– Minister Bulkan silentIn clear violation of the Municipal and District Councils Act, Chapter 28:01, Linden Mayor Carwyn Holland on Thursday decided to unilaterally send Town Clerk Jenella Bowen on administrative leave pending the outcome of an investigation, which is before Communities Minister Ronald Bulkan. Only the Communities Minister in the absence of a Local Government Commission is vested with the power to make that decision.Holland and the Linden Mayor and Town Council (LMTC) had passed two no-confidence motions against Bowen and subsequently wrote Minister Bulkan requesting she be removed. But Minister Bulkan is still to make a decision, which seemingly angered Holland, prompting him to decide to take his own action against the Town Clerk.Linden Town Clerk Jenella BowenGuyana Times has seen a letter dated October 6, 2016 that Holland wrote to Bowen, instructing that she proceed on administrative leave with immediate effect until the conclusion of “the hearing”.“Please be informed that the Ministry of Communities has reviewed the Council’s recommendation and granted no objection,” the letter copied to Communities Ministry Permanent Secretary Emile McGarrel and the LMTC Personnel Officer stated.It went on to highlight that the LMTC proceeded in accordance with the Municipal and District Councils Act, Chapter 28:0, Section 8 A, Subsection G, which states that the Council shall “ensure that the municipality is managed in a professional and competent manner by a qualified Town Clerk” and Section 8 A, Subsection H, which states that the Council “shall perform any other duties or functions imposed on the Council by this or any other law or by the Council”. Subsequently, the Mayor; his deputy, Waneka Arrindell and two senior Police Officers reportedly showed up at the home of the Town Clerk and demanded that she hand over all of the Council’s belongings to them.However, nowhere in the cited act is the Council given the authority to discipline or remove from office the Town Clerk.When contacted, Bowen told Guyana Times that she made attempts to contact Minister Bulkan, but those attempts were unsuccessful; however, she was able to speak with Permanent Secretary McGarrel who advised that she comply with the instructions of the Council.McGarrel confirmed this to Guyana Times , but stated that his advice was to defuse any possible “physical” confrontation. He declined to answer any other question on the issue.Efforts to contact Minister Bulkan proved futile, as calls to his office and mobile phones went unanswered. But a call to his residence was answered and after a prolonged delay, Guyana Times was told he was not at home at that time.Bowen said she has since sought legal advice on the way forward, but could not say if she would report for duty today.The Mayor’s action was deemed unconstitutional, since Section 118 of the Municipal and District Councils Act, Chapter 28:01 clearly states that in the absence of a Local Government Commission, the Communities Minister holds the power to appoint, discipline and disappoint any Local Government Officer.Section 120 of the Act states; “The power to exercise disciplinary control over Local Government Officers (including the power to remove them from office) shall be exercised by the Commission or other person or authority in whom such power is vested under Section 118 or Section 119 in accordance with any rules pertaining to discipline made by the Commission under Section 114.”Section 121 adds that where a Local Government Officer is disciplined, including removal from office by anyone other than the Commission or its designate, the officer can appeal that decision, which the Council or its designate can confirm, set aside or vary any finding on such persons or authority and to confirm, quash or vary any penalty awarded.Former Attorney General and Legal Affairs Minister Anil Nandlall, in an invited comment on Thursday evening, said that Town Clerks, like Regional Executive Officers (REOs), are creatures of the Minister and it is only him who can discipline or dismiss them.He said what was playing out at the Linden municipality was purely authoritarian action by the Mayor and his gang.“Again we are witnessing authoritarianism and a clear violation of the rule of law. The municipality has no authority to discipline or dismiss the Town Clerk: the Town Clerk is a creature of the Minister,” Nandlall, a respected lawyer, opined.He said the actions by Holland and others in Linden and the silence of Bulkan may very well be a sign of the Minister’s weak leadership skills.The spat between Bowen and several Councillors, including Holland and Arrindell, began after she accused the Mayor and Deputy Mayor of spending over $500,000 on travel expenses from the already depleted coffers of the Town Council.The Linden Town Council has not met in more than two months and when contacted last week, Holland told Guyana Times that he was unable to get a quorum for the meetings as Councillors were anxiously awaiting Minister Bulkan’s ruling on the Town Clerk.
