|Carrie Underwood Is Overcome With Hysterical Laughter In Mike Fisherâ€™s Instagram Story|
Saturday, 22 August 2020 07:35
Something clearly got the better of Carrie Underwood this week, as the star was overcome with hysteria in her husband Mike Fisher’s latest Instagram update. Mike shared a hilarious video, which can be seen via his Instagram story here for a few more hours, on Friday night (August 21) which showed the “Something In The Water” singer laughing so hard she was unable to move or speak.
She sat with her right hand covering her eyes and appeared to be crying with laughter. The country superstar snorted multiple times during her hysterical moment.
The retired Nashville Predators player admitted in the caption that he had no idea what actually tickled his wife, though he too could be heard giggling from behind the camera.
“My guess is as good as yours,” he wrote, alongside a smiley face made of a colon and bracket.
Publisher: Digital Trends
Saturday, 22 August 2020 07:34
The latest YouTube news and guides, all in one place. Digital Trends offers in-depth coverage of the largest video-sharing platform and everything it encompasses. With helpful user guides, videos, and channel suggestions, and detailed info on YouTube TV, here are all of the things you need to know. Related Categories:Â | | | |
|2 Tropical Storms Arenâ€™t Going To Merge Into A Megastorm - Hereâ€™s Why|
Publisher: Forbes Real Time
Saturday, 22 August 2020 07:34
No, 2 hurricanes won't merge into a megastorm. Why it will not happen with Laura and Marco in The Gulf of Mexico.
|Sat Aug 22 '20 Announcement from Flash: World's Most Powerful 210W USB-C Powerbank|
Publisher: Indiegogo: Announcements
Saturday, 22 August 2020 07:34
We love seeing the Flash in action so keep sending us photos as we want to keep re-sharing them :)
Some backers have reached out about the capacity of Flash. We’d like to advise everyone that there is always a conversion loss when the power is sent from a powerbank to the device being charged and this is normal for every charger.
If you’re unsure, here is how to calculate what charge % the Flash Powerbank can achieve for a specific device. Let's use an 87W MacBook Pro 15" as an example. The best way to answer your question is using the following formula which calculates the conversion of watt hrs to mah whr = mah*1000*V.
The Flash is 74whr/3.7v x 1000 * 70% (efficiency at 20V) = 14000mA.
The Macbook Pro 15" = 83.6 whr = 22,000mah = 63%.
In another example with a 29.37Wh Ipad Pro 11, 1.75 times is about right as that's 51.3975wh 74wh (flash) x 70% (remaining power at 20V after conversion loss) = 51.8wh
~ Shipping to US: We’re excited to share that the bulk shipment of 144 cartons has left our warehouse to begin its journey to our US fulfilment centre. Our shipping agent has advised that it will leave the Chinese port next Sunday as that is the earliest availability the ships have. Shipping via sea will take around 20- 35 days. While we try to account for events like bad weather or extended customs processing upon arrival in the US, which is what we unexpectedly experienced with our previous shipment that took 2 weeks alone, please note that this is our estimation given current circumstances. Upon arrival at the fulfilment centre, they will process all the received orders and arrange for them to be dispatched via DHL or UPS, where it’ll only take 3-5 days to reach you. You’ll receive a tracking number when it has left the fulfilment centre.
~ Asia: We have finished shipping to the majority of Asia now, except for Philippines, Indonesia and remote parts e.g. Borneo. The number of reduced passenger flights due to COVID-19 have made it extremely difficult with most forwarders not offering this service or charging exorbitant prices. If you are from Philippines or Indonesia and would like to receive your order faster by assisting with shipping, we are willing to cover the majority of the increase in price so please fill out the form for a quote
~ Europe: We have finished shipping to the majority of Europe with the exception of remote islands or parts of Eastern Europe e.g. Romania. The only forwarder we have found for Romania has advised it will take up to 60 days for delivery, which we find unacceptable. We are currently actively searching for a better solution. Our shipping agent this week is fulfilling the remaining rewards for our German backers.
~ Shipping Canada & India: The shipping suspension has just been lifted however the shipping price is still 160% more compared to pre-COVID. The ongoing tensions between China and India has also further increased shipping and made it extremely difficult. We have reached out to 15+ forwarders already and are still actively working on finding an economical shipping solution
~ Shipping to Aus & NZ: The majority has been shipped with our shipping agent this week fulfilling the remaining rewards for our Australian backers.
~ Shipping to Qatar, Saudi Arabia, Middle East, Africa, South America and remote or island countries remains unavailable until the temporary shipping suspension has been lifted. We’ve enquired with 15+ different forwarders now however none of them have a shipping method available. We will keep searching and will advise when things have changed.
Thank you for your continued support and patience. We remain committed to shipping rewards to all our backers as quickly as possible.
