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Tuesday, November 3, 2020

2020 election: Biden, Trump score wins, but battlegrounds too early to call

Early victories draw to an end a campaign that was reshaped by the coronavirus and marked by contentiousness.

Polls closed across the country Tuesday night as President Donald Trump and Democratic challenger Joe Biden concluded an epic campaign that will shape America’s response to the surging pandemic and foundational questions of economic fairness and racial justice.

The night opened with predictable victories for each candidate, with Trump taking states including Louisiana and North Dakota and Biden’s haul including New York and Virginia a former battleground that has become a Democratic stronghold. It was too early to call, in a tight race, the 2020 battleground of Florida as well as Georgia and Pennsylvania.

Americans made their choices as the nation faced a confluence of historic crises with each candidate declaring the other fundamentally unfit to navigate the challenges. Daily life has been upended by the coronavirus, which has killed more than 232,000 Americans and cost millions of jobs.

Read More: Armed Trump supporter arrested at North Carolina poll site

Millions of voters put aside worries about the virus — and some long lines — to turn out in person, joining 102 million fellow Americans who voted days or weeks earlier, a record number that represented 73% of the total vote in the 2016 presidential election.

Biden entered Election Day with multiple paths to victory, while Trump, playing catch-up in a number of battleground states, had a narrower but still feasible road to clinch 270 Electoral College votes.

Control of the Senate was at stake, too: Democrats needed to net three seats if Biden captured the White House to gain control of all of Washington for the first time in a decade. Senate Majority Leader Mitch McConnell of Kentucky won reelection in an early victory for the Republicans. The House was expected to remain under Democratic control.

As the results began to come in, the nation braced for what was to come — and an outcome that might not be known for days.

A new anti-scaling fence was erected around the White House, and in downtowns from New York to Denver to Minneapolis, workers boarded up businesses lest the vote lead to unrest.

With the worst public health crisis in a century still fiercely present, the pandemic — and Trump’s handling of it — was the inescapable focus for 2020.

For Trump, the election stood as a judgment on his four years in office, a term in which he bent Washington to his will, challenged faith in its institutions and changed how America was viewed across the globe. Rarely trying to unite a country divided along lines of race and class, he has often acted as an insurgent against the government he led while undermining the nation’s scientists, bureaucracy and media.

Read More: Ahmaud Arbery’s mother will vote for Biden near spot son was killed

At the White House Tuesday night, more than 100 family members, friends, donors and staff were set to watch returns from the East Room. Trump was watching votes come in upstairs in the residence with a few close aides. Most top campaign officials were monitoring returns from a “war room” set up in the Eisenhower Executive Office Building.

Biden spent the day last-minute campaigning in Scranton, Pennsylvania, where he was born, and in Philadelphia with a couple of local stops in Wilmington, Delaware, where he was spending Election Night.

The president began his day on an upbeat note, predicting that he’d do even better than in 2016. But during a midday visit to his campaign headquarters, he spoke in a gravelly, subdued tone.

“Winning is easy,” Trump told reporters. “Losing is never easy, not for me it’s not.”

President Donald Trump speaks at a rally on November 02, 2020 in Avoca, Pennsylvania. Donald Trump is crossing the crucial state of Pennsylvania in the last days of campaigning before Americans go to the polls on November 3rd to vote. Trump is currently trailing his opponent Joe Biden in most national polls. (Photo by Spencer Platt/Getty Images)

Trump left open the possibility of addressing the nation Tuesday night, even if a winner hadn’t been determined. Biden was also scheduled to give a nighttime speech from Wilmington.

“I’m superstitious about predicting what an outcome’s gonna be until it happens … but I’m hopeful,” said Biden. “It’s just so uncertain … you can’t think of an election in the recent past where so many states were up for grabs.”

With the coronavirus now surging anew, voters ranked the pandemic and the economy as top concerns in the race between Trump and Biden, according to AP VoteCast, a national survey of the electorate.

Voters were especially likely to call the public health crisis the nation’s most important issue, with the economy following close behind. Fewer named health care, racism, law enforcement, immigration or climate change

The survey found that Trump’s leadership loomed large in voters’ decision-making. Nearly two-thirds of voters said their vote was about Trump — either for him or against him.

The momentum from early voting carried into Election Day, as an energized electorate produced long lines at polling sites throughout the country. Voters braved worries of the coronavirus, threats of polling place intimidation and expectations of long lines caused by changes to voting systems, but appeared undeterred as turnout appeared it would easily surpass the 139 million ballots cast four years ago.

No major problems arose on Tuesday, outside the typical glitches of a presidential election: Some polling places opened late, robocalls provided false information to voters in Iowa and Michigan, and machines or software malfunctioned in some counties in the battleground states of Ohio, Pennsylvania, Georgia and Texas.

The cybersecurity agency at the Department of Homeland Security said there were no outward signs by midday of any malicious activity.

The record-setting early vote — and legal skirmishing over how it would be counted — drew unsupported allegations of fraud from Trump, who had repeatedly refused to guarantee he would honor the election’s result.

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Trump: ‘Winning is easy. Losing is never easy’

President Donald Trump does not have a victory speech ready.

President Donald Trump is not a hundred percent sure he is winning the election.

On Tuesday, he visited his campaign headquarters in Arlington, Virginia and told reporters per The Hill, “I’m not thinking about concession speech or acceptance speech yet.”

He added, “Hopefully we’ll be only doing one of those two. Winning is easy. Losing is never easy. Not for me it’s not.”

Donald Trump thegrio.com
(Photo by Kamil Krzaczynski/Getty Images)

Read More: Vermont GOP Gov. Phil Scott votes for Biden over Trump

He stopped by the campaign headquarters to thank his staff and admitted that a defeat would be a challenge for him.

Trump says, “depending on the extent of victory,” it should be clear by the end of the night who won. He complained by saying “We should be entitled to know who won on Nov. 3.”

He also isn’t thrilled that Pennsylvania accepts mail in ballots received by  Nov. 6.

When asked if he had a message for those who did not vote for him in case he wins, his response was, “Everybody should come together, and I think success brings us together.”

Read More: Armed Trump supporter arrested at North Carolina poll site

Dozens of his staffers attended the headquarters gathering and while many wore masks, others did not including senior adviser Jared Kushner, press secretary Kayleigh McEnany, and chief of staff Mark Meadows were seen without them.

The president is expected to return to the White House to attend a party in the East Room with hundreds of others despite the fact that coronavirus is still a real threat, especially in crowded spaces.