AD Quality Auto 360p 720p 1080p Top articles1/5READ MOREPettersson scores another winner, Canucks beat Kings “I am grateful that I work with supportive, thoughtful, intelligent people who like to have fun.” “I totally believe in focusing on the positive, and that’s why I enjoy so much my volunteer work. Giving without expecting anything in return is so fulfilling and gratifying, and it always comes back multiplied.” “I am very grateful to have a great job working for a terrific company that truly cares about my well-being, my professional growth and my overall happiness. I am grateful to work with a wonderful team, and grateful that the rest of the people in our office are wonderful, too. I truly enjoy coming to work every day.” “I’m thankful because the people I work with have become like a second family.” “My job allows me to help others, and that’s truly gratifying. I am thankful to be able to make a living being of service.” Today is a day to spend time with friends and family, to eat a bountiful feast, and maybe watch some football. It’s also a day to give thanks. While most of us are grateful for having a day off, we also should take the time to be thankful for the job we are privileged to have. I asked people I know to think about what they are thankful for when it comes to their jobs. Here’s what they had to say: “I am fortunate to work from a home office and not have to commute. I give thanks for that every time I have to venture out on the freeway!” “I have to be honest – my job pays really well, so I am thankful for that. And gratefully, I enjoy it, too.” “I spent a lot of time in college (and paid a lot in student loans) so I am thankful to finally be working in my chosen career, and thankful that it’s as fun as I’d hoped it would be.” “I’m thankful to have a job! Truthfully, whenever I pass the homeless on the street, I am appreciative that someone has put their faith in me as an employee and given me the chance to make an honest living.” As for me, I am thankful for the opportunity to get paid for doing what I love to do. And I’m grateful to you, my readers, for enabling me to keep it going. Happy Thanksgiving! Dawn Anfuso is a Southern California business writer and former managing editor of Workforce magazine. If you have workplace or job-search questions, e-mail Dawn at email@example.com. Writers will remain anonymous.160Want local news?Sign up for the Localist and stay informed Something went wrong. Please try again.subscribeCongratulations! You’re all set!
Mario Balotelli has revealed he was NEVER happy at Liverpool and does NOT want to move back to Merseyside in the summer.The 25-year-old striker was loaned to AC Milan this season after scoring just once in the Premier League following his £16million Reds switch in August 2014.He has struggled for game time at San Siro, too, and it was claimed in February that the Italian is set to return to Anfield in the summer after Milan decided to turn down the option to sign him permanently.But, after starting in Milan’s last two Serie A games, the Italian media are now suggesting he might have a future with Cristian Brocchi’s team and Balotelli is keen to stay in his homeland.“In terms of my future I want to stay with Milan because I was not happy at Liverpool and don’t want to go back,” he was quoted as saying by Gazzetta dello Sport.“Plus, Milan have the money to buy me.“I’ve played well in my last two games and there are six left for me to prove what I can do.” 1 Mario Balotelli had admitted he was never happy at Liverpool
12 In: Romelu Lukaku (Everton) – £9.8m – Click the right arrow for more advice – Having scored four goals against Bournemouth in the gameweek before last, Romelu Lukaku is on good form at present. If youre looking for a striker who will play in all three of the upcoming gameweeks, Lukaku is your man. 12 12 In: Seamus Coleman (Everton) – £5.9m – Click the right arrow for more advice – In his last seven games, Seamus Coleman has picked up one goal, three assists and four clean sheets. Combine that with the fact he will play in all three of the upcoming gameweeks and the Irishman becomes a must have. 12 12 Out: Eden Hazard (Chelsea) – £10.3m – Click the right arrow for more advice – Eden Hazard has only scored one goal in his last seven league games. For £10.3m, thats simply not good enough. 12 12 12 Out: Zlatan Ibrahimovic (Manchester United) – £11.5m – Click the right arrow for more advice – As mentioned below, Manchester United miss two of the next three gameweeks. Itd be unwise to keep their players in your team for this period. In: Sadio Mane (Liverpool) – £9.3m – Click the right arrow for more advice – Sadio Mane has come back from the Africa Cup of Nations with a bang as he scored twice against Spurs last time out in the league. Liverpool are one of a select few teams who play in all of the next three gameweeks and so investing in Mane could see you picking up points where others are missing out. 12 12 12 12 Out: Gabriel Jesus (Manchester City) – £9.2m – Click the right arrow for more advice – Gabriel Jesus was injured in his last Premier League outing at Bournemouth and will now miss two/three