likely to be a benefactor, he said.

Overall the panel was net positive on just three cryptocurrencies, Bitcoin, Ethereum and Tezos. It was most negative on TRON, EOS and Litecoin.

University of Canberras Dr. John Hawkins was negative on all 11 cryptocurrencies.

None of these cryptocurrencies have made any substantial progress in becoming payments instruments and may face stronger rivals in 2020 such as Libra and then central bank cryptocurrencies, he said.

Despite speculation Facebooks Libra wont eventuate, 85% of panellists, including Dr. at the University of New South Wales, Elvira, Soji, think it will launch.

It will launch in a very limited way, and governments will look much more seriously into central bank digital cash, she said.

The report also reveals the majority of panellists (77%) believe stable coins, such as Facebooks Libra, threaten the monetary sovereignty of nations.

Ritchie noted that we are only now really starting to experiment with money, and the threat to nations will be a bi-product of their lack of adoption to change.

Technologist Joseph Raczynski went as far as to say there is a bit of an arms race to develop a widely held crypto that can be used around the world.

You can view the full report here

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Top 3 Price Prediction Bitcoin, Ethereum, XRP: Set for a dive before the next big bull market – FXStreet

January 24, 2020 | Author: admin

Crypto goes mainstream the cryptoverse is spreading to people's daily lives.

The first initiative comes from WhatsApp. Users of Facebooks popular instant messaging application will be able to exchange Ether among themselves and other tokens that function over the ERC20 protocol.

The second thing to note is a statement from a former PayPal executive, Dan Schatt, in which he states that stablecoins can facilitate the acceptance of Blockchain technology by the traditional financial system. Stablecoins may function as virtual bridges between the two systems the fiduciary and the decentralized can be the gateway to the technology for the general public.

Despite this potential, Vodafone withdrew from Libra's stablecoin project on Wednesday, although it said it would continue to support it with a less prominent position.

The ETH/BTC cross is currently trading at the price level of 0.01938. During the Asian session, Ether lost strength against Bitcoin, something that usually happens when the market falls.

But the fall has no technical impact at the moment, and the previous scenario remains intact.

The EMA50 average loses a bit of tilt and is already heading towards the projection area of the SMA100 and 200.

Above the current price, the first resistance level is at 0.0192, then the second at 0.020 and the third one at 0.0217.

Below the current price, the first support level is at 0.01905, then the second at 0.01877 and the third one at 0.0185.

The MACD on the 4-hour chart is tilting downward and looking for support in the neutral zone of the indicator. At that point, the path taken by the moving averages will indicate the market's tone for the coming weeks.

The DMI on the 4-hour chart shows a small advantage for bears over bulls, but not enough to give the selling side a victory.

BTC/USD is currently trading at $8,403and is losing support of the EMA50. The short term exponential average loses its upward profile and seems to be heading towards the SMA100 level at $8,400.

Above the current price, the first resistance level is at $8,600, then the second at $8,800 and the third one at $9,150.

Below the current price, the first support level is at $8,500, then the second at $8,400 and the third one at $8,200.

The MACD on the 4-hour chart is heading back down, suggesting a bearish test that could drag the price down to $7,800 in the worst-case scenario.

The DMI on the 4-hour chart shows that despite the declines, bears are losing strength while bulls are gaining it. This behavior is divergent with the price and should keep us alert to the chart and flexible to act in case of a sudden change in direction.

ETH/USD is currently trading at $162.6and is trading below the EMA50 for the first time since the 13th.

Moving averages continue to trend higher, although the short term exponential is beginning to lose momentum.

Above the current price, the first resistance level is at $167, then at $170 and the third one at $180.

Below the current price, the first support level is at $160, then the second at $155 and the third one at $151.5.

The MACD on the 4-hour chart is sloping lower and is already moving in the neutral zone of the indicator. The MACD on the daily chart is sloping lower and is already moving in the neutral zone. How the current situation will be resolved, either above or below the neutral zone, will determine the development of ETH/USD in the coming days.