While Trump is staying kept in the White House, Michelle Obama has continued to support the former vice president. As reported by theGrio, Obama took to Twitter to speak about his character.

“I know Joe. He has lived his life guided by values and principles that mirror ones that most Americans can recognize. He understands the struggles of everyday folks. Vote today for the future you want to see for our country. Vote for @JoeBiden,” she tweeted.

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Ahmaud Arbery’s mother will vote for Biden near spot son was killed

Ahmaud Arbery’s mother met with Trump after her son was killed but will vote for Biden instead

Wanda Cooper, the mother of Ahmaud Arbery, isn’t letting a three-hour drive stop her from voting. The mother who laid her son to rest earlier this year after he was shot and killed in Glynn County, Georgia allegedly by resident Travis McMichael while on a jog.

Read More: Ahmaud Arbery’s life and death profiled in ’48 Hours’ documentary: ‘Modern-day lynching’

According to TMZ, Arbery’s mother returned to Brunswick, GA, to vote. She moved away after her son passed but she says the three-hour drive from where she currently lives is worth it because she is honoring her son.

Wanda Jones-Cooper, Ahmaud Arbery theGrio.com
Wanda Jones-Cooper with her son, Ahmaud Arbery (Personal Family Picture)

She voted for Joe Biden despite meeting with President Donald Trump after her son was killed.

“A GREAT woman. Her son is looking down from heaven & is very proud of his wonderful & loving mom!!!,” Trump tweeted in June.

Cooper says she isn’t impressed with Trump. She told the publication she does not believe he will live up to his promises such as fixing the racial tensions in this country and she isn’t a fan of how he has handled the coronavirus pandemic and the little remorse for the over 200,000 Americans who have lost their lives. She explained Biden won her over with his message of unity. She believed Biden could bring about real change and says her son would have felt the same way.

Read More: Ahmaud Arbery’s mother says 2:23 Foundation using son’s name without consent

Cooper previously authored an article for ABC News in July and shared that her son’s final words to her were sweet and that they shared a special bond.

“The last time I saw Ahmaud alive his last three words were, “I love you.” And whenever I get discouraged or really sad, I hear his voice saying those words,” she wrote.

“My other two children, sometimes they thought Ahmaud was my favorite. But I’d tell them, “I love you all.” It’s because Ahmaud and I shared a very special bond. We were really close. Ahmaud was the baby that would come and give me a kiss on the cheek. And when he grew into a young adult, he would still give me those same little kisses.”

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The Somali man who has a scorpion named after him

Somali environmentalist Ahmed Ibrahim Awale hopes it will inspire African researchers.

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Create A Unique, Private Business Phone Number With This App For Just $20 A Year

Many small business owners use their personal phone number as their business’s primary point of contact, but this can be quite confusing if you want to keep your business and personal life separate. That’s why it’s recommended that every business, whether it’s brick-and-mortar or 100% digital, gets a separate phone number to handle business inquiries. 

That doesn’t mean you need to buy a second phone plan, let alone a new phone. With Hushed, you get a second, private phone line with a unique number that you can use for public use while keeping your personal phone number hidden. Plans start at 6,000 SMS messages and 1,000 talk minutes per year, which you can get for just $19.99 with this deal

Hushed is a secure, app-based private phone line service that works on iOS and Android devices. You’ll get a new phone number to make calls, send texts, and customize voicemail with the option to choose from over 100 different area codes across the US and Canada. You can even conduct all of your communications through Wi-Fi so you don’t incur service charges. Best of all, you can enjoy all of these features without signing up for a new, expensive phone plan from your mobile provider. 

If you want to run your business professionally, it’s best to separate work and play. That includes having a separate phone number for your business. With Hushed, you get a private phone line that works on your current mobile device without committing to an expensive new phone plan. Plans start at $19.99 per year and go as high as $59.99 for 12,000 SMS messages and 2,500 minutes per year. 

Prices subject to change.



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George Floyd’s brother rallies voters on Election Day

Terrence Floyd feels under constant pressure to relay his brother’s voice — especially on this Election Day, when, as he sees it, race and racial justice are on the ballot

NEW YORK (AP) — The murmurs spread quickly among the poll workers late Tuesday morning at a Brooklyn neighborhood station: George Floyd’s brother was present.

A few came up to Terrence Floyd, whose brother George died in the custody of Minneapolis police, sparking protests for racial justice across the nation. “Keep the fight going,” one Black woman urged. Others asked to take their photos with Terrence.

Read More: Vermont GOP Gov. Phil Scott votes for Biden over Trump

Since the death of his older brother on May 25th, Terrence has been thrust into a spotlight he did not seek. A 42-year-old school bus driver in New York, Terrence is normally a quiet man, deeply attached to his three children. But now, he feels under constant pressure to relay his brother’s voice — especially on this Election Day, when, as he sees it, race and racial justice are on the ballot.

“Ever since then, I’ve felt like he was talking to me,” he says of George’s death. “He was saying, Little bro, just speak for me. Walk for me. Love for me. Get these people to understand what happened to me can happen to anybody.”

On this Tuesday, Terrence’s black hoodie and face mask included the words “I can’t breathe,” “Justice for George,” and “8:46,” representing the approximate time that a white officer held a knee to his brother’s neck until he became unresponsive.

Terrence Floyd, brother of George Floyd, waits to speak at a Get Out the Vote Rally outside the Brooklyn Museum, Tuesday, Nov. 3, 2020, in New York. (AP Photo/Frank Franklin II)

After famously urging calm as anger spilled onto the streets over his brother’s death, Terrence planned to spend Election Day following up on a less-noticed part of his emotional plea to protesters: please vote.

The names George Floyd, Breonna Taylor, Ahmaud Arbery and Rayshard Brooks, all killed by police or vigilantes, re-energized the Black Lives Matter movement this year and put race and justice at the center of the election. As voting wraps up coast to coast, their loved ones awaited signs that their public grief and loss of anonymity weren’t in vain.

Former Vice President Joe Biden has promised racial justice and reforms, while President Donald Trump has stuck to a stern “law and order” rhetoric. After a summer of protests, about half of voters call racism a “very serious” problem in U.S. society, AP polling found. But compared with the pandemic and the economy, relatively few voters – about one in 10 – deemed racism or law enforcement the country’s top issue, the poll found.

The Floyd family has reached out on behalf of Biden’s campaign. On Sunday, Terrence joined his sister, Bridgett Floyd, and other family members for a rally with Jill Biden in Tallahassee, Florida. Last month, Bridgett appeared in a campaign ad for Joe Biden.