months. Out: Antonio Valencia (Manchester United) – £5.6m – Click the right arrow for more advice – As mentioned below, Manchester United miss two of the next three gameweeks. Itd be unwise to keep their players in your team for this period. Out: Laurent Koscielny (Arsenal) – £6.3m – Click the right arrow for more advice – As mentioned below, Arsenal miss two of the next three gameweeks. Itd be unwise to keep their players in your team for this period. In: Pedro (Chelsea) – £6.9m – Click the right arrow for more advice – Pedro is on good form for Chelsea at the moment, having scored in both of his last two games. With a price tag £3.4m less than that of Eden Hazards, the Spaniard is not bad value at all. In: David Luiz (Chelsea) – £6.3m – Click the right arrow for more advice – Chelsea may not play on gameweek 28 due to their FA Cup tie, but it is still worth having David Luiz in your team at least until then. Chelseas next two fixtures against Swansea (H) and West Ham (A) provide two good chances to collect clean sheets. There’s nothing like the cup competitions to absolutely destroy a Fantasy Premier League team.This week Manchester United, Manchester City, Arsenal and Southampton all don’t play due to Sunday’s League Cup final between United and the Saints.And two weeks after that, Manchester United, Arsenal, Southampton, Chelsea, Spurs, Palace, Leicester, ‘Boro, Sunderland and Watford all have a blank gameweek because of their FA Cup fixtures.There are lots of players to be avoided as a result of this, especially at United, Arsenal and Southampton, as these teams will miss two out of the next three gameweeks!Check out the Fantasy Premier League transfers you might need to make this week by clicking the right arrow above… Out: Alexis Sanchez (Arsenal) – £11.7m – Click the right arrow for more advice – As mentioned below, Arsenal miss two of the next three gameweeks. Itd be unwise to keep their players in your team for this period. In: Diego Costa (Chelsea) – £10.6m – Click the right arrow for more advice – Chelsea dont play on GW28, but do have two appealing fixtures against Swansea (H) and West Ham (A) in GW26 and GW27. For this reason, it may be worth keeping an eye on their star striker.
The Shandon Hotel & Spa have announced a spectacular Black Friday deal on their B&B rates.The Portnablagh hotel is slashing 50% off B&B rates if you book using the code BLACKFRIDAY on their website. The sale has already begun, so book now to avoid disappointment. This offer is valid for B&B rates between 25th Nov – 28th Feb 2017. With this offer, guests will stay in luxurious rooms overlooking the breathtakingly beautiful Sheephaven Bay for just half the price. The Shandon Hotel & Spa has had huge success since it opened earlier this year, and this latest offer is sure to bring further crowds to the hotel for the festive period and into the new year. The hotel’s magical winter wonderland walkthrough was opened this season, and Mrs Claus’ Cabin, Gingerbread Alley and Narnia are all open for kids to explore.The Shandon Spa has also been a fabulous addition to the resort. The spa encompasses a swimming pool, thermal spa, relaxation room and outdoor Canadian hot-tub – all overlooking the beautiful Marble Hill Beach. With so many reasons to stay at the hotel, this Black Friday 50% off deal is an excellent reason to book your stay now.Simply visit https://app.thebookingbutton.com/properties/shandondirect?check_in_date=19-11-2016&check_out_date=20-11-2016&number_adults=2And put in promo code BLACKFRIDAY*Promo code only valid on dates between 25th Nov and 28th Feb 2017. Offer is subject to availability.What a bargain! Shandon Hotel offers half price B&B rates was last modified: November 23rd, 2016 by Rachel McLaughlinShare 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)
In this web-enabled world of ours, you have to wonder why business cards are still so popular. Shouldn’t there be a better way? A number of startups have attempted to address this problem with ingenious solutions that range from iPhone apps to custom URLs. Others are calling for the use of QR Codes for mobile data exchange. Unfortunately, no one service has hit the sweet spot just yet, but newcomer “E” thinks they have it figured out. Will “E” succeed where the others have failed? Or is this one industry that refuses to become digitized?HelloMyNameIsE.com You have to appreciate E’s creative URL – it’s memorable, but also makes you curious. E? What’s E?, you wonder. When I first encountered the URL, it was in a tweet which read “I’m now using E to add friends to my Twitter account. More info on http://hellomynameise.com.” Did I click though? You bet. “E,” as it turns out, is a new spin on digital contact exchange. Instead of using paper business cards, you use your phone to exchange data. At first, you may think that sounds very much like mobile contact service Dropcard, but it’s not. The only similarity between E and Dropcard is that they both allow you to customize your profile online and share it with others, but the similarities end there. To use Dropcard, you either text or use a mobile app which emails your contact info to the