WAR OF WRATH

WAR OF WRATH

Heads were lost! Arms were ripped from bodies! 

Chaos isn't a pit. Chaos is a ladder. Many who try to climb it fail and never get to try again. The fall breaks them. And some, are given a chance to climb. They refuse, they cling to the realm or the gods or love. Illusions. Only the ladder is real. The climb is all there is. And when chaos wasn’t erupting on Westeros, we found out where the loyalties of Queen Cersei and King Joffrey lie.

“What killed him?” Lord Stark asked the monster, who demands us to pay loyalties towards him.

“Loyalty, never,” the wise-beyond-her-years Sansa Stark replied.

“I will take what is mine, with fire and blood. My reign has just begun. When the sun rises in the west, and sets in the east, then you shall return to me, my sun and stars. I will answer injustice with justice”, said Daenerys.

Lord Stark called in for a peace, but Joffery's honor had really gone to the dogs. I never witnessed anything as such. I got hurt as Sansa pushed me aside. Holy Gods, we were safe.

‘Drogon. Rhaegal. Viserion’, she uttered and we were into the air.

Once that murky green liquid took fire, it burnt fiercely until it was no more. Moreover, it seeped into cloth, wood, leather, even steel, so they take fire as well. Wildfire, they call it. Lord Tyrion directed us all to the Mud Gate.

Unfortunately, not all of us. Lord Stark was no more. We kept ourselves into a hiding unless we had an army to fight against. But, we lacked time. The Lannister army was already searching like dogs for us and they may anytime hunt us. 

In the blink of eye, Daenerys rose with Drogon to set fire to the Red Keep. It was insane. She lost Viserion as he was shot by a ballista. This broke her into pieces. She was mad in fury, she started burning the entire King’s Landing, no mercy at all. 

Jon rode Rhaegal meanwhile, to stop her. But, the children, the women, the poor all were victimised by her enrage. Lord Tyrion secretly took us to the weapon room, a room underground, with hoard of weapons. 

With every other thing we could have taken, we burst into the Red Keep. “Deal with all this, live with myself, Neh! I honestly didn't know. 

I stood often enough at the abyss of my soul, asking that same question, looking down into the dark crevices where the black monster dwells on the bottom. He gazed up at me, and I looked him in the eyes. “There you are,” he said, and I almost fell into the void.”

“And then?”, asks Little Sam!

“And then? I turn around and go do what needed to be done. I don’t know whether I cared for my life or not, I just had to kill him. Blood for blood. After that dark night, I always waited for a vengeance, with the monster, and the day came. 

We all were scattered, finding our own ways, to reach the ones who sowed seeds of hatred in our hearts. I was astonished to see Gregor Clegane, Cersei’s bodyguard, how magnificent was he! Jon came along, hunting for Cersei. But, I spotted my goal. 

There, saw him, at the Throne, like a coward. He approached me again, with the same monstrous soul, hoping for my loyalties towards him. I took out the dagger and killed him, eh. 

Relief. I assassinated the dark shadow. I came along out and found the body of Tywin Lannister and Jaime Lannister lying. Sansa and Lord Tyrion killed them. Happiness knocked as we broke part by part the traitors. 

Daenerys started believing that this was our plan to take away the throne from her. Screaming, WHY from the sky, Drogon released plumes of fire upon us. What happened was unbelievable. Rhaegal too streamed a fire, but upon Drogon. 

Arya was perplexed, because only a true Targaryen could control a dragon. Drogon was injured. Daenerys completely broke up now, she stood helpless. 

But, love is of all passions the strongest, for it attacks simultaneously the head, the heart and the senses, and John decided to stick with love. He jumped off Rhaegal to calm Daenerys. For a moment everything freezed. Both of them seemed making love, like never before. 

But, they were tricky, those demons. Could they be trusted? Of course they couldn’t be trusted. She'd created them. She owned them. They would lead her astray, and they took. The Ballista fired, Cersei felt victorious. 

Tears rolled down her eyes amidst her laugh, as Arya hit her dagger through her heart. But it was a little late. Drogon was no more. Everything stopped. Blood poured like tears. It was love that wiped. It was Jon who wiped. 