Like all of America, Terrence was anxious on Tuesday.

“Tuesday is so important,” said the Rev. Nicolas O’Rourke, the Pennsylvania organizing director for the Working Families Party, which focuses on systemic racism. Philadelphia became a hot spot in the wake of the fatal police shooting of Walter Wallace, Jr., a Black man whose family members had requested mental crisis intervention on Oct. 26.

Terrence Floyd, brother of George Floyd, second from left, waits to vote with Sandy Rubenstein, left, and Rev. Kevin McCall, Tuesday, Nov. 3, 2020, in the Brooklyn borough of New York. (AP Photo/Frank Franklin II)

“While communities are at varying points on the reform spectrum….it’s pretty clear there is a unilateral agreement that something needs to shift,” he said.

By early afternoon, Terrence, along with his attorney Sanford Rubenstein and civil rights activist Kevin McCall, were driving around Brooklyn looking for potential voters, with a loudspeaker and a microphone in their SUV. But there were no lines at a handful of schools and community centers.

Perhaps most people had already voted early, Terrence thought. And hoped. Maybe they had already heeded the message about the importance of voting.

“I never really wanted to be political and tell people who to vote for, because everybody has their own decision, their own opinions,” Terrence said. “But I do say, ‘wake up, use your eyes, pay attention to what’s going on.’”

Just after 1 p.m., they parked across the street from the Brooklyn Museum, which has been serving as a polling location. Outside of the building, a small marching band sang, drummed and blew wind instruments. They paused to allow Terrence a moment to speak.

“If you don’t vote, you cannot complain when something goes wrong,” he said, using a loudspeaker and microphone. “I’m out here to let y’all know that I voted, because I can’t talk the talk, if I don’t walk the walk.”

More than a dozen people had stopped to hear what Terrence had said and, when he concluded, the band resumed playing.

“Don’t forget to vote!” he chanted in rhythm with the band.

Terrence Floyd, brother of George Floyd, speaks at a Get Out the Vote rally, outside the Brooklyn Museum, Tuesday, Nov. 3, 2020, in the Brooklyn borough of New York. (AP Photo/Frank Franklin II)

Tuesday marked exactly 155 days since Terrence visited Minneapolis, where his brother died. On June 1, in the wake of arson, looting and other violence that spread to cities nationwide, Terrence begged for calm.

“Let’s switch it up, y’all. Let’s switch it up. Do this peacefully, please,” Terrence said at a June 1 press conference in Minneapolis.

That same day, the president threatened the nation’s governors with deployment of the military to states, if leaders did not quell violent unrest.

“My administration is fully committed that, for George and his family, justice will be served,” Trump said in remarks from the White House Rose Garden. “He will not have died in vain. But we cannot allow the righteous cries and peaceful protesters to be drowned out by an angry mob.”

That day in June, Terrence cancelled previously scheduled interviews with TV news networks. He was overwhelmed.

His surviving brothers and sisters have become much closer over the last several months, Terrence said. His 17-year-old son, Amaree Floyd, learned of his uncle’s passing by seeing the viral video of the officer kneeling on his neck.

Read More: Michelle Obama makes final push for Biden: ‘He’s a good man’

“I had to really talk to him about channeling his anger,” Terrence said. “I said, put that anger into your schoolwork. Put that anger into making a difference, talking to your friends about what’s going on. I can’t reach your friends, but you can.”

By late afternoon on Tuesday in Brooklyn, Terrence planned to continue rallying voters until polls were closed. He said felt watching the election returns would give him the same feeling as watching the New York Knicks play – you had no idea if you were going to win.

“I have a whole lot of emotions,” Terrence said. “I’m more anxious than excited. I remember when Obama was running and everybody went out. I see that same energy now. So I’m really excited to see what happens.”

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Offset runs into trouble while trying to feed voters on line in Georgia

Offset lent his talents to The Lincoln Project to help get out the vote in Atlanta

Rapper Offset joined up with The Lincoln Project to provide further incentives to Georgia voters to vote. The rapper was scheduled to use his celebrity to support voters on long lines to vote in Georgia providing moral support and vegan food from Atlanta’s famed Slutty Vegan restaurant as well as Big Dave’s Cheesteak for those with more carnivorous leanings.

The Lincoln Project is a group of conservatives and Republicans who have united over their desire to propel Trump out of office. They’ve released some of the ads most critical to the 45th president during the election run-up, including powerful words from a press conference this year from former L.A. Clippers coach Doc Rivers.

Read More: Doc Rivers’ impassioned speech on race turned into ad by conservatives against Trump

But somewhere things went awry with Offset as The Lincoln Project tweeted that the Migos rapper was threatened by officials from Gwinnett county. Offset was scheduled to make appearances at Fickett Elementary and William Walker Rec Center, both in Atlanta.

For anyone outside of Atlanta, Gwinnett county covers a suburban swatch of the city, including areas like Dunwoody, Norcross and Peachtree Corners. Further details of any incident were not provided but it appears that something happened that Gwinnett county officials had issues with.

Offset in Atlanta on Election Day working with The Lincoln Project to get out the vote. (The Lincoln Project)

As Offset said that he did vote today, perhaps he was threatened for some reason while voting in his own swanky neighborhood. It is not, as several commenters on social media said today, illegal to provide food and refreshments to voters waiting on line. It is only a problem if you try to sway voters vote for one candidate or another.

The good news is, he voted.

There was no sign of Offset’s on-and-off-wife, Cardi B. at the voting booth with her husband, though that certainly just means that they didn’t vote together, at least as far as we know. The couple recently reconciled after Cardi filed for divorce, but she has now officially withdrawn the petition. As theGrio reported, Cardi said that she wanted the public to know her relationship was just as dysfunctional as anyone else’s while adding in her no-BS way that she missed ‘intimacy’ with her husband. But of course, she didn’t say intimacy.

Read More: Long lines, enthusiasm but no major problems as US votes

Offset, born Kiari Kentrell Cephus, is an Atlanta native. He and Cardi, born Belcalis Almanzár in New York City are parents to daughter Kulture, 2. Cardi has used her platform to support Democratic and progressive causes, doing an interview with Joe Biden for Elle magazine in August.

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Voting in Georgia remains mainly smooth, with a few hiccups

Polls in Spalding County, Georgia will stay open to 9 p.m. due to technical glitches

ATLANTA (AP) — Despite some technical problems, voting in Georgia on Tuesday got off to a mostly smooth start — a marked departure from a June primary that required some voters to wait in line for hours to cast their ballots.