The DMI on the daily chart shows bears taking advantage of the bullish trend, although both sides of the market are moving above the ADX line. This setup is conducive to sudden changes in market control.

XRP/USD is currently trading at $0.2261and has lost all support from the EMA50 on the 4-hour chart. The exponential moving average is curving downward, and the SMA100 is losing its upward slope, which could signal a wide range of downward movement.

Above the current price, the first resistance level is at $0.2317, then the second at $0.2375 and the third one at $0.2538.

Below the current price, the first support level is at $0.224, then the second at $0.217 and the third one at $0.2100.

The MACD on the 4-hour chart is sloping downward, indicating that the bearish trend is coming to an end. The signal is harmful for the price and suggests a drop in the next few days.

The DMI on the 4-hour chart shows that bears are taking advantage of the bullish trend. Both sides of the market are holding above the ADX line, which would allow for a quick change of scenery and price direction.

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Interim proprietary injunction granted over bitcoin cyber extortion payment – Data Protection Report

January 24, 2020 | Author: admin

An interim proprietary injunction has been granted by the English High Court over a bitcoin ransom payment paid to a third-party wallet.

The case was brought by an English insurer (requesting anonymity) against four defendants, consisting of unknown cyber-extortionists (as well as three other parties who respectively hold and/or trade Bitcoins). The claim related to a customer of the Insurer whose data and systems had been encrypted and bitcoin ransom payment demanded.

After some negotiation, the Insurer agreed to pay the ransom (equal to $950,000) in return for the decryption tool. Following the payment of the ransom and the provision of the decryption tool, further investigations were undertaken on behalf of the insurer as to the destination of the ransom with the ultimate aim of recovering the Bitcoins by way of a restitutionary or equitable remedy.

Whilst some of the Bitcoins were transferred into fiat currency, a substantial proportion of the Bitcoins (96) were transferred to a specific address; this address is linked to the exchange known as Bitfinex, operated by the third and fourth defendants. The insurer sought a proprietary injunction over those Bitcoins, as the initial step in looking to recover them via the courts.

The judge was satisfied that the test for a proprietary injunction over the Bitcoins against each of the four defendants was satisfied. A fundamental element of the decision was the conclusion that crypto assets, such as Bitcoin, are property for the purposes of English law and therefore can be the subject-matter of a proprietary injunction.

While historically it has been very difficult to recover ransom payments, the case highlights the potential for corporations to recover these payments via the courts (or, at the very least, to obtain interim relief in respect of them). The decision should certainly be borne in mind by any corporations who become the subject of a targeted and substantial ransom demand and in circumstances where the ransom is paid and is subsequently traceable.

Given the typical speed in which ransom crypto assets are transferred / dissipated, in order to increase any potential for the recovery of such assets, it would be advisable for those considering making such an application, to act with expediency.

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So Is an AI Winter Really Coming This Time? – Walter Bradley Center for Natural and Artificial Intelligence

January 24, 2020 | Author: admin

AI has fallen from glorious summers into dismal winters before. The temptation to predict another such tumble recurs naturally. So that is the question the BBC posed to AI researchers: Are we on the cusp of an AI winter:

The 10s were arguably the hottest AI summer on record with tech giants repeatedly touting AIs abilities.

AI pioneer Yoshua Bengio, sometimes called one of the godfathers of AI, told the BBC that AIs abilities were somewhat overhyped in the 10s by certain companies with an interest in doing so.

There are signs, however, that the hype might be about to start cooling off.

