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Dr Paul Wright: Swift decision needed to fix horse racing industry

first_img NEGOTIATIONS Last week, the best kept secret in horse racing in Jamaica was officially exposed. There was a statement from the Government that Supreme Ventures was now the preferred bidder in the much ballyhooed divestment of Caymanas Park, the only racetrack in the island. Although everybody at the track knew that Supreme Ventures had won months before, the comments from the vice president of the trainers’ association and the president of the Jamaica Racehorse Owners Association (JROA) reflected sentiments at the track that racing NEEDED divestment. Some of the older (and wiser?) fans and punters at the track were very wary of the announcement, however, as they remembered that there were two previous ‘preferred bidders’ in the planned divestment of racing out of the hands of Government and into the hands of private individuals (or companies) with the knowledge and the money that is so vital in the successful promotion of racing, as the Danny Melville-led Board showed some year s ago. Both bids came to nought. So after the collective sigh of relief from the representatives of the stakeholders in racing, came the return to reality by statements from Paul Hoo, a representative of Supreme Ventures and from lawyers representing the present champion jockey at the track, Shane Ellis. First, Mr Hoo reminded all of us in racing that the title ‘preferred bidder’ only means that negotiations for the divestment will now begin in earnest and the lawyers for Mr Ellis obtained an injunction in the courts that restrained the planned divestment until the promoting company, Caymanas Track Limited (CTL), settled a lawsuit brought by Mr Ellis against the CEO of the track, who made comments (deemed derogatory by Mr Ellis and his lawyers). Those comments were made after Mr Ellis fell from a horse during a race some years ago. So for at least the next 9-12 months the status quo at the track remains – no Board in place and management that has become decidedly worse after the ‘preferred bidder’ official statement. For example, ‘technical difficulties’ is now the official response to queries about race day incidents that reek of incompetence. Last Saturday, a race was held up for at least 15 minutes because of ‘technical difficulties’ at the starting gate. It turned out that the gates “malfunctioned” because of a “lack of power”. This was quickly remedied by the frantic call for an electrician – obviously transported in a van racing from the starting gate to the grandstand area over and over again – to correct a problem that scheduled and regular maintenance checks could have prevented. The first race, on more than one occasion, has been delayed by “technical difficulties” when investigations revealed that a crucial member of the management team was “late” coming to work. Betting terminals at Off Track betting stations are turned on up to one hour late on race days because of “technical difficulties”, which on investigation revealed that crucial operatives “came to work late”. Horses are withdrawn from races because of lameness or illness the day before racing are not declared as late non-starters until a few minutes before the scheduled start of the race, playing havoc with the important exotic wagers of punters whose selection is now transferred to the ‘on time favourite’, which in some case have very little or no chance of winning and therefore depriving the knowledgeable punter from choosing another horse with a more realistic winning chance. I could go on and on. Racing cannot continue like this. The Chinese ambassador has praised the present Prime Minister, Andrew Holness, for his penchant for making “quick decisions”. Racing people are now calling for a swift decision by his Government to try to correct the present promotion of racing. TECHNICAL DIFFICULTIESlast_img read more

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‘Anything is possible’ – Thompson says race execution key to getting national record