People lined up outside polling places before they opened at 7 a.m. but the average wait was down to 12 minutes a little less than an hour later, the secretary of state’s office announced.

“We are having a successful election in Georgia today,” Secretary of State Brad Raffensperger said with roughly five hours of voting still to go.

Read More: Here’s how Facebook, Twitter and YouTube are handling Election Day

Raffensperger credited the large numbers of people who voted ahead of Election Day. A record of nearly 2.7 million voters cast their ballots during the state’s three-week early in-person voting period. Another 1.5 million absentee ballots had been received and accepted.

The primary was the first statewide election carried out on the new election system the state bought for more than $100 million last year from Dominion Voting Systems. The system includes touchscreen voting machines that print paper ballots for voters to insert into scanners, which read a barcode to record and tally the votes.

There were some problems. An apparent database error affected all polling sites in Spalding County about 40 miles (64 kilometers) south of Atlanta, where voters encountered delays after electronic ballots wouldn’t load on touchscreen voting machines. Poll workers switched to a manual process and voting continued. Eight of the 18 locations were operating normally by the afternoon, according to Gabe Sterling with the Secretary of State’s Office, but a court order will keep polls open until 9 p.m.

Four of seven locations that experienced technical problems in Morgan County east of Atlanta also were running normally later Tuesday, as was Morris Brandon Elementary School in Atlanta, where voters initially were forced to cast paper ballots instead of voting on machines.

A judge ordered two polling sites in DeKalb County to remain open past 7 p.m. because they opened late. One in Atlanta will be open until 7:45 p.m. and one in neighboring Decatur will be open until 7:40 p.m.

“This extension was requested, in an abundance of caution, to ensure that all electors at the locations have the required full 12 hours of voting,” according to a county news release.

A polling place in Cobb County, in Atlanta’s northwest suburbs, was to stay open until 7:20 p.m. because a poll manager overslept and it opened late, elections director Janine Eveler said.

One polling place in Gwinnett County, in Atlanta’s northeast suburbs, was also to stay open until 7:20 p.m., according to a court order.

Voting in the suburb of Powder Springs northwest of Atlanta, Susan Spence, a supporter for President Donald Trump, said she feels “terrified in a world with Biden, absolutely terrified.”

“I’m here because I believe in Americanism, not socialism,” said Spence, a 69-year-old retired teacher.

A voter with a Black Lives Matter mask reviews her ballot before dropping it off at Lucky Shoals Park Community Recreation Center in Norcross, Ga., on Tuesday, Nov. 3, 2020. (Casey Sykes/Atlanta Journal-Constitution via AP)

But Cynthia McDonald, a 52-year-old consultant in Sandy Springs who voted early for Biden, compared Trump to a catastrophe.

“It’s kind of like a train wreck that you can’t look away from,” she said. “Then you realize you’re not watching the train wreck, you’re on the damn train!”

Kelvin Hardnett stood in line in near-freezing weather for nearly an hour before polls opened at the Cobb County Civic Center outside Atlanta.

“I believe there’s a lot of division and separation,” said Hardnett, 36, who works for a security firm. “And I believe that once we get past the names and the titles and the personal agendas, then you know, we can focus on some real issues.”

A poll worker talks to a voter before they vote on a paper ballot on Election Day in Atlanta on Tuesday, Nov. 3, 2020. (AP Photo/Brynn Anderson)

A combination of factors contributed to long lines in June, including equipment problems, coronavirus-related poll worker shortages and consolidation of polling places. Voters also queued for hours during early in-person voting last month, with some waiting more than eight hours to cast a ballot.

The coronavirus outbreak complicated training on the new system and many experienced poll workers dropped out ahead of the primary, fearing exposure to the virus. Since then, thousands of new poll workers have been recruited and trained, and election officials organized an army of technicians to be on hand to troubleshoot any equipment problems.

Read More: Vermont GOP Gov. Phil Scott votes for Biden over Trump

Raffensperger has said his office reviewed wait times and check-in times for precincts across the state after the primary, along with the number of registered voters, turnout and equipment distribution. They then advised counties to add more voting equipment in some places or to split precincts. That has resulted in several hundred new polling places for the general election, he said.

Fulton County alone added 91 polling places, bringing the total from 164 for the primary to 255 for the general election, according to elections director Rick Barron.

“We’ve had minimal lines throughout the county,” Barron told reporters on Tuesday morning. “It always helps when you have robust turnout during early voting to alleviate issues that can crop up on election day.”

___

Associated Press writers Jeff Martin, Ben Nadler, Sophia Tulp and Christina Cassidy contributed reporting.

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Despite Hacking Fears, Election Day Has a Mostly Smooth Start

Plenty of hours remain. But so far, the worst-case scenarios about ransomware and other meltdowns have seemingly not come to pass.

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Monday, November 2, 2020

A Process to minimize the gap between research and its applications

Human history is numerous pieces of evidence, doctrine, theologies through logic, and by extensive research in every field exists in the universe. 

There is a huge gap between research and its practical application. Studies should conduct with enormous responsibility with extreme efforts, but which has a very minimal effect on real-world problems. The majority of the research across the globe appears only in a few journals (s) /books / digital form or in a printed manifestation only that is forgotten by the real-world at the earliest and in the name of the new paradigm of investigate research they are re-inventing the wheel. A huge of this knowledge has been unused or never have the intention of using this with due diligence incomprehension or non-availability to the generations. Which is causing wasting valuable resources of an individual’s/organizations/ educational institutions and might be an enormous burden to their research and findings.

The previous research should be made available to the researchers across the globe to have unique research topics and to get valuable research findings. When any research conducted should not be based on individual preferences (or) benefits to them but keep humanity facing problems as a high priority and inclination to conduct studies.

The best and most resilient and most welcoming choice to reduce this gap is as follows:

  • It should be a need of the hour for global research institutions and corporate organizations should come together to co-operate and co-ordinate in conducting research
  • share common objectives, preferences, benefits and should encourage researchers to work on real-world issues
  • also, fund them to speed up the understanding and resolve the existing problems that the human race challenges in every aspect of their life and that can encourage humans to solve issues collectively
  • hence, establish global peace and transform the world as a universal safest place for living.

In this contemporary world, using the available technology, architecture, and computing power with artificial intelligence (AI) algorithms can effortlessly summarize the subsist research findings. It can have also help to find the research gaps and future research needs. These algorithmic findings are certainly guidance to the upcoming researchers to create their research objectives and motivate them to provide logic and enormous power to provide, investigate and find solutions where the to the problems in a better/optimal way to scale it up and implement across the globe.