- Chargasap Team
|2020 Northern Trust: Live stream, watch online, golf schedule, coverage, channel, Tiger Woods start time|
Publisher: CBS Sports
Saturday, 22 August 2020 07:30
Find out when and how to watch the first playoff event of the 2019-20 PGA Tour season live all week
|Abbreviated Pundit Roundup: Successful Democratic convention finished, the dystopic RNC next|
Publisher: Daily Kos
Saturday, 22 August 2020 07:30
Amy Walter/Cook Report:
Chris Truax/USA Today:
David Lauter/LA Times:
|The UK used a formula to predict studentsâ€™ scores for canceled exams. Guess who did well.|
Saturday, 22 August 2020 07:30
Protesters in London objected to the governmentâ€™s handling of exam results after exams were canceled due to the coronavirus outbreak. | Aaron Chown/PA Images via Getty Images
The formula predicted rich kids would do better than poor kids whoâ€™d earned the same grades in class.
Every spring, British students take their A-level exams, which are used to determine admission into college.
But this year was different. With the Covid-19 pandemic still raging, springâ€™s A-levels were canceled. Instead, the government took an unorthodox â€” and controversial â€” approach to assessing admissions without those exam scores: It tried to use a mathematical rule to predict how the students would have done on their exams and then use those estimates as a stand-in for actual scores.
The approach the government took was fairly simple. It wanted to guess how well a student would have done if they had taken the exam. It used two inputs: the studentâ€™s grades this year and the historical track record of the school the student was attending.
So a student who got excellent grades at a school where top students usually get good scores would be predicted to have achieved a good score. A student who got excellent grades at a school where excellent grades historically havenâ€™t translated to top-tier scores on the A-levels would instead be predicted to get a lower score.
The overall result? There were more top scores than are awarded in any year when students actually get to take the exam.
But many individual students and teachers were still angry with scores that they felt were too low. Even worse, the adjustment for how well a school was â€œexpectedâ€� to perform ended up being strongly correlated with how rich those schools are. Rich kids tend to do better on A-levels, so the prediction process awarded kids at rich schools higher grades.
The predictive process and its outcome set off alarm bells. One Guardian columnist called it â€œshockingly unfair.â€� Legal action was threatened. After a weekend of angry demonstrations where students, teachers, and parents chanted, â€œFuck the algorithm,â€� Britain backed off and announced that it will give students whatever grade their teachers estimated they would get if itâ€™s higher than the exam score estimates.
Whatâ€™s playing out in Britain is a bunch of different things at once: a drama brought on by the Covid-19 pandemic exacerbated by bad administrative decision-making against the backdrop of class tensions. Itâ€™s also an illustration of a fascinating dilemma often discussed as â€œAI biasâ€� or â€œAI ethicsâ€� â€” even though it has almost nothing to do with AI. And it raises important questions about the kind of biases that get our attention and those that for whatever reason largely escape our scrutiny.
Predicting an unfair world
Imagine a world where rich children and poor children are just as likely to do drugs, but poor children are five times more likely to be arrested. Every time someone is arrested, a prediction system tries to predict whether they will re-offend â€” that is, whether someone like that person who is arrested for drugs will likely be arrested for drugs again within a year. If they are likely to re-offend, they get a harsher sentence. If they are unlikely to re-offend, they are released with probation.
Since rich children are less likely to be arrested, the system will correctly predict that they are less likely to be re-arrested. It will declare them unlikely to re-offend and recommend a lighter sentence. The poor children are much more likely to be re-arrested, so the system tags them as likely re-offenders and recommends a harsh sentence.
This is grossly unfair. There is no underlying difference at all in the tendency to do drugs, but the system has disparities at one stage and then magnifies the disparities at the next stage by using them to make criminal judgments.
â€œThe algorithm shouldnâ€™t be predicting re-jailing; it should be predicting re-offending. But the only proxy variable we have for offending is jailing, so it ends up double-counting anti-minority judges and police,â€� Leor Fishman, a data scientist who studies data privacy and algorithmic fairness, told me.
If the prediction system is an AI trained on a large dataset to predict criminal recidivism, this problem gets discussed as â€œAI bias.â€� But itâ€™s easy to see that the AI is not actually a crucial component of the problem. If the decision is made by a human judge, going off their own intuitions about recidivism from their years of criminal justice experience, it is just as unfair.
Some writers have pointed to the UKâ€™s school decisions as an example of AI bias. But itâ€™s actually a stretch to call the UKâ€™s Office of Qualifications and Examinations Regulationâ€™s approach here â€” taking student grades and adjusting for the schoolâ€™s past yearâ€™s performance â€” an â€œartificial intelligenceâ€�: it was a simple math formula for combining a few data points.