The more you love, the more you have to give. Love itself comes with a lot of sacrifices. It is the only feeling they had which was infinite and Daenerys forgot about her dragons then. All she needed was love. 

What is love, when it does not get you pain? Jon, never wanted to, but he did. We all just saw it. It was not a murder of passion, rather a murder for peace, the murder of the mad queen, to be. 

He lost his love, he lost his friend. He had nothing to do with the rest of us. He disappeared then, with Rhaegal. Where to, no one knew and he never returned. 

Oh my little Sam, love is always meeting of two souls, where they fully accept the light and dark in each other, bounded by courage to grow through struggle into bliss; but Jon never wanted people to suffer. 

He sacrificed. The pain of his love was such a hit that even the teardrops flowing down felt like a kiss by your father.   

Hope you liked the third saga. Please drop in your reviews and tell us your expectations for the fourth and the final saga. Stay tuned for the final saga, next Sunday at 7:00 pm.

Don't forget to stay at home, and wash hands regularly. God protect us all.

FAKE NEWS DETECTION

Greeting readers,

While researching, we have found many tools and researches in this domain. We tried really hard to come up with the most trending tools. Have a good read while you find WhatsApp case study, Facebook case study, ways to unearth fake news, ways to combat fake news, AI tools, some exemplary researches in this field and ways to check fake news generated by AI chatbots.

FAKE NEWS DETECTION

Today in this era of internet where new digital platforms have unleashed innovative forms of communication and greater global reach, but on the other hand, disinformation and hoaxes that are popularly referred to as “fake news” are accelerating and affecting the way individuals interpret daily developments.

India’s battle against the novel Covid-19 has many impediments – huge population, inadequate infrastructure and many more. But beyond these, familiar foes are rearing their heads: misinformation and fake news.

Not only in this situation of pandemic but also the past records of various situations have proved that a series of fake news and rumours spread like a wildfire in the country. A havoc is created as fake news rise and send shockwaves across the media and the world.

Biggest market for WhatsApp

India is the biggest market for the Facebook-owned messaging application, WhatsApp, with more than 400 million users in a country as per reports of 2019.

Dozens of people have died in mob lynchings by furious crowds during the past four years over WhatsApp rumours. Since the coronavirus outbreak last December in China, misinformation and misleading facts, especially through WhatsApp, have increased, says Shachi Sutaria, a fact checker focused on science and health, with Boom, one of India's leading fact-checking websites. She says:
"Normally, we don't see such high levels of misinformation around health issues in India. Earlier, we would get two to three messages a week on health issues that we would fact check. Now, we get up to five to six messages every day, much of it on coronavirus."[Extracted from her latest interview to Mr. Purohit Jain.]

WhatsApp comes forward for fake news detection

With over four billion users, WhatsApp is one of the most tremendous mobile application in spreading information. That’s why, in order to curb fake news, spread across social media, especially in the crucial time of coronavirus outbreak, WhatsApp developers according to trusted sources have been found to be working on a feature called Search Messages on the Web. 

The version, WhatsApp beta for Android 2.20.94, may bring in a feature that will help WhatsApp users combat fake news and misinformation. The feature called Search Messages on The Web will direct a user to check if a message is true or authentic. It has not been very long since WhatsApp started labelling text messages, photos or videos as forwarded. This is one of the determining factors that would help the user track information which could be misleading. It is already part of beta, is under testing and may roll out in coming months.

But now the question arises that what could be the possible solution to cease this fire. Technologists have been constantly addressing this using Artificial Intelligence and Machine Learning. So,IS ARTIFICIAL INTELLIGENCE-DRIVEN DATA VERACITY THE LENS ON MISINFORMATION?

Let’s check how.

A comprehensive study, in March 2018 , from MIT  looks at a decade of tweets, and finds that not only is the truth slower to spread, but that the threat of bots and the natural network effects of social media are no excuse: we’re doing it to ourselves.

The study looked at the trajectories of more than 100,000 news stories, independently verified or proven false, as they spread (or failed to) on Twitter. The conclusion, as summarized in the abstract: “Falsehood diffused farther, faster, deeper, and more broadly than the truth in all categories of information.”

When it comes to combat rumours, Facebook has emerged as a brave face by using Artificial Intelligence to leverage to search for words or their pattern to check for fake stories.