person you just met. With E, you go to a mobile web URL that lets you exchange a passcode with your new contact. The passcode is simply a five-digit code which is entered into the mobile web app itself. They show your theirs, you show them yours…that sort of thing. Once connected, you don’t receive an email message with their contact info like with Dropcard. E goes a step further and actually adds that contact to all the services you’ve already integrated with E. Service IntegrationAt the moment, E allows you to integrate Twitter, PICNIC (a network for the PICNIC conference), and Soocial. However, Delicious, European social portal Netlog, and LastFM are listed as coming soon. After you integrate these services with E, when you add a contact they’re immediately added to all those other web services, too. And thanks to Soocial, an address book solution, E contact info can also synchronize with your email address book in Gmail, Highrise, your OSX address book, or the address book on your phone itself. Barriers To AdoptionE faces one of the typical problems that many web 2.0 startups do – they don’t work for you until a lot of people are using it. Just because you have a profile on E, that doesn’t mean that those you meet do. And unlike a service like Dropcard, there isn’t a way to use E without the other person’s involvement. In addition to the service itself, the developers of E came up with a crazy but interesting idea for a hardware device called the “Connector.” With this device, you can exchange contact info with others just by touching the two connectors together. While gadget junkies and shiny object collectors may find this device appealing, it could easily remain a niche gadget that ends up sitting on the shelf next to your Chumby and Nazbaztag. To cross the adoption barrier, those at E would be smart to sponsor events where everyone gets a Connector at registration. After a few high-profile events, they would have industry movers and shakers on board, and that’s always a good place to start. Sponsoring events may be just what the company is planning, though, since their site mentions that the “Connector will be released at large events in the near future.” Will It Work?At present, the E service is very basic. Twitter integration is the only service of note that works yet. (Soocial looks great, but is in private beta). The profiles themselves are also not as flexible as those with Dropcard are. You can easily add and remove services with Dropcard, but with E, I wasn’t even able to add a second company that represents my second job. The services section of the web site is confusing – it doesn’t allow you to do anything more than customize which services are connected. The actual profile information is entered under “Settings,” so you can’t specify that only personal contacts get your home address, for example. It appears to be all-or-nothing. E still has far to go to become a truly successful digital contact exchange service, but at least they’re trying something different. Because they operate via mobile URL, not an app specific to any one device, they’re better positioned for more universal adoption that a service that designates itself as iPhone-only, for example. The service is in private beta testing now, but you have the opportunity to make an impassioned plea as to why they should invite you on the signup page here. (If you get in, feel free to add me: 17975.)Check out the video below to see E in action:Hello, my name is E from Renato Valdés Olmos on Vimeo. Related Posts Why Tech Companies Need Simpler Terms of Servic… Tags:#Features#Product Reviews#web Top Reasons to Go With Managed WordPress Hosting A Web Developer’s New Best Friend is the AI Wai… sarah perez 8 Best WordPress Hosting Solutions on the Market
GRAPHIC: G. GRULLÓN/SCIENCE By Paul VoosenJul. 6, 2017 , 2:00 PM Jason Yosinski sits in a small glass box at Uber’s San Francisco, California, headquarters, pondering the mind of an artificial intelligence. An Uber research scientist, Yosinski is performing a kind of brain surgery on the AI running on his laptop. Like many of the AIs that will soon be powering so much of modern life, including self-driving Uber cars, Yosinski’s program is a deep neural network, with an architecture loosely inspired by the brain. And like the brain, the program is hard to understand from the outside: It’s a black box. This particular AI has been trained, using a vast sum of labeled images, to recognize objects as random as zebras, fire trucks, and seat belts. Could it recognize Yosinski and the reporter hovering in front of the webcam? Yosinski zooms in on one of the AI’s individual computational nodes—the neurons, so to speak—to see what is prompting its response. Two ghostly white ovals pop up and float on the screen. This neuron, it seems, has learned to detect the outlines of faces. “This responds to your face and my face,” he says. “It responds to different size faces, different color faces.”No one trained this network to identify faces. Humans weren’t labeled in its training images. Yet learn faces it did, perhaps as a way to recognize the things that tend to accompany them, such as ties and cowboy hats. The network is too complex for humans to comprehend its exact decisions. Yosinski’s probe had illuminated one small part of it, but overall, it remained opaque. “We build amazing models,” he says. “But we don’t quite understand them. 