I keep up with this kind of thing. The answer is: Yes, and no. AI did surge past milestones during the 2010s that it had not been expected to cross for many more years:

2011 IBMs Watson wins at Jeopardy! IBM Watson: The inside story of how the Jeopardy-winning supercomputer was born, and what it wants to do next (Tech Republic, September 9, 2013)

2012 Google unveils a deep learning systems that recognized images of cats

2015 Image recognition systems outperformed humans in the ImageNet challenge

2016 AlphaGo defeats world Go champion Lee Sedol: In Two Moves, AlphaGo and Lee Sedol Redefined the Future (Wired, March 16, 2016)

2018 Self-driving cars hit the road as Googles Waymo launched (a very limited) self-driving taxi service in Phoenix, Arizona

But other headlines during the period have been less heeded:

Despite High Hopes, Self-Driving Cars Are Way in the Future (2019)

The Next Hot Job: Pretending to Be a Robot (2019)

Boeings Sidelined Fuselage Robots: What Went Wrong? (2019)

Self-driving cars: Hype-filled decade ends on sobering note (2019)

Tesla driver killed in crash with Autopilot active, NHTSA investigating (2016)

Dont fall for these 3 myths about AI, machine learning (2018)

A Sobering Message About the Future at AIs Biggest Party (2019)

And so on.

So which is it? AI Winter or Robot Overlords? I suggest neither. And so do active researchers.

Gary Marcus, an AI researcher at New York University, said: By the end of the decade there was a growing realisation that current techniques can only carry us so far.

He thinks the industry needs some real innovation to go further.

There is a general feeling of plateau, said Verena Rieser, a professor in conversational AI at Edinburgh[s Heriot Watt University.

One AI researcher who wishes to remain anonymous said were entering a period where we are especially sceptical about AGI.

Recent AI developments, notably those lumped under the rubric of Deep Learning have advanced the state-of-the-art in machine learning. Lets not forget that prior efforts, such as the poorly named Expert Systems, had faded because, well, they werent expert at all. Deep Learning systems, as highly flexible pattern matchers, will endure.

What is not coming is the long-predicted AI Overlord, or anything that is even close to surpassing human intelligence. Like any other tool we build, AI has its place when it amplifies and augments our abilities.

Just as tractors and diggers have not led to legions of people who no longer use their arms, the latest advances in AI will not lead to human serfs cowering before beneath an all-intelligent machine. If anything, AI will require more from us, not less, because how we choose to use these tools will make an increasingly stark difference between benefit and ruin.

As Samin Winiger, a former AI research at Google says, What we called AI or machine learning during the past 10-20 years, will be seen as just yet another form of computation

Machines are tool in the toolbox, not a replacement for minds. An AI winter would only be coming if we forgot that.

Here are some of Brendan Dixons earlier musings on the concept of an AI Winter:

Just a light frost? Or an AI winter? Its nice to be right once in a whilecheck out the evidence for yourself

and

AI WinterIs Coming:Roughly every decade since the late 1960s has experienced a promising wave of AI that later crashed on real-world problems, leading to collapses in research funding.

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What is Machine Learning? | Types of Machine Learning …

January 23, 2020 | Author: admin

Machine learning is sub-categorized to three types:

Supervised Learning Train Me!

Unsupervised Learning I am self sufficient in learning

Reinforcement Learning My life My rules! (Hit & Trial)

Supervised Learning is the one, where you can consider the learning is guided by a teacher. We have a dataset which acts as a teacher and its role is to train the model or the machine. Once the model gets trained it can start making a prediction or decision when new data is given to it.

The model learns through observation and finds structures in the data. Once the model is given a dataset, it automatically finds patterns and relationships in the dataset by creating clusters in it. What it cannot do is add labels to the cluster, like it cannot say this a group of apples or mangoes, but it will separate all the apples from mangoes.

Suppose we presented images of apples, bananas and mangoes to the model, so what it does, based on some patterns and relationships it creates clusters and divides the dataset into those clusters. Now if a new data is fed to the model, it adds it to one of the created clusters.

It is the ability of an agent to interact with the environment and find out what is the best outcome. It follows the concept of hit and trial method. The agent is rewarded or penalized with a point for a correct or a wrong answer, and on the basis of the positive reward points gained the model trains itself. And again once trained it gets ready to predict the new data presented to it.