Rather, the larger category here is perhaps better called â€œprediction biasâ€� â€” cases where, when predicting some variable, we are going to end up with predictions that are disturbingly unequal. Often theyâ€™ll be deeply influenced by factors like race, wealth, and national origin that anti-discrimination laws broadly prohibit taking into account and that it is deeply unfair to hold against people.
AIs are just one tool we use to make predictions, and while their failings are often particularly legible and maddening, they are not the only system that fails in this way. It makes national news when a husband and wife with the same income and debt history apply for a credit card and get offered wildly different credit limits thanks to an algorithm. It probably wonâ€™t be noticed when the same thing happens but the decision was made by a local banker not relying on complex algorithms.
In criminal justice, in particular, algorithms trained on recidivism data make sentencing recommendations with racial disparities â€” for instance, unjustly calling to imprison Black men for longer jail time than white men. But when not using algorithms, judges make these decisions off sentencing guidelines and personal intuition â€” and that produces racial disparities, too.
Are disparities in predictions really more unjust than disparities in real outcomes?
Itâ€™s important not to use unjust systems to determine access to opportunity. If we do that, we end up punishing people for having been punished in the past, and we etch societal inequalities deeper in stone. But itâ€™s worth thinking about why a system that predicts poor children will do worse on exams generated so much more rage than the regular system that just administers exams â€” which, year after year, poor children do worse on.
For something like school exam scores, there arenâ€™t disparities just in predicted outcomes but in real outcomes too: Rich children generally score better on exams for many reasons, from better schools to better tutors to more time to study.
If the exam had actually happened, there would be widespread disparities between the scores of rich kids and poor kids. This might anger some people, but it likely wouldnâ€™t have led to the widespread fury that similar disparities in the predicted scores produced. Somehow, weâ€™re more comfortable with disparities when they show up in actual measured test data than when they show up in our predictions about that measured test data. The cost to studentsâ€™ lives in each instance is the same.
The UK effectively admitted, with their test score adjustments, that many children in the UK attended schools where it was very implausible they would get good exam scores â€” so implausible that even the fact they got excellent grades throughout school wasnâ€™t enough for the government to expect theyâ€™d learned everything they needed for a top score. The government may have backed down now and awarded them that top score anyway, but the underlying problems with the schools remain.
We should get serious about addressing disparities when they show up in real life, not just when they show up in predictions, or weâ€™re pointing our outrage at the wrong place.
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|Landon Clifford of the Cam&Fam YouTube Channel Dead: Camryn Clifford’s Husband Dies at 19 Following ‘Brain Injury’|
Saturday, 22 August 2020 07:29
Landon Clifford, the husband of Camryn Clifford and stars of the YouTube channel Cam&Fam, has died at 19, his wife said in an Instagram post. The couple had two daughters together, Collette Briar and Delilah Rose. Clifford’s death comes three months after the birth of the couple’s second child.
Clifford had been in a coma since August 13 following a brain injury, his wife said. The cause of the brain injury was not made public by Camryn Clifford, 19. Clifford donated his organs “to people in need all over the country,” his wife also said.
Camryn Clifford described her husband as, “Compassionate, loving, thoughtful, kind, and gentle. He was an amazing husband and the best father those girls could have ever asked for.” She added, “Words can not come close to describe the pain I feel. All I can do now is make sure our girls know how much he loved us.”
Clifford and his wife began their YouTube channel in November 2017. Their first video was a gender reveal for their first child. At the time, both Clifford and his wife were 17 years old. Camryn Clifford became pregnant at 16. In the description of the video, Collette Clifford said that at the time of the video, the pair were living in different states. The Clifford’s YouTube channel has over 1.2 million subscribers.
A GoFundMe page that has been set up to help to raise money for the Clifford family has already surpassed its goal of $10,000. The page refers to Clifford as “a beloved husband, father, son, brother, and friend.” The Clifford family also sell merchandise through their official website.
In December 2019, Camryn Clifford tweeted a photo of her with her future husband in 2015. In a separate tweet, Camryn Clifford said that the couple attended a homecoming dance together in 2015 and their prom in 2019. The became engaged on June 29, 2018. In October 2019, the couple announced that Camryn Clifford was pregnant with their second child.
On February 17, the day of Clifford’s 19th birthday, his wife paid tribute to him saying in part, “I couldn’t ask for a better husband. Our daughters couldn’t ask for a better dad. Your parents couldn’t ask for a better son.”
|Sancho quizzed on Man Utd transfer â€˜noiseâ€™ as Borussia Dortmund winger targets two Ballons dâ€™Or|
Publisher: Goal.com News - English - America
Saturday, 22 August 2020 07:25
The England international continues to see a big-money move to Old Trafford mooted, but he is ignoring the gossip and focusing on his game
|Biden is not the only one with difficulty speaking part 2|
Publisher: Live Leak
Saturday, 22 August 2020 07:24
Trump forgot to engage his brain