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They can predict the best way to synthesize organic molecules. They can detect genes related to autism risk. They are even changing how science itself is conducted. The AIs often succeed in what they do. But they have left scientists, whose very enterprise is founded on explanation, with a nagging question: Why, model, why?That interpretability problem, as it’s known, is galvanizing a new generation of researchers in both industry and academia. Just as the microscope revealed the cell, these researchers are crafting tools that will allow insight into the how neural networks make decisions. Some tools probe the AI without penetrating it; some are alternative algorithms that can compete with neural nets, but with more transparency; and some use still more deep learning to get inside the black box. Taken together, they add up to a new discipline. Yosinski calls it “AI neuroscience.” Mark Riedl, Georgia Institute of Technology Like many AI coders, Mark Riedl, director of the Entertainment Intelligence Lab at the Georgia Institute of Technology in Atlanta, turns to 1980s video games to test his creations. One of his favorites is Frogger, in which the player navigates the eponymous amphibian through lanes of car traffic to an awaiting pond. Training a neural network to play expert Frogger is easy enough, but explaining what the AI is doing is even harder than usual.Instead of probing that network, Riedl asked human subjects to play the game and to describe their tactics aloud in real time. Riedl recorded those comments alongside the frog’s context in the game’s code: “Oh, there’s a car coming for me; I need to jump forward.” Armed with those two languages—the players’ and the code—Riedl trained a second neural net to translate between the two, from code to English. He then wired that translation network into his original game-playing network, producing an overall AI that would say, as it waited in a lane, “I’m waiting for a hole to open up before I move.” The AI could even sound frustrated when pinned on the side of the screen, cursing and complaining, “Jeez, this is hard.”Riedl calls his approach “rationalization,” which he designed to help everyday users understand the robots that will soon be helping around the house and driving our cars. “If we can’t ask a question about why they do something and get a reasonable response back, people will just put it back on the shelf,” Riedl says. But those explanations, however soothing, prompt another question, he adds: “How wrong can the rationalizations be before people lose trust?” Marco Ribeiro, a graduate student at the University of Washington in Seattle, strives to understand the black box by using a class of AI neuroscience tools called counter-factual probes. The idea is to vary the inputs to the AI—be they text, images, or anything else—in clever ways to see which changes affect the output, and how. Take a neural network that, for example, ingests the words of movie reviews and flags those that are positive. Ribeiro’s program, called Local Interpretable Model-Agnostic Explanations (LIME), would take a review flagged as positive and create subtle variations by deleting or replacing words. Those variants would then be run through the black box to see whether it still considered them to be positive. On the basis of thousands of tests, LIME can identify the words—or parts of an image or molecular structure, or any other kind of data—most important in the AI’s original judgment. The tests might reveal that the word “horrible” was vital to a panning or that “Daniel Day Lewis” led to a positive review. But although LIME can diagnose those singular examples, that result says little about the network’s overall insight.New counterfactual methods like LIME seem to emerge each month. But Mukund Sundararajan, another computer scientist at Google, devised a probe that doesn’t require testing the network a thousand times over: a boon if you’re trying to understand many decisions, not just a few. Instead of varying the input randomly, Sundararajan and his team introduce a blank reference—a black image or a zeroed-out array in place of text—and transition it step-by-step toward the example being tested. Running each step through the network, they watch the jumps it makes in certainty, and from that trajectory they infer features important to a prediction.Sundararajan compares the process to picking out the key features that identify the glass-walled space he is sitting in—outfitted with the standard medley of mugs, tables, chairs, and computers—as a Google conference room. “I can give a zillion reasons.” But say you slowly dim the lights. “When the lights become very dim, only the biggest reasons stand out.” Those transitions from a blank reference allow Sundararajan to capture more of the network’s decisions than Ribeiro’s variations do. But