Facebook: Case Study viz. Fake News Detection

One of the major platforms where fake news is spread mercilessly is Facebook.Since last year, after Zuckerberg’s Congress session, Facebook is trying to curb fake news with new enthusiasm. The efforts, though commendable are not very effective.

Facebook uses various machine learning algorithms to identify hate text and figure out the context of the text but it still depends on manual flagging of fake news. It has got a team of AP behind them which manually flags news as fake or real. One of the major hindrances is the different languages being used on the platform and the lack of language specific reviewer.

ML is also used to generate fake news which is more sophisticated and that leads to the probability of their detection being very less. For now, manual detection and reporting of news is the best way Facebook can curb fake news.

AI is now looked as a turning point in the detection and checking of fake news.
AI enables to understand behaviours, through pattern recognition and taking the help from stories that were flagged as fake in the past. As the volume of data increases day-by-day, so is the need to handle hoaxes. AI has turned into a beacon of hope for assurance of data veracity and fake news detection, majorly.

So, now the question arises, HOW TO DEAL WITH MISINFORMATION DYNAMICS? Misinformation dynamics tends to link the fake news to big data concept called data veracity. Reports suggest that AI again enables us to sort this problem.

METHODS TO UNEARTH FAKE NEWS

AI is all set to identify fake news as we are keen to find how. Some methods are:

So, now we would like to bring you some tools that could help combat fake news:

NEWSWHIP

It is a social media engagement tracking firm(www.newswhip.com) that tracks and predicts the impact of millions of stories, empowering the world’s news and communications professionals. It tracks content by amount and location of user engagement and also tracks audience interest and changes in interest over time.

HOW DOES IT WORKS?

1)Social monitoring platform- The social monitoring platforms (NewsWhip Spike), use APIs from leading social platforms to provide accurate and real-time insights into the stories, videos, pictures and topics that are spreading fastest on social media using an algorithm, to provide a picture of what content is getting attention among different audiences.

2) Social media intelligence-The NewsWhip Spike and the social analytics platform NewsWhip Analytics utilize the data signals like the social media reactions to provide content intelligence.

3) Facebook analytics tool- NewsWhip Analytics provides insight into the responses to the Facebook pages content.

4) Social influencer tracking-Using Newswhip discovery platform one can monitor the social influencers and then using the analytics platform can look at historical trends in social influencer monitoring.

NewsWhip has really great reviews from news agencies, publishers, brands, creative agencies, marketing agencies, PR and communications, governments and non-profit organisations.

SNOPES

Snopes is a fact checking website which has helped in determining the veracity of latest news. The website works by doing extensive research on an article from various sources and then publishing it, hence it is considered as an unimpeachable source of information. The website has been used by prominent newspapers and magazines as well.

CROEDTANGLE

CroEdTangle is a social networking monitoring and content discovery tool for social networks and has multi user capabilities. It has developed an intelligence tool that discovers which posts on various social media pages are performing best and enables news outlets to compare their different account's performance on upto five social accounts on Facebook, Twitter or Reddit.

It is a web based service and integrates with other apps like Slack. Its main users are social media strategists in small, medium and large enterprises. It costs for about $449 per month for one platform,$899 for three platforms and $ 1299 for 5 platforms with an annual contract and scored 86 /100 in the Social Media category on the basis of its user satisfaction with a score of 93/100.

MEEDAN

It is a non-profit, social technology company. It aims to increase global interaction on the web by translating texts in English and Arabic. The technology used is Machine translation and machine augmented translation. People all across the world appreciate the initiative taken by the company and find it user friendly, it makes their work easier. Meanwhile a check is alsolaid on facts and news they translate.

GOOGLE TRENDS

This is a website by Google that analyses the popularity of top search queries in Google search engines. Through this one can detect how search volume has varied for that term over time and in different location. Changes can be made to the location, time frame, category or industry and type of search (web, news, shopping or YouTube) for more fine grained data as shown in the graph.

HOW IT WORKS?

By sampling the Google searches, we can look at its database representative through its graphical representation while finding insights that can be processed within minutes of an event happening in the real world.