Companies like Google, IBM Watson have already established their NLP tools to summarise the text information to a certain extent. Such companies can co-operate and co-ordinate with the research insinuations and then provide the unique methodologies which can be another level of the business model for the benefit of societies and companies as well.

It’s global researchers’ responsibility to avoid or not to spread the misleading research findings that are confusing to the entire communities across the globe; they should also stop the biased results. Many types of research have ushers to show their presence, which does not significantly have any impact on real-world issues. This habit should stop at the earliest or should able to use these capabilities, funds to find real solutions. And it’s also a huge responsibility to accept the bitter truth research findings and should also adopt.

Finally, exchange ideas and research findings will always help to build good societies for the human race around the globe.

I would be happy to receive your feedback or thought process to enhance this idea to be implemented. Please contact me @ varadivk@gmail.com or +91-7829033033 to discuss further.



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Digital Transformation in the age of COVID-19

COVID-19, by limiting us to our homes and bringing the global economy to a standstill has proved that the world healthcare ecosystem is not prepared for a pandemic. However, what it did teach us is that as consumers we are prepared to adopt the digital era in all life facets.  

This new found pro digital movement, however, has shown a glaring picture as well - despite of the preparatory stages that businesses and governments had entered into years ago, there still exists a disequilibrium )of sky ground size) in the demand of going digital and supply of digital solutions support. 

To close the gap, businesses which had mapped their digital strategies in two to three years phases have brought down the initiative activation milestone to as low as a couple of days and weeks. 

In a European survey, nearly 70 percent of executives from regions like Germany, Switzerland, and Austria, said that the pandemic is possibly going to speed up their digital transformation efforts. This speedening is visible across a range of geographies and sectors.

Consider how:

  • their physical banking channels online. 
  • How the healthcare service providers have moved into telehealth while the insurers have started focusing on self-service assessment of claims. 
  • And the retailers have started focusing on contactless purchasing and delivery. 

A trend that we are seeing emerging is that digital foundations are helping top cream companies adapt and grow in the crisis situation quickly. Brands like Walmart, Amazon, Citrix, and Netflix etc. which are known to be the digital leaders are performing a lot better in this crisis - we are constantly seeing them doubling down their investments for widening the gap. On the other hand, the laggards still have a scope of catching up if they jump-start the digital chart at a greater speed. 

When we work with clients on their digital transformation journey, most of the CEO/CMO executives tell us that while they understand the end goals and the fact that it has become the only survival mode, they are unsure of how to get there with confidence and godspeed. 

What we suggest to them is to look into where they currently stand in addition to lowering their expectations. The reality for companies that have never been digital or have been keeping adoption their third or fourth priority is that they cannot just wake up one day and reduce costs and change how their employees view digital transformation and customers expectations - all the while pivoting toward newer growth opportunities.  

Once they realize where they presently stand and how far the bar has been raised, we start at a point where they understand the need better. This is where we help them bounce ahead from competition by helping them rethink transformation through these practices:

Cloud Migration

Digital leaders are able to develop a digital base and scale it across the business when they have a strong foundation in cloud. A foundation that is built on efficiency, innovation, and talent based advantages for delivering outcomes fast and differently. 

We ask them to make a cloud migration and expertise a leadership level agenda. We ask them to set a target of shifting a minimum of 60% of their business on the cloud in the next quarter.

Go Back to the New Basics

A good amount of clients that come to us seeking help with their digital transformation needs are top in their industries. However, for achieving true digital transformations, businesses have to relook and redefine their traditional modes of doing a process and delivering values. We ask them to learn from their employees, clients, and the emerging digital-only competitors to know how they are approaching the service delivery that they are. 

According to a McKinsey report, bold moves taken to adopt digital technologies at scale and early when combined with greater allocation of digital-focused resources aligns with high value creation. 

Retain forced “agility”

The moment the coronavirus was announced to be transmitted through physical spaces and interactions, the foundation of work from the office fell down like a house of cards.  Almost overnight, businesses became digital enough to enable organization-wide remote working. What was then forced has become a new trend now with employees and executives alike saying that they don’t want to go back. 

To retain this speed in digital adoption, look back at the challenges you faced - internally and externally - which prevented you from achieving your goals. Then, develop lean processes to aid decision making and streamline the procurement process, evolve the culture for aiding new working methods. 

In the situations of extreme unclarity, where we are living under today, the leadership teams have to learn what is working for them and what is not, quickly. This calls for identifying and leaning unknown elements as and when they appear. 

Refocus on Technologies 

The sudden shift to the virtual interactions and operations both outside and inside the organization offers an opportunity for speed up the process of learning about and adopting new technologies which your businesses must have only started experimenting with. 

Up until this point, as CEOs and CMOs you must have realized the pain points in the present technology stack. You also must have gotten a preview on the impact that the technology stack would have if carried forward. 

In the ode of adopting new technologies, we help our clients look at the process on these grounds:

  • Scalability - ever since you have shifted to virtual delivery of your services, have you been able to maintain the customer inflow and acquisition or has the number lowered. If it’s the same, is your digital architecture prepared to increase the count? For improving scalability, we generally advise our clients to work on their backend by moving to microservice architecture and leg up their cloud migration efforts. 
  • Data security - were there any data breaches you faced when you shifted to remote working mode and the subsequent data sharing practices? If yes, you can look into technologies like AI, Blockchain, IoT etc to make the data movement secure in the future. 
  • Usability - before the crisis, the consumers and business partners had little choice in how they accessed your services or products through the new digital offerings. The options, however, have expanded at a stage where we are coming out of the eye of the crisis. 

Relook your offerings - if they stack up your internal and external stakeholders expectations. If the usability is low, any digital consultancy firm would advise you to work on improving it by learning from your customers and employees. 

Expedite the Outcome 

The only way businesses can take advantage of digital-movement friendly time is by developing a culture of constant innovation. They should begin by developing a task force in businesses to look at contributing external factors, review the internal processes and limitations, identify new opportunities, and all the while, keep an eye on competition. 

It has become all the more crucial for them to partner with an external digital transformation consultancy firm which can help their team and processes understand what is lacking and look at new opportunities from a digital perspective. The opportunities should then be combined with a new fail-fast culture that helps in understanding customers' needs which are rapidly changing and then create prototypes to gain customers’ feedback and see how digital tools help move them into becoming loyal consumers. 