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Vectorspace AI Datasets are Now Available to Power Machine Learning (ML) and Artificial Intelligence (AI) Systems in Collaboration with Elastic -…

January 23, 2020 | Author: admin

SAN FRANCISCO, Jan. 22, 2020 /PRNewswire/ -- Vectorspace AI (VXV) announces datasets that power data engineering, machine learning (ML) and artificial intelligence (AI) systems. Vectorspace AI alternative datasets are designed for predicting unique hidden relationships between objects including current and future price correlations between equities.

Vectorspace AI enables data, ML and Natural Language Processing/Understanding (NLP/NLU) engineers and scientists to save time by testing a hypothesis or running experiments faster to achieve an improvement in bottom line revenue and information discovery. Vectorspace AI datasets underpin most of ML and AI by improving returns from R&D divisions of any company in discovering hidden relationships in drug development.

"We are happy to be working with Vectorspace AI based on their most recent collaboration with us based on the article we published titled 'Generating and visualizing alpha with Vectorspace AI datasets and Canvas'. They represent the tip of the spear when it comes to advances in machine learning and artificial intelligence. Our customers and partners will certainly benefit from our continued joint development efforts in ML and AI," Shaun McGough, Product Engineering, Elastic.

Increasing the speed of discovery in every industry remains the aim of Vectorspace AI, along with a particular goal which relates to engineering machines to trade information with one another, connected to exchanging and transacting data in a way that minimizes a selected loss function. Data vendors such as Neudata.co, asset management companies and hedge funds including WorldQuant, use Vectorspace AI datasets to improve and protect 'alpha'.

Limited releases of Vectorspace AI datasets will be available in partnership with Amazon and Microsoft.

About Vectorspace AI (vectorspace.ai)

Vectorspace AI focuses on context-controlled NLP/NLU (Natural Language Processing/Understanding) and feature engineering for hidden relationship detection in data for the purpose of powering advanced approaches in Artificial Intelligence (AI) and Machine Learning (ML). Our platform powers research groups, data vendors, funds and institutions by generating on-demand NLP/NLU correlation matrix datasets. We are particularly interested in how we can get machines to trade information with one another or exchange and transact data in a way that minimizes a selected loss function. Our objective is to enable any group analyzing data to save time by testing a hypothesis or running experiments with higher throughput. This can increase the speed of innovation, novel scientific breakthroughs and discoveries. For a little more on who we are, see our latest reddit AMA on r/AskScience or join our 24 hour communication channel here. Vectorspace AI offers NLP/NLU services and alternative datasets consisting of correlation matrices, context-controlled sentiment scoring, and other automatically engineered feature attributes. These services are available utilizing the VXV token and VXV wallet-enabled API. Vectorspace AI is a spin-off from Lawrence Berkeley National Laboratory (LBNL) and the U.S. Dept. of Energy (DOE). The team holds patents in the area of hidden relationship discovery.

SOURCE Vectorspace AI

vectorspace.ai

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Red Hat Survey Shows Hybrid Cloud, AI and Machine Learning are the Focus of Enterprises – Computer Business Review

January 23, 2020 | Author: admin

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The data aspect in particular is something that we often see overlooked

Open source enterprise software firm Red Hat now a subsidiary of IBM have conducted its annual survey of its customers which highlights just how prevalent artificial intelligence and machine learning is becoming, while a talent and skill gap is still slowing down companies ability to enact digital transformation plans.

Here are the top three takeaways from Red Hats customer survey;

When asked to best describe their companies approach to cloud infrastructure 31 percent stated that they run a hybrid cloud, while 21 percent said their firm has a private cloud first strategy in place.

The main reason cited for operating a hybrid cloud strategy was the security and cost benefits it provided. Some responders noted that data integration was easier within a hybrid cloud.

Not everyone is fully sure about their approach yet, as 17 percent admitted they are in the process of establishing a cloud strategy, while 12 percent said they have no plans at all to focus on the cloud.