NORMALISATION OF DATA

Google Trends normalizes search data to make comparisons between terms easier. Search results are normalized to the time and location of a query by the following process:

• Each data point is divided by the total searches of the geography and time range it represents, to compare relative popularity. Otherwise, places with the most search volume would always be ranked highest.

• The resulting numbers are then scaled on a range of 0 to 100 based on a topic’s proportion to all searches on all topics.

Google trends is very popular among industrialists, competitors and professionals of all major companies across the globe and its Use Cases and Deployment Scope has received great ratings.

LE DECODEURS

Les` Decodeurs or Decoders is an initiative taken in 2014 by the French Daily Newspaper,‘Le Monde.’ It is a section of this newspaper with purpose of verifying information given on various themes. In 2017, those journalists created Decodex, a search engine whose objective is to provide as many simple tools as possible to facilitate the verification of information. The creators believe that maybe it is not possible to verify all the information circulating online but it will offer everyone the means of discerning the most obvious of them, and being warned when consulting them; a site known for spreading false information.

PHEME

Pheme is a tool powered by Artificial Intelligence and Machine Learning algorithms, which has brought about a technology leap to read the veracity of user-generated and online content.

Pheme intends to better understand and automate the question of veracity. The interdisciplinary big data project is being funded by the European Union. The word Pheme is named after the Greek goddess of fame and rumours. It brings together partners from the domains of natural language processing and text mining, web science, social network analysis, and information visualization.

It also aims to develop and release veracity intelligence algorithms as open source material so that we can all benefit from them. Such algorithms could then be applied on social media networks, web search or email systems to detect rumour, lies, or any kind of misinformation being spread.

SOME OTHER WAYS FOR FAKE NEWS DETECTION

Fake news detection through Geometric Deep learning

UK startup ‘Fabula AI’ reckons its devised way for artificial intelligence to help user generated content platforms get on the top of the disinformation crisis that keeps rocking the world of social media with antisocial scandals.

Fabula, which has patented what it dubs a “new class” of machine learning algorithms to detect “fake news” — in the emergent field of “Geometric Deep Learning”; where the datasets to be studied are so large and complex that traditional machine learning techniques struggle to find purchase on this ‘non-Euclidean’ space.

Geometric Deep learning-  It is the class of Deep Leaning that can operate on the non-Euclidean space (like Molecules, Graphs, Trees, Networks etc.) with the goal of teaching models how to perform predictions and classifications on the datatypes.

The approach it’s taking to detect disinformation relies not on algorithms parsing news content to try to identify malicious nonsense but instead looks at how such stuff spreads on social networks — and also therefore who is spreading it.

There are characteristic patterns to how ‘fake news’ spreads vs the genuine article (the MIT study mentioned above).

The essence of geometric deep learning is it can work with network-structured data. So here we can incorporate heterogeneous data such as user characteristics; the social network interactions between users; the spread of the news itself; so many features that otherwise would be impossible to deal with under machine learning techniques.

Fabula envisages its own role, as the company behind the tech, as that of an open, decentralised “truth-risk scoring platform” — akin to a credit referencing agency just related to content, not cash.
Scoring comes into it because the AI generates a score for classifying content based on how confident it is looking at a piece of fake vs true news.

In its own tests Fabula says its algorithms were able to identify 93 percent of “fake news” within hours of dissemination — which is “significantly higher” than any other published method for detecting ‘fake news’.

For their training dataset Fabula relied on true/fake labels attached to news stories by third party fact checking NGOs, including Snopes and PolitiFact. And, overall, pulling together the dataset was a process of “many months”.

Fake news detection through Stance Detection

In a paper presented at the 2019 NeurIPS AI conference, researchers at Darwin AI and Canada’s University of Waterloo presented an AI system that uses advanced language models to automate stance detection, an important first step towards identifying disinformation.

Before creating an AI system that can fight fake news, we must first understand the requirements of verifying the veracity of a claim. In their paper, the AI researchers break down the process into the following steps:

1-Retrieving documents that are relevant to the claim.

2-Detecting the stance or position of those documents with respect to the claim.

3-Calculating a reputation score for the document, based on its source and language quality.

4-Verify the claim based on the information obtained from the relevant documents.

Instead of going for an end-to-end AI-powered fake-news detector that takes a piece of news as input and outputs “fake” or “real”, the researchers focused on the second step of the pipeline. They created an AI algorithm that determines whether a certain document agrees, disagrees, or takes no stance on a specific claim.