first_img POWERING AWAY Despite winning the women’s 100m in a wind-aided 10.71 seconds at Saturday night’s 13th Jamaica International Invitational at the National Stadium, IAAF World Championship 200m silver medallist Elaine Thompson rued not executing a ‘complete race’. The time is not official because the wind reading was +2.4, above the allowable +2.0 mps limit. Thompson, whose 100m PB is 10.84 seconds, believes that with good race execution and ideal conditions, she could better the national 100m mark (10.70 seconds), which is held by her training partner, Olympic and World Champion Shelly-Ann Fraser-Pryce. “Anything is possible, hopefully,” Thompson said of her chances of getting the national record in her post-race interview. Speaking about her race execution, Thompson said: “… Not the first part only, I am working on all of the 100m. My first 30 metres is not the best, so I am trying to work on that more.” Continuing, she said: “The comparison between last year and this year, I mean, last year, I was a collegiate athlete. I am not racing that much this year, but I’ll just keep on training and putting in the work and go out there and deliver.” The 23-year-old’s time was greeted by voracious cheers of approval from the National Stadium crowd. She ran from Lane Four, stamped her class over the final 20 metres and powered from the rest of a competitive field, which included American English Gardner (10.85), who finished second, and Trinidad & Tobago’s Michelle-Lee Ahye (10.98), who placed third. The meet record is 10.86, set by American Carmelita Jeter in 2011. Thompson reiterated that she has been “training really hard and happy to come out victorious”. “It’s a stepping stone for me to see where I’m at, so I have to go home and train harder and see the mistake that I made and see if I can correct it from there,” emphasised the MVP athlete. Meanwhile, Thompson is not sure what sprint event(s) she will do at trials for this summer’s Oympics in Rio de Janeiro, Brazil, but leaves the decision to veteran tactician Stephen Francis. “I am not sure. My coach will decide. My training has been going okay so far, so I’ll just continue doing my best out there at all times.”last_img read more

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John Downey fails in second bail application

first_imgDonegal man John Downey, who stands accused of the murder of two UDR soldiers, has had another bail application refused today.Downey appeared at Belfast Magistrates’ Court, where lawyers made the case that he would qualify for early release if he were to be convicted and handed a two-year sentence for Troubles-related offences, the Belfast Telegraph reports. However, the 67-year-old’s second application was denied, with the prosecution saying that he was unsuitable for bail. His renewed application for bail was first denied in November, when £225,000 in cash and a further £500,000 in equity was proposed as sureties.Downey, who has an address in Creeslough Co. Donegal, is charged with murdering two British soldiers in an IRA bomb attack in Enniskillen in 1972. He was extradited to the UK after handing himself into gardaí in October.Read more at: https://www.belfasttelegraph.co.uk/news/northern-ireland/alleged-ira-bomber-john-downey-denied-bail-for-second-time-38767240.htmlJohn Downey fails in second bail application was last modified: December 11th, 2019 by Staff WriterShare this:Click to share on Facebook (Opens in new window)Click to share on Twitter (Opens in new window)Click to share on LinkedIn (Opens in new window)Click to share on Reddit (Opens in new window)Click to share on Pocket (Opens in new window)Click to share on Telegram (Opens in new window)Click to share on WhatsApp (Opens in new window)Click to share on Skype (Opens in new window)Click to print (Opens in new window)last_img read more

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Giants plan to add former A’s fan favorite at catcher

first_imgSCOTTSDALE–When pitchers and catchers report to the Giants’ complex in Scottsdale on Tuesday, popular clubhouse presence Nick Hundley won’t be joining them.Hundley is moving across the bay to Oakland, but a former A’s catcher will have a chance to replace him in San Francisco. Two-time All-Star Stephen Vogt is expected to finalize a minor league deal with the Giants once he completes a physical on Tuesday.The Associated Press first reported Vogt reached an agreement with the Giants.Vogt had …last_img read more

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The Potential “Holy Shit” Threats Surrounding AI and ML