deeper, unanswered questions are always there, Sundararajan says—a state of mind familiar to him as a parent. “I have a 4-year-old who continually reminds me of the infinite regress of ‘Why?’”The urgency comes not just from science. According to a directive from the European Union, companies deploying algorithms that substantially influence the public must by next year create “explanations” for their models’ internal logic. The Defense Advanced Research Projects Agency, the U.S. military’s blue-sky research arm, is pouring $70 million into a new program, called Explainable AI, for interpreting the deep learning that powers drones and intelligence-mining operations. The drive to open the black box of AI is also coming from Silicon Valley itself, says Maya Gupta, a machine-learning researcher at Google in Mountain View, California. When she joined Google in 2012 and asked AI engineers about their problems, accuracy wasn’t the only thing on their minds, she says. “I’m not sure what it’s doing,” they told her. “I’m not sure I can trust it.”Rich Caruana, a computer scientist at Microsoft Research in Redmond, Washington, knows that lack of trust firsthand. As a graduate student in the 1990s at Carnegie Mellon University in Pittsburgh, Pennsylvania, he joined a team trying to see whether machine learning could guide the treatment of pneumonia patients. In general, sending the hale and hearty home is best, so they can avoid picking up other infections in the hospital. But some patients, especially those with complicating factors such as asthma, should be admitted immediately. Caruana applied a neural network to a data set of symptoms and outcomes provided by 78 hospitals. It seemed to work well. But disturbingly, he saw that a simpler, transparent model trained on the same records suggested sending asthmatic patients home, indicating some flaw in the data. And he had no easy way of knowing whether his neural net had picked up the same bad lesson. “Fear of a neural net is completely justified,” he says. “What really terrifies me is what else did the neural net learn that’s equally wrong?”Today’s neural nets are far more powerful than those Caruana used as a graduate student, but their essence is the same. At one end sits a messy soup of data—say, millions of pictures of dogs. Those data are sucked into a network with a dozen or more computational layers, in which neuron-like connections “fire” in response to features of the input data. Each layer reacts to progressively more abstract features, allowing the final layer to distinguish, say, terrier from dachshund.At first the system will botch the job. But each result is compared with labeled pictures of dogs. In a process called backpropagation, the outcome is sent backward through the network, enabling it to reweight the triggers for each neuron. The process repeats millions of times until the network learns—somehow—to make fine distinctions among breeds. “Using modern horsepower and chutzpah, you can get these things to really sing,” Caruana says. Yet that mysterious and flexible power is precisely what makes them black boxes. A new breed of scientist, with brains of silicon Special package: AI in science Opening up the black box Loosely modeled after the brain, deep neural networks are spurring innovation across science. But the mechanics of the models are mysterious: They are black boxes. Scientists are now developing tools to get inside the mind of the machine. How AI detectives are cracking open the black box of deep learning First, Yosinski rejiggered the classifier to produce images instead of labeling them. Then, he and his colleagues fed it colored static and sent a signal back through it to request, for example, “more volcano.” Eventually, they assumed, the network would shape that noise into its idea of a volcano. And to an extent, it did: That volcano, to human eyes, just happened to look like a gray, featureless mass. The AI and people saw differently.Next, the team unleashed a generative adversarial network (GAN) on its images. Such AIs contain two neural networks. From a training set of images, the “generator” learns rules about imagemaking and can create synthetic images. A second “adversary” network tries to detect whether the resulting pictures are real or fake, prompting the generator to try again. That back-and-forth eventually results in crude images that contain features that humans can recognize.Yosinski and Anh Nguyen, his former intern, connected the GAN to layers inside their original classifier network. This time, when told to create “more volcano,” the GAN took the gray mush that the classifier learned and, with its own knowledge of picture structure, decoded it into a vast array of synthetic, realistic-looking volcanoes. Some dormant. Some erupting. Some at night. Some by day. And some, perhaps, with flaws—which would be clues to the classifier’s knowledge gaps.Their GAN can now be lashed to any network that uses images. Yosinski has already used it to identify problems in a network trained to write captions for random images. He reversed the network so that it can create synthetic images for any random caption