The University of Waterloo researchers used a deep bidirectional transformer, RoBERTa, which was developed by Facebook in 2019, is an open source language model.

Transformers, a type of deep learning algorithm, use special techniques to find the relevant bits of information in a sequence of bytes instead. This enables them to become much more memory efficient than other deep learning algorithms in handling large sequences. Transformers are also an unsupervised machine learning algorithm, which means they don’t require the time- and labour-intensive data-labelling work that goes into most contemporary AI work.

For stance detection, the researchers used the dataset used in the Fake News Challenge (FNC-1), a competition launched in 2017 to test and expand the capabilities of AI in detecting online disinformation. The dataset consists of 50,000 articles as training data and a 25,000-article test set. The AI takes as input the headline and text of an article, and outputs the stance of the text relative to the headline. The body of the article may agree or disagree with the claim made in the headline, may discuss it without taking a stance, or may be unrelated to the topic.

The RoBERTa-based stance-detection model presented by the University of Waterloo researchers scored better than the AI models that won the original FNC competition.

A significant advantage of deep bidirectional transformer language models is that we can harness pre-trained models, which have already been trained on very large datasets using significant computing resources, and then fine-tune them for specific tasks such as stance-detection.

THE OTHER SIDE

Every coin has two sides. We have relied so much on AI for checking fake news. But reports also say that AI can be used to spread fake news, write fake reviews and to create a pretend mob of social media users aimed at bombarding comments sections with specific agendas by AI bots.
However, Harvard University and MIT-IBM Watson AI Lab researchers recently developed a new tool that spots text that has been generated by AI.

The tool, called the Giant Language Model Test Room (GLTR), takes advantage of the fact that AI text generators use fairly predictable statistical patterns in text.

While these patterns might not be easy to spot by an average reader, it seems that an algorithm can do a pretty good job at it. The AI tool, essentially, can tell if the text is too predictable to have been written by a human.

How does it work?

GLTR tests for predictability in texts by looking at the statistical probability of one word being chosen after another in a sentence.

We ran the opening passage of 1984 through the tool in order to put George Orwell through his paces — and to prove he wasn't really an AI sent back in time from the future.

Less predictable words are flagged by purple — a sprinkling of these throughout a text shows that it was most likely written by a human hand.

Green words, on the other hand, are the most predictable, while yellow and red fall in between.

Of course, we can envision a future in which text-generating machine-learning tools are trained on these purple words in order to trick GLTR by coming across as more human — here's hoping the GLTR researchers can keep up.

To test GLTR, the researchers asked Harvard students to identify AI-generated text — firstly with the tool, and then without it.

The students only successfully spotted half of all fake texts on their own. With the tool, on the other hand, they spotted 72%.

So, we could conclude that Artificial Intelligence has come up with many ways to unearth the fake news, combat it and even detect fake news spread by itself in other forms.

Thanks for reading. We hope you liked the article and would utilise one of the tools to detect a fake news that reaches you amidst this chaos and confusion. 

IEEE SB NITP would like to once again remind its readers to obey the guidelines as issued by the Government and WHO. Stay at home and be safe. Please drop your views in the comment section.

THE WATCH REMEMBERS

In that time of tribulations, heart ached to hear the demise of the beloved John Arryn when the letter of your father Sam added to the misery. Everyone at Winterfell has believed in the coming dark threat and his theories about the virus, as all of us have faith in him but we were not alone.

There was a need to make everyone believe in it. Lord Eddard Stark has been worried sick about this deadly virus. We all were tensed, but we had to engage ourselves to see the arrangements as Winterfell expected the Baratheons and Lannisters to be there by anytime.

You know, I was not at all contended by this visit. I could see grand preparations everywhere but all I did was missing Sam as the men talked of celebration. Winterfell was in a state of revelry as King Robert announced Ser Eddard to be the new Hand of the King.

A grand feast was thrown on that day, which I didn’t wish to attend in the first place. But I went, as Sansa insisted. Loud music, gala time, Ser Tyrion and his jokes all were good and worth attending for, but the night was dark, rather for me. 