first_imgRelated Posts Artificial intelligence(AI) and machine learning (ML) are the most viral topics discussed in this age. It has been a big controversy among scientists today, and their benefits to humankind cannot be overemphasized. We need to watch for and understand the potential “holy shit” threats surrounding AI and ML.Who could have imagined that one day the intelligence of machine would exceed that of a human — a moment futurists call the singularity? Well, a renowned scientist (the forerunner of AI), Alan Turing, proposed in 1950 —  that a machine can be taught just like a child. Turing asked the question, “Can machines think?” Turing also explores the answers to this question and others in one of his most read thesis titled — ‘’Computing Machinery and Intelligence.” In 1955, John McCarthy invented a programming language LISP termed “artificial intelligence.” A few years later, researchers and scientists began to use computers to code, to recognize images, and to translate languages, etc. Even back in 1955 people were hoping that they’d one day make computer to speak and think.Great researchers like Hans Moravec (roboticist), Vernor Vinge (sci-fi author), and Ray Kurzweil were thinking in a broader sense. These men were considering when a machine will become capable of devising ways of achieving its goals all alone. Greats like Stephen Hawking warns that when people become unable to compete with advanced AI, “it could spell the end of the human race.”  “I would say that one of the things we ought not to do is to press full steam ahead on building superintelligence without giving thought to the potential risks. It just feels a bit daft,” said Stuart J. Russell, a professor of computer science at the University of California, Berkeley.Here are five possible dangers of implementing ML and AI and how to fix it:1.  Machine learning (ML) models can be biased — since its in the human nature.As promising as machine learning and AI technology is, its model can also be vulnerable to unintended biases. Yes, some people have the perception that ML models are unbiased when it comes to decision making. Well, they are not wrong, but they happen to forget that humans are teaching these machines —  and by nature — we aren’t perfect.Additionally, ML models can also be biased in decision-making as it wades through data. You know that feeling-biased data (incomplete data), down to the self-learning robot. Can a machine lead to a dangerous outcome? Let’s take for instance, you run a wholesale store, and you want to build a model that will understand your customers. So you build a model that is less likely to default on the purchasing power of your distinguish goods. You also have the hope of using the results of your model to reward your customer at the end of the year.So, you gather your customers buying records — those with a long history of good credit scores, and then developed a model.What if a quota of your most trusted buyers happen to run into debt with banks — and they’re unable to find their feet on time? Of course, their purchasing power will plummet; so, what happens to your model? Certainly it won’t be able to predict the unforeseen rate at which your customers will default. Technically, if you then decide to work with its output result at year end, you’ll be working with biased data.Note: Data is a susceptible element when it comes to machine learning, and to overcome data bias — hire experts that will carefully manage this data for you. Also note that no one but you was looking for this data — but now your unsuspecting customer has a record — and you are holding the “smoking gun” so to speak.  These experts should be ready to honestly question whatever notion that exists in the data accumulation processes; and since this a delicate process, they should also be willing to actively look for ways of how those biases might manifest themselves in data. But look what type of data and record you have created.2. Fixed model pattern.In cognitive technology, this is one of the risks that shouldn’t be ignored when developing a model. Unfortunately, most of the developed models, especially those designed for investment strategy, are the victim of this risk.Imagine spending several months developing a model for your investment. After several trials, you still got an “accurate output.” When you try your model with “real world inputs” (data), it gives you a worthless result.Why is it so? This is because the model lacks variability. This model is built using a specific set of data. It only works perfectly with the data with which it was designed.For this reason, safety conscious AI and ML developers should learn to manage this risk while developing any algorithmic models in the future. By inputting all forms of data variability that they can find, e.g., demo-graphical data sets [yet, that is not all the data.]3. Erroneous interpretation of output data could be a barrier.Erroneous interpretation of data output is another risk machine learning might face in the future. Imagine after you’ve worked so hard to achieve good data, you then do everything right to develop a machine. You decided to share your output result with another party — perhaps your boss for review. After everything — your boss’ interpretation is not even close to your own view. He has a different thought process — and therefore a different bias than you do. You feel lousy thinking how much effort you gave for the success. This scenario happens all the time. That’s why every data scientist should not just be useful in building modeling, but also in understanding and correctly interpreting “every bit” of output result from any designed model. In machine learning, there’s no room for mistakes and assumptions — it just has to be as perfect as possible. If we don’t consider every single angle and possibility, we risk this technology harming humankind.Note: Misinterpretation of any information released from the machine could spell doom for the company. Therefore, data scientists, researchers, and whoever involved shouldn’t be ignorant of this aspect. Their intentions towards developing a machine learning model should be positive, not the other way round.4. AI and ML are still not wholly understood by science.In a real sense, many scientists are still trying to understand what AI and ML are all about fully. While both are still finding their feet in the emerging market, many researchers and data scientists are still digging to know more.With this inconclusive understanding of AI and ML, many people are still scared because they believe that there are still some unknown risks yet to be known. Even big tech companies like Google, Microsoft are still not perfect yet. Tay Ai, an artificial intelligent ChatterBot, was released on the 23 March 2016, by Microsoft Corporation. It was released through twitter to interact with Twitter users — but unfortunately, it was deemed to be a racist. It was shut down within 24 hours.Facebook also found that their chatbots deviated from the original script and started to communicate in a new language it created itself. Interestingly, humans can’t understand this newly created language. Weird, right? Still not fixed — read the fine print. Note: To solve this “existential threat,” scientists and researchers need to understand what AI and ML are. Also, they must also test, test, and test the effectiveness of the machine operational mode before it’s officially released to the public.5. It’s a manipulative immortal dictator.A machine continues forever — and that’s another potential danger that shouldn’t be ignored. AI and ML robots cannot die like a human being. They’re immortal. Once they’re trained to do some tasks, they continue to perform and often without oversight.If artificial intelligence and machine learning properties are not adequately managed or monitored — they can develop into an independent killer machine. Of course, this technology might be beneficial to the military — but what will happen to the innocent citizens if the robot cannot differentiate between enemies and innocent citizens?This model of machines is very manipulative. They learn our fears, dislike and likes, and can use this data against us. Note: AI creators must be ready to take full responsibility by making sure that this risk is considered while designing any algorithmic model.Conclusion: Machine learning is no doubt one of the world most technical capabilities with promising real-world business value — especially when merged with big data technology.  As promising it might look — we shouldn’t neglect the fact that it requires careful planning to suitably avoid the above potential threats: data biases, fixed model pattern, erroneous interpretation, uncertainties, and manipulative immortal dictator. Entrepreneur and Online Marketing Consultant, Ejiofor Francis is the Founder of EffectiveMarketingIdeas. He’s highly enthusiastic about all things business, IT and blockchain technology, and he shares informative resources to help businesses and consumers stay informed, safer, and smarter online. Want to say hi? Shoot him an email at francis@effectivemarketingideas.com What it Takes to Build a Highly Secure FinTech … How Data Analytics Can Save Lives AI: How it’s Impacting Surveillance Data Storage Ejiofor FrancisDigital Marketer, Blogger, IT/Technology Copywriter Leveraging Big Data that Data Websites Should T… Tags:#AI#AI Machine Learning#AI risks#data science#design models last_img read more