When it comes to digital transformation there has been a notable rise in the amount of firms that undertaken transformation projects. In 2018; under a third of responders (31 percent) said they were implementing new processes and technology, this year that number has nearly doubled as 58 percent confirm they are introducing new technology.

Red Hat notes that: The drivers for these projects vary. And the drivers also vary by the role of the respondent. System administrators care most about simplicity. IT architects focus on user experience and innovation. For managers, simplicity, user experience, and innovation are all tied for top priority. Developers prioritize innovationwhich, overall, was cited as the most important reason to do digital transformation projects.

However, one in ten surveyed said they are facing a talent and skillset gap that is slowing down the pace at which they can transform their business. The skillset is being made worse by the amount of new technologies that are being brought to market such as artificial intelligence, machine learning and containerisation, the use of which is expected to grow significantly in the next 24 months.

Artificial intelligence, machine learning models and processes is the clear emerging technology for firms in 2019, as 30 percent said that they are planning to implement an AI or ML project within the next 12 months.

However, enterprises are worried about the compatibility and complexity of implementing AI or ML, with 29 percent stating they are worried about evolving software stacks.

One in five (22 percent) responders are worried about getting access to the right data. The data aspect in particular is something that we often see overlooked; obtaining relevant data and cleansing or transforming it in ways that its a useful input for models can be one of the most challenging aspects of an AI project, Red Hat notes.

Red Hats survey was created by compiling 876 qualified responses from Red Hat customers during August and September of 2019.

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Learning that Targets Millennial and Generation Z – HR Exchange Network

January 23, 2020 | Author: admin

Both Millennials and Generation Z can be categorized as digital natives. The way in which they learn reflects that reality. From a learning perspective, a companys learning programs must reflect that also.

Utilizing technologies such as microlearning, which is usually delivered with mobile technology, or machine learning to can engage these individuals in the way they are accustomed to consuming information.

Microlearning is delivering learning in bite-sized pieces. It can take many different forms such an animation or a video. In either case, the information is delivered in a short amount of time; in as little as two to three minutes. In most cases, micro-learning happens on a mobile device or tablet.

When should micro-learning be used?

Think of it as a way to engage employees already on the job. It can be used to deliver quick bits of information that will become immediately relevant to their daily responsibilities. To be more pointed, microlearning is the bridge between formal training and application. At least one study shows after six weeks following a formal training, 85% of the content consumed will have been lost. Microlearning can deliver that information in the interim and can be used at the moment of application.

Microlearning shouldnt be used to replace formal training, but rather as a compliment which makes it perfect for developing and retaining high-quality talent.

Amnesty International piloted a microlearning strategy to launch its global campaign on Human Rights Defenders. The program used the learning approached to build a culture of human rights. It allowed Amnesty to discuss human rights issues in a quick, relevant, and creative manner. As such, learners were taught how to talk to people in everyday life about human rights and human rights defenders.

WEBINAR: L&Ds Role in Enabling the Future of Work with a Skills Focused Strategy

Dell has also used the strategy to implement a digital campaign to encourage 14,000 sales representatives around the world to implement elements of its Net Promoter Score methodology. Using mobile technology and personal computers, the company was able to achieve 11% to 19% uptake in desire among sales reps globally.

Machine learning can also be used as a strategy. Machine learning, which is a branch of artificial intelligence, is an application that provides systems the ability to automatically learn and improve from experience without being programmed to do so.

For the purpose of explanation, the example of an AI-controlled multiple-choice test is relevant. If a person taking the test marked an incorrect answer, AI would then give them a question a bit easier to answer. If the question was answered wrong again, AI would follow with a question lower in difficulty level. When the student began to answer questions correctly, the difficulty of the questions would increase. Similarly, a person answering questions correctly would continue to get more difficult questions. This allows the AI to determine what topics the student understands least. In doing so, learning becomes personalized and specific for the student.

But technology isnt the sole basis for disseminating information. Learning programs should also focus on creating more experience opportunities that offer development in either leadership or talent. Those programs should also prioritize retention. Programs such as mentoring and coaching are great examples.