input. After connecting it to the GAN, he found a startling omission. Prompted to imagine “a bird sitting on a branch,” the network—using instructions translated by the GAN—generated a bucolic facsimile of a tree and branch, but with no bird. Why? After feeding altered images into the original caption model, he realized that the caption writers who trained it never described trees and a branch without involving a bird. The AI had learned the wrong lessons about what makes a bird. “This hints at what will be an important direction in AI neuroscience,” Yosinski says. It was a start, a bit of a blank map shaded in.The day was winding down, but Yosinski’s work seemed to be just beginning. Another knock on the door. Yosinski and his AI were kicked out of another glass box conference room, back into Uber’s maze of cities, computers, and humans. He didn’t get lost this time. He wove his way past the food bar, around the plush couches, and through the exit to the elevators. It was an easy pattern. He’d learn them all soon. Gupta has a different tactic for coping with black boxes: She avoids them. Several years ago Gupta, who moonlights as a designer of intricate physical puzzles, began a project called GlassBox. Her goal is to tame neural networks by engineering predictability into them. Her guiding principle is monotonicity—a relationship between variables in which, all else being equal, increasing one variable directly increases another, as with the square footage of a house and its price. Gupta embeds those monotonic relationships in sprawling databases called interpolated lookup tables. In essence, they’re like the tables in the back of a high school trigonometry textbook where you’d look up the sine of 0.5. But rather than dozens of entries across one dimension, her tables have millions across multiple dimensions. She wires those tables into neural networks, effectively adding an extra, predictable layer of computation—baked-in knowledge that she says will ultimately make the network more controllable.Caruana, meanwhile, has kept his pneumonia lesson in mind. To develop a model that would match deep learning in accuracy but avoid its opacity, he turned to a community that hasn’t always gotten along with machine learning and its loosey-goosey ways: statisticians.In the 1980s, statisticians pioneered a technique called a generalized additive model (GAM). It built on linear regression, a way to find a linear trend in a set of data. But GAMs can also handle trickier relationships by finding multiple operations that together can massage data to fit on a regression line: squaring a set of numbers while taking the logarithm for another group of variables, for example. Caruana has supercharged the process, using machine learning to discover those operations—which can then be used as a powerful pattern-detecting model. “To our great surprise, on many problems, this is very accurate,” he says. And crucially, each operation’s influence on the underlying data is transparent.Caruana’s GAMs are not as good as AIs at handling certain types of messy data, such as images or sounds, on which some neural nets thrive. But for any data that would fit in the rows and columns of a spreadsheet, such as hospital records, the model can work well. For example, Caruana returned to his original pneumonia records. Reanalyzing them with one of his GAMs, he could see why the AI would have learned the wrong lesson from the admission data. Hospitals routinely put asthmatics with pneumonia in intensive care, improving their outcomes. Seeing only their rapid improvement, the AI would have recommended the patients be sent home. (It would have made the same optimistic error for pneumonia patients who also had chest pain and heart disease.)Caruana has started touting the GAM approach to California hospitals, including Children’s Hospital Los Angeles, where about a dozen doctors reviewed his model’s results. They spent much of that meeting discussing what it told them about pneumonia admissions, immediately understanding its decisions. “You don’t know much about health care,” one doctor said, “but your model really does.”Sometimes, you have to embrace the darkness. That’s the theory of researchers pursuing a third route toward interpretability. Instead of probing neural nets, or avoiding them, they say, the way to explain deep learning is simply to do more deep learning. If we can’t ask … why they do something and get a reasonable response back, people will just put it back on the shelf. AI is changing how we do science. Get a glimpse Researchers have created neural networks that, in addition to filling gaps left in photos, can identify flaws in an artificial intelligence. PHOTOS: ANH NGUYEN Back at Uber, Yosinski has been kicked out of his glass box. Uber’s meeting rooms, named after cities, are in high demand, and there is no surge pricing to thin the crowd. He’s out of Doha and off to find Montreal, Canada, unconscious pattern recognition processes guiding him through the office maze—until he gets lost. His image classifier also remains a maze, and, like Riedl, he has enlisted a second AI to help him understand the first one.