Accept that Perfection is Good’s Enemy

In our experience, there’s nothing that pulls back an organization’s digital adoption efforts than them aiming to be perfect - the perfect digital message, perfect tools, perfect optimization, etc. the sudden nature of COVID-19 has given birth to a shift from “after months of hypothesis and A/B testing, we have assembled the best digital plan” to “it works”. 

The present time has gotten the Agile Manifesto concept of “Working Software” the rightful space under the sun that it deserves.  

Parting Statement

It is more or less the rule of human nature that the best learnings happen in some of the most uncertain and devastating times. The present coronavirus crisis fits all the boxes of being an uncertain and devastating event. 

We know that the companies and even industries which simultaneously learn the newness and are open and quick to adapt them with the help of acceleration that digital offerings provide will be able to rise above day-to-day digital demands. The unique insights that they will draw from their employees and customers at this point will help them ensure that the digital future is a lot more robust as we come out of the COVID-19 crisis than it was when we were coming in.



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4 Powerful Use Cases for Data Science in Finance

Data-driven solutions play a fundamental role in enhancing the services and profit margins of modern businesses in the finance sector. JP Morgan, one of the USA’s largest banking institutions, invests $11.5 billion a year in new technologies for this purpose. The company’s machine learning-based COiN platform reviews 12,000 annual commercial loan agreements in just a few hours, as opposed to the 360,000 man-hours it would take to do so manually. The benefits of applying data science in finance are diverse. And this is just one example.
There are a plethora of success stories demonstrating how major financial players capitalise on their data. But what's the significance of data science in finance now, in particular?
The coronavirus pandemic and the global measures that have followed have created a perfect economic storm. The financial sector stands at the front line of a growing credit crisis, with banks trying to manage disruption and maintain strict compliance amid social distancing guidelines which are at odds with their processes. Then there are the extraordinarily low interest rates and increasingly cash-insecure consumers to contend with. Some of the biggest banking challenges posed by the pandemic are:
  • Prioritising resources to cover the most critical business processes. Like many industries, the banking sector has found itself scrambling for answers and slow to make decisions on resourcing capacity, because it lacked an adequate data repository.
  • Delivering financial services off-site. Some essential financial operations, like branch banking, treasury or settlements, can only be done on-site. And the lack of a comprehensive customer database has prevented banks from being able to promptly accept and process payments from different accounts.
  • Dealing with the rising number of fraud cases. There have been numerous cases of critical data theft since COVID-19 first appeared. With rigorous data analysis, suspicious transactions could have been identified sooner and monetary fraud prevented.

To navigate the immediate obstacles, financial institutions must assess short-to-medium-term financial risks and adapt to new ways of operating in a post-pandemic world. Data science can be a powerful tool in finance, aiding risk management and continuity planning so that the industry is better prepared when the next challenge arises.

4 ways to harness data science within finance

A recent report from the World Economic Forum predicts that 463 exabytes of data will be generated daily by 2025. That‘s equal to 212 million DVDs a day, with an almost incomprehensible amount of actionable insights. Here are four key examples of how insurance, banking and investment companies can use data science to innovate the financial field.

1. Detect and prevent fraud

According to the American Bankers Association, banking institutions prevented $22 billion worth of fraudulent transactions in 2018. Now, using solutions powered by machine learning technologies, the finance industry is aiming at real-time fraud detection to minimise losses.

Machine learning enables the creation of algorithms that can learn from data, spot any unusual user behaviour, predict risks, and automatically notify financial companies of a threat. Data science helps banks recognise:

  • Fake insurance claims. With the help of machine learning algorithms, data provided by insurance agents, police, or clients can be analysed to spot inconsistencies more accurately than with manual checks.
  • Duplicate transactions and insurance claims. Duplicated invoices or claims aren’t always sinister, but machine learning algorithms can distinguish between an accidental click and a premeditated fraud attempt, thus preventing financial losses.
  • Account theft and suspicious transactions. Algorithms can analyse a user’s routine transactional data, then any suspicious activity can be flagged and verified by the card owner.

2. Manage customer data more efficiently

Financial institutions are responsible for managing vast amounts of customer data – transactions, mobile interactions and social media activity. This information can be categorised as “structured” or “unstructured” – the latter posing a real challenge when it comes to processing.

Employing data science within finance helps companies manage and store customers’ data far more efficiently. Firms can boost profits using AI-driven tools and technologies such as natural language processing (NLP), data mining and text analytics, while machine learning algorithms analyse data, identify valuable insights and suggest better business solutions.

3. Enable data-driven risk assessment

The financial industry faces potential risks from competitors, credits, volatile markets and more. Data science can help finance firms analyse their data to proactively identify such risks, monitor them, then prioritise and address them if investments become vulnerable.

Financial traders, managers, and investors can make reliable predictions around trading, based on past and present data. Data science can analyse the market landscape and customer data in real time, enabling financial specialists to take action to mitigate risks.

Data science can also be used in finance to implement a credit scoring algorithm. Using the wealth of available customer data, it can analyse transactions and verify creditworthiness far more efficiently.

4. Leverage customer analytics and personalisation

Data science is a powerful tool for helping financial institutions understand customers. Machine learning algorithms are able to gather insights on clients’ preferences, to improve personalisation and build predictive models of behaviour. Meanwhile, NLP and voice recognition software can improve communication with consumers. Thus, financial institutions can optimise business decisions and offer enhanced customer service.

Studying behavioural trends allows financial institutions to predict each consumer’s actions. Insurance companies use consumer analysis to minimise losses by defining below zero customers and measuring customer “lifetime value”.

Conclusion

The use of data science in the financial sector goes beyond fraud, risk management and customer analysis. Financial institutions can harness machine learning algorithms to automate business processes and improve security.

By using data science within finance, companies have new opportunities to win customer loyalty, safeguard their profits and stay competitive.

Originally published here



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Data Science Movies Recommendation System

Nearly everybody wants to invest their recreation energy to watch motion pictures with their loved ones. We as a whole have a similar encounter when we sit on our lounge chair to pick a film that we will watch and go through the following two hours yet can't discover one following 20 minutes. It is so baffling. We unquestionably need a PC operator to give film proposals to us when we have to pick a film and spare our time.

Evidently, a film suggestion specialist has just become a fundamental aspect of our life. As indicated by Data Science Central "Albeit hard information is hard to obtain, many educated sources gauge that, for the significant online business stages like Amazon and Netflix, that recommenders might be liable for as much as 10% to 25% of steady income."