Dipankar Bandyopadhyay led this charge when he was the Vice President of HR Global R&D and Integration Planning Lead Culture & Change Management for the Monsanto Company. Monsanto achieved this through itsGlobal Leadership Program For Experienced Hires.

A couple of years ago, we realized we had a need to supplement our talent pipeline, essentially in our commercial organization and businesses globally really building talent for key leadership roles within the business, which play really critical influence roles and help drive organizational strategy in these areas. With this intention, we created Global Commercial Emerging Leaders Program, Bandyopadhyay said. Essentially, what it does is focus on getting external talent into Monsanto through different industry segments. This allows us to broaden our talent pipeline, bringing in diverse points of view from very different industry segments (i.e., consumer goods, investment banking, the technology space, etc.) The program selects, onboards, assimilates and develops external talent to come into Monsanto.

Microlearning and machine learning are valuable in developing the workforce, but they are not the only ones available. Additionally, its important to note an organization cant simply provide development and walk away. There has to be data and analysis that tracks employee learning success. There also needs to be strategies in place to make sure workers are retaining that knowledge. Otherwise, it is a waste of money.

NEXT: How L&D Can Help Itself

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Iranian chess referee Shohreh Bayat remains scared to return home to her family over headscarf controversy – CNN International

January 23, 2020 | Author: admin

Currently the chief adjudicator at the Women's World Chess Championship held in Russia and China, Shohreh Bayat says she fears arrest after a photograph of her was taken during the event and was then circulated online in Iran.

"They are very sensitive about the hijab when we are representing Iran in international events and even sometimes they send a person with the team to control our hijab," Bayat told CNN Sport in a phone interview Tuesday.

Bayat said she had been wearing a headscarf at the tournament but that certain camera angles had made it look like she was not.

"If I come back to Iran, I think there are a few possibilities. It is highly possible that they arrest me [...] or it is possible that they invalidate my passport," added Bayat.

"I think they want to make an example of me."

'A very hard situation'

The photographs were taken at the first stage of the chess championship in Shanghai, China, but Bayat has since flown to Vladivostok, Russia, for the second leg between Ju Wenjun and Aleksandra Goryachkina.

She was left "panicked and shocked" when she became aware of the reaction in Iran after checking her phone in the hotel room.

The 32-year-old said she felt helpless as websites reportedly condemned her for what some described as protesting the country's compulsory law.

Subsequently, Bayat has decided to no longer wear the headscarf.

"I'm not wearing it anymore because what is the point? I was just tolerating it, I don't believe in the hijab," she added.

"People must be free to choose to wear what they want, and I was only wearing the hijab because I live in Iran and I had to wear it. I had no other choice."

Bayat says she sought help from the country's chess federation. She says the federation told her to post an apology on her social media channels.

She agreed under the condition that the federation would guarantee her safety but she said they refused.

"My husband is in Iran, my parents are in Iran, all my family members are in Iran. I don't have anyone else outside of Iran. I don't know what to say, this is a very hard situation," she said.

CNN contacted the Iranian Chess Federation on Tuesday but has yet to receive a response.

FIDE, the international federation for chess, has provided support to Bayat saying it leaves "total freedom to the individual" when it comes to religious symbols or clothing.

However, due to the law being enforced by the Iranian government, FIDE said the situation escapes its influence.

"In FIDE we respect all cultures, but above everything, we respect the individual's freedom of choice," FIDE said in a statement sent to CNN.

"And it is solely a decision of Ms. Bayat: wearing or not the headscarf is ultimately her choice, which we will duly respect as it is in no way contradicts FIDE statutes.

"She is a great professional, one of our best international arbiters and the first woman arbiter in Asia to reach the highest category in her field.

"We regret that she finds herself in this situation, and she will have our support whatever she does."

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Iranian chess referee Shohreh Bayat remains scared to return home to her family over headscarf controversy - CNN International

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