MSSA: Harsh fires Campion into final Emiliano Sala’s sister Romina Sala who was very close to the footballer, posted a picture of Emiliano’s dog Nala, staring outside the door, waiting for his master to return. The heartbreaking picture has taken the internet by storm and with football fans all over the world sharing the picture all over the internet. Earlier this week, British investigators said they had spotted a body in the wreckage of a plane that disappeared in the Channel two weeks ago carrying Argentine footballer Emiliano Sala and his pilot. The wreck was found on the seabed and closer inspection by a remotely operated vehicle (ROV) confirmed both that it was the missing plane, and that a body was inside. “Tragically, in video footage from the ROV, one occupant is visible amidst the wreckage,” the British government’s Air Accident Investigation Branch (AAIB) said in a statement. “The AAIB is now considering the next steps, in consultation with the families of the pilot and passenger, and the police.” The AAIB also released a grainy image showing a part of the fuselage with the aircraft registration. The depth indicated on the image was 67.7 metres (222 feet). Local police called off the search after a few days. But Sala’s family launched a crowd-funding campaign for a private search, which raised over 300,000 euros. They hired shipwreck hunter David Mearns, whose vessel used sonar equipment to identify the plane wreckage on Sunday morning within a few hours of starting the search. “Based on analysis of ROV video footage, the AAIB investigators on board the vessel concluded that the object is wreckage from the missing Piper Malibu aircraft,” the AAIB said. Catch up on all the latest T20 news and updates here. Also download the new mid-day Android and iOS apps to get latest updates Tottenham Hotspur appoint Jose Mourinho as manager Promising footballer Emiliano Sala’s plane crash has shaken the football world. The Argentine footballer was on his way to join English football club Cardiff City to start a new chapter in his career. Emiliano Sala, 28, was flying from France to join his new club, when the light aircraft, carrying Sala and his pilot disappeared on January 21 north of the island of Guernsey.Related News Miquel Blazquez Font to emerge as a competent sports journalist in the sporting world
Embattled Jamaican sprinter Nesta Carter will return to the track this weekend in his first meeting since he was stripped of his Beijing Olympics gold medal after a retroactive test uncovered a banned substance in his sample.Carter’s re-tested sample from 2008 was found to have traces of the banned stimulant methylhexaneamine, the International Olympic Committee (IOC) said last month.Jamaica’s 4×100 metres relay team that included Usain Bolt were stripped of their gold medals. Last year in Rio, Bolt completed a ‘treble treble’ of Olympic gold medals in winning the 100, 200 and 4×100 titles at three successive Games.Bolt has already returned his Beijing relay medal.Carter has said he would appeal to the Court of Arbitration for Sport.The 31-year-old Carter, who has not raced competitively for 17 months due to injury and then because he was notified of the positive test, will run at the Western Relays in Montego Bay, his manager Bruce James told Reuters.Carter has not been banned by world governing body the International Association of Athletics Federations (IAAF) and correspondence between Jamaican athletics authorities and the IAAF seen by Reuters confirmed he would be clear to run until his appeal had been heard. (Life goes on for ‘disappointed’ Usain Bolt after losing gold medal)”Having consulted the IAAF Medical and Anti-Doping Department, it appears that Mr. Carter is not currently provisionally suspended,” IAAF chief executive Olivier Gers wrote in a letter in response to a query by Jamaican Athletics President Warren Blake.”He is eligible to compete in athletics competition pending the CAS proceedings.”advertisementCarter has until Feb. 15 to file his appeal with CAS.
“Had a great interaction with youth from Jammu and Kashmir who are touring different parts of India as a part of Watan Ko Jaano initiative,” the Prime Minister tweeted later. “We had a discussion on various issues like infrastructure development, sports facilities, education and employment opportunities in J&K,” he added. PTI AKK AKK