What is recommender System?

There are two types of recommendation systems. They are:

Content-Based Recommender System

A content-based recommender system functions on a user's generated data. We can create the data either directly (such as clicking likes) or indirectly (such as clicking links). This information is used to create a personal profile for the personal that includes the metadata of the user-interacted objects. The more reliable the device or engine collects results, the Interactive Recommender System becomes.

Collaborative Recommender System

A collaborative recommender system makes a suggestion based on how the item was liked by related people. Users with common preferences would be grouped by the system. Recommender schemes can also conduct mutual filtering using object similarities in addition to user similarities (such as 'Users who liked this object X also liked Y'). Most systems will be a combination of these two methods.

It is not a novel idea to make suggestions. Even if e-commerce was not so prevalent, retail store sales workers promoted goods to consumers for the purpose of upselling and cross-selling, eventually optimising profit. The goal of the recommendation programmes is exactly the same.

The recommendation system's other goal is to achieve customer satisfaction by delivering valuable content and optimising the time a person spends on your website or channel. It also tends to increase the commitment of customers. On the other hand, ad budgets can be tailored only for those who have a tendency to respond to them by highlighting products and services.

Why Recommendation systems?

1. They assist the customer with identifying objects of interest
2. Helps the provider of products distribute their products to the proper customer
(a) To classify, for each consumer, the most appropriate products
(b) Display each user customised content
(c) Recommend the correct customer with top deals and discounts
3. User interaction will enhance websites
4. This raises company profits by increased consumption.

Daily Life Examples of Movies Recommender Systems:

1.GroupLens
a) Helped in developing initial recommender systems by pioneering collaborative filtering model.
b) It also provided many data-sets to train models including Movie Lens and Book Lens

2. Amazon
a) Implemented commercial recommender systems
b) They also implemented a lot of computational improvements

3. Netflix
a) Pioneered Latent Factor/ Matrix Factorization models


4. Google
a) Search results in search bar
b) Gmail typing next word

5. YouTube
a) Making a playlist
b) Suggesting same Genre videos
c) Hybrid Recommendation Systems
d) Deep Learning based systems

Let’s go with the Coding part. The dataset link is: https://www.kaggle.com/rounakbanik/the-movies-dataset

 import pandas as pd  import numpy as np 
 df1=pd.read_csv('../input/movies-dataset/movie_dataset.csv')
df1.columns
df1.head(5)
import matplotlib.pyplot as plt
rich=df1.sort_values('budget',ascending=False)
fig, ax = plt.subplots()
rects1 = ax.bar(rich['title'].head(15),rich['budget'].head(15),
color=["Red","Orange","Yellow","Green","Blue"])
plt.xlabel("Movie Title")
plt.rcParams["figure.figsize"] = (50,50)
plt.title("Budget Wise top movies")
plt.ylabel("Movie Budeget")
def autolabel(rects):
for rect in rects:
height = rect.get_height()
ax.text(rect.get_x() + rect.get_width()/2., 1.05*height,
'%f' % float(height/100000),
ha='center', va='bottom')
autolabel(rects1)
plt.xticks(rotation=90)
plt.show()
rich1=df1.sort_values('vote_average',ascending=False)
rich1.head()
fig, ax = plt.subplots()
rects1 = ax.bar(rich1['title'].head(20),rich1['vote_average'].head(20),
color=["Red","Orange","Yellow","Green","Blue"])
plt.xlabel("Movie Title")
plt.rcParams["figure.figsize"] = (30,20)
plt.title("Rating Wise top movies")
plt.ylabel("Average rating")
def autolabel(rects):
for rect in rects:
height = rect.get_height()
ax.text(rect.get_x() + rect.get_width()/2., 1.05*height,
'%f' % float(height),
ha='center', va='bottom')
autolabel(rects1)
plt.xticks(rotation=90)
plt.show()
C= df1['vote_average'].mean()
print(C)
m= df1['vote_count'].quantile(0.9)
q_movies = df1.copy().loc[df1['vote_count'] >= m]
q_movies.shape
def weightedrating(x,m=m,C=C):
v = x['vote_count']
R = x['vote_average']
# Calculation based on the IMDB formula
return (v/(v+m) * R) + (m/(m+v) * C)
# A new column for weighted rating named weight_score in the dataset
q_movies['weight_score'] = q_movies.apply(weightedrating, axis=1)
#Sort movies based on score calculated above
q_movies = q_movies.sort_values('weight_score', ascending=False)
#Print the top 20 movies
q_movies[['title', 'vote_count', 'vote_average', 'weight_score']].head(20)
pop= df1.sort_values('popularity', ascending=False)
import matplotlib.pyplot as plt
plt.figure(figsize=(12,4))
plt.barh(pop['title'].head(5),pop['popularity'].head(5), align='center',
color=['red','pink','orange','yellow','green'])
plt.gca().invert_yaxis()
plt.xlabel("Popularity")
plt.title("Popular Movies")
df1['overview'].head(5)
features = ['keywords','cast','genres','director']
##Step 3: Create a column in DF which combines all selected features
for feature in features:
df1[feature] = df1[feature].fillna('')
def combine_features(row):
try:
return row['keywords'] +" "+row['cast']+" "+row["genres"]+" "+row["director"]
except:
print("Error:", row)
df1["combined_features"] = df1.apply(combine_features,axis=1)
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.metrics.pairwise import cosine_similarity
cv = CountVectorizer()
count_matrix = cv.fit_transform(df1["combined_features"])
##Step 5: Compute the Cosine Similarity based on the count_matrix
cosine_sim = cosine_similarity(count_matrix)
sim_df = pd.DataFrame(cosine_sim,index=df1.title,columns=df1.title)
sim_df.head()
movie_user_likes = "Avatar"
sim_df[movie_user_likes].sort_values(ascending=False)[:20]
movie_user_likes = "Gravity"
sim_df[movie_user_likes].sort_values(ascending=False)[:20]
from scipy import sparse
from sklearn.metrics.pairwise import cosine_similarity
ratings = pd.read_csv("../input/colab-fitting/toy_dataset.csv",index_col=0)
ratings = ratings.fillna(0)
ratings
def standardize(row):
new_row = (row - row.mean())/(row.max()-row.min())
return new_row
ratings_std = ratings.apply(standardize)
item_similarity = cosine_similarity(ratings_std.T)
print(item_similarity)
item_similarity_df =
pd.DataFrame(item_similarity,index=ratings.columns,columns=ratings.columns)
item_similarity_df
def get_similar_movies(movie_name,user_rating):
similar_score = item_similarity_df[movie_name]*(user_rating-2.5)
similar_score = similar_score.sort_values(ascending=False)
return similar_score
print(get_similar_movies("romantic3",1))
action_lover = [("action1",5),("romantic2",1),("romantic3",1)]
similar_movies = pd.DataFrame()
for movie,rating in action_lover:
similar_movies = similar_movies.append(get_similar_movies(movie,rating),ignore_index=True)
similar_movies.head()
similar_movies.sum().sort_values(ascending=False)

In case the user or the movie is very new, we do not have many records to predict results. In such cases, the last value in the prediction will appear in recommendations and the performance of the recommendation system by comparing predicted values and original rating values. We will calculate the ‘RMSE’ (root mean squared error) value. In this case, the RMSE value is 0.9313, which one can judge if it is good or bad depending on the size of the dataset.