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Narada tapes case: CBI court rejects SMH Mirza’s bail plea

first_imgA special CBI court on Wednesday rejected the bail plea of suspended IPS officer SMH Mirza, who was arrested by the central agency for corruption in connection with the Narada tapes case, extending his judicial remand till November 26. Mr. Mirza’s counsel pleaded before the Kolkata court that his client is in no manner connected with the scandal but has been in custody for 49 days. He prayed to the court to grant Mr. Mirza bail as there’s been no progress in the case since his arrest. CBI lawyers pleaded that Mr. Mirza’s appeal be rejected as his custodial remand was needed further for interrogation.Mr. Mirza was the Burdwan Superintendent of Police when he was allegedly caught in a sting operation carried out by Mathew Samuel, the editor of Narada news portal, in 2014. He was arrested on September 26 this year and produced before the court, which had initially remanded him to CBI custody for five days. The court had remanded Mr. Mirza to judicial custody for 14 days on September 30 and had extended it twice. The Narada tapes surfaced ahead of the 2016 West Bengal Assembly polls. In the tapes, persons resembling senior Trinamool Congress leaders and Mr. Mirza were seen accepting money from representatives of a fictitious company in return for favours. The Calcutta High Court had ordered a CBI probe into the Narada sting operation case on a public interest litigation, which sought an impartial investigation into the footage.last_img read more