Disadvantages of Movie Recommendation system

It does not work for a new user who has not rated any item yet as enough ratings are required content-based recommender evaluates the user preferences and provides accurate recommendations.
No recommendation of serendipitous items.
Limited Content Analysis- The recommender does not work if the system fails to distinguish the items that a user likes from the items that he does not like.

Conclusion

In this article we discussed about recommender system, recommendation systems, daily real life examples and disadvantages of data science movie recommendation system.

Author Bio

Rohit Sharma is the Program Director for the upGrad-IIIT Bangalore, PG Diploma Data Analytics Program, one of the leading data science courses. Motivated to leverage technology to solve problems. Working on solving problems of scale and long term technology strategy.



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AI Generated Avatars Becoming Digital Influencers

As the recent rise in Covid-19 threatens once again to shutter advertising agencies, film studios, and similar media "factories" globally, a quiet, desperate shift is taking place in the creation of new media, brought about by increasingly sophisticated AI capabilities. A new spate of actors and models are making their way to people's screens, such as pink-haired Imma, above, who has developed an extensive following in Japan on Instagram and TikTok, and is appearing increasingly on the covers of Japanese magazines.

She also doesn't exist.

Imma joins a growing host of digital avatars who are replacing human actors, models, and photographers with computer-generated equivalents. Cloud-based GPUs and sophisticated game and modeling software have increasingly attracted the attention of a new generation of artist/programmers who are taking advantage of this to generate images, video, and audio that are becoming increasingly indistinguishable from reality, especially when that reality is otherwise captured via jump cuts, and matte overlays that have made tools such as TikTok and Reels the primary tools for video production for the typical Instagram celebrity.

The business potential for such virtual models and spokespeople is huge, according to a recent piece by Bloomberg on digital avatars. Such avatars have obvious benefits over their flesh and blood counterparts. They can appear in print or video anywhere - on a far-off beach, on a busy street in a bustling city, or staring out at dirigibles and flying saucers while taking a taxi above the clouds - without ever having to send a crew out for several days to some otherwise uninhabited Caribbean beach, reserving expensive permits for filming or dealing with observers, or spending a great deal of time with specialized green screen effects.

The models don't age out of roles, don't have bad hair days, or become prima donnas. The initial cost to develop such models may be fairly high (though seldom more than the cost of sending models and crew to a tropical island) but once created, that model becomes highly malleable, and can be used in a large number of different situations.

Ordinarily, these changes have been on the horizon for a while, and until the pandemic, the use of such models was increasing slowly anyway. Yet as for so many other things, the pandemic shifted the need for virtual models and actors into overdrive, as social distancing requirements and lockdowns put a very real limit on the ability of creative agencies to put together content with live actors.

It is significant, for instance, that The Walt Disney Company, which had already invested heavily in the use of CGI-based actors and props for its wildly popular series The Mandalorian, was able to finish production on the awaited second season of that show so quickly after California's Governor Newcom started loosening the limits on production. It did so by taking advantage of the hyperrealistic rendering capabilities of graphical processing units (GPUs) which are now capable of extensive texture mapping, shading, ray tracing, subdermal lighting and so forth by dint of the GPU architectures that were optimized for better gameplay.

Moreover, such processing can readily be done in parallel across multiple dedicated cloud processors, which not only increases the render time dramatically but also makes modeling, rigging (the process of positioning objects relative to one another) and lighting take far less time than they would on a single laptop. This also makes procedural shaders, which handle the animation of everything from hair to skin to dirt to water and smoke, feasible to the home-bound graphic artist or designer. Companies such as nVidia have partnered with cloud providers to make racks of GPUs acting in parallel available to anyone with a decent Internet connection even without necessarily needing to have such GPUs available on the artist's computers directly. 

This process is also driven by the rise of generative adversarial networks (a form of neural network that is able to take related types of images and build subtle composites that can then be evaluated to determine the "verisimilitude" of a given image. Those that survive are then used as the basis for other such images. When used as is, such GANs are remarkably effective at creating realistic portraits of people quickly, while at the same time also providing templates for the generation of models underlying such templates that can then be used for simulating action. The StyleGan2 algorithms drive the site This Person Does Not Exist, which generates unique, very realistic facial images. The site also contains detailed information about the StyleGan2 algorithms involved in the process.

The ability to create such realistic avatars has also led to the rise of fake identities in social media sites, as people take advantage of such tools to either disguise themselves on places as diverse as Facebook and Tinder, or simulate fake profiles for spamming and trolling, or, in at least a couple of cases, creating faked dossiers for political mischief, complete with people who existed only within a GPU. 

StyleGan2, in conjunction with similar research for capturing facial orientation and lip-synch movements, are also changing the nature of gaming as the ability to wear avatars that are able to speak and make facial gestures. From pre-generated audio recorded live, or text-to-speech interfaces such as are used to power a host of verbal virtual assistants (Siri being the Ur example), such viseme-matching algorithms are increasingly putting a face to what once had been primarily audio only "digital-companions".  

It is very likely that, for good or ill, this particular area of development will become one of the hottest faces of the AI movement. If the Japanese experience is any indication, such "Virtual Ambassadors" may very well become celebrities in their own rights. In many cases, the environments for creating such virtual models are likely to be the same -platforms that currently are used for developing immersive reality games, such as Microsoft's Unreal Engine or  Reallusion's Character Creator platform. As the pandemic continues to change how we work, it is likely that the next generation of advertising, media creation and immersive gaming will rely upon these virtual avatars, the next general of digital influencers.

Kurt Cagle is the Community Editor for Data Science Central.



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