It was something I could never forget and would bring tears in my eyes. I just ran away from the celebration to my room. I was afraid. 

There was a knock at my door, then. I took a dagger as I opened the gate, but to my luck, it was Sansa and Jon. If it would not have been them, I might have completely broken up, my Little Sam. Alas, this remains another story, I’ll tell you someday.

King Robert was aware of the deadly sickness by dawn, as Lord Stark informed him after the party. Almost everyone believed it at first, though Queen Cersei and the Lannisters denied such presence. 

I guess this discussion ceased thereafter as everyone got into the preparations for their departure to King’s Landing. Upon Sansa’s request to her father, I also accompanied them to the capital while Lady Catelyn stayed back in Winterfell.

That dark night, Jon assured me that he will help me in saving the seven kingdoms and do every possible effort. Queen Cersei was already vexed at Sansa for rejecting Prince Joffrey, during the Lannister visit to the North. 

She convinced the small council to believe that the kingdoms had other important affairs to attend, and Joffrey’s marriage being the most prime. Nothing was happening, and fear encountered me. 

Lannisters were cruel to us, except Lord Tyrion, who had a tender spot in his heart and was a great reader claiming that a mind needs books like a sword needs a whetstone. 

Sansa and I started to learn using swords from Arya, the little brave girl, Sansa’s younger sister. Lord Tyrion’s knowledge inspired us a lot and these two things became our daily chores as nothing was happening regarding the virus outbreak.

Luckily Lord Stark found out that Joffrey was not the true heir of King Robert and rather he was a bastard born from Queen Cersei’s incestuous relationship with her twin brother Ser Jaime Lannister of the Kingsguard. 

Queen fearing her crown and position asked Pycelle, the Grand Maester of the Citadel to visit the Castle Black. It was he who confirmed the news, and the queen believed it, but it was relatively late, a few months after we all reached King’s Landing.

Panic grew among all. Lord Varys’s spiders then confirmed the presence of Daenerys Stormborn, one of the last surviving members of House Targaryen, who ruled the seven kingdoms from the Iron Throne before King Robert’s Rebellion at Qarth along with her three baby dragons.

Daenerys denied the supply of ‘Shade of the Evening’ to Westeros and rather asked for the Iron Throne back, as she was the true heir to the throne in response to the request letter sent to her by the Hand of the King. 

Situations grew tense and then it was the Small Council who decided that Jon, Sansa, Lord Tyrion Lannister, Hand of the King and I will go to Essos; Qarth through the Narrow Sea along with Ser Davos; the onion knight’s ship. The journey was a good one. On our way, we thought of ways to persuade Daenerys. We reached Qarth and were presented before the Dragon Queen.

Finally, we all were able to convince her but in return, we had to give away the throne, other positions remaining the same though. We were all set for our return to Kings Landing along with Daenerys, her dragons, which have quite grown a bit and plenty of Shade of the Evening for the entire Westeros. 

We used our journey back to Westeros to lay out plans for finishing the sickness completely. Weeks passed. Jon spent a great time with Daenerys and her dragons throughout. Daenerys fell in love with Jon as they used to ride the dragons across the sea. We all were hopeful as we were about to reach our destiny. Our journey came to a halt, but not what we had expected.

We were welcomed by a huge army and a new king.

To be continued……

Stay tuned every Sunday, 7:00 PM for this amazing GOT crossover saga, an IEEE SB NITP ORIGINAL. And don’t forget to give your reviews/expectations in the comment section below.

Stay Safe. Stay Home.

AI for COVID-19

HOW FAR HAS ARTIFICIAL INTELLIGENCE REACHED TO BEAT THE NOVEL COVID-19?

Technology has been efficacious invariably in extricating living beings from perilous diseases. Any disease can become more threatening when humankind is incapacitated in spotting its existence in the body, and thus, it always acts as a conundrum for them.  The burgeoning science and technology sector has come up with a plan of bringing AI into play by using it to detect intimidating viruses.

Since the first report of the novel COVID-19 in Wuhan, China, it is now a pandemic causing stillness to at least 140 countries. As China initiated its response to the virus, it leaned on its strong technology sector and specifically artificial intelligence (AI), data science, and technology to track and fight the pandemic while tech leaders, including Alibaba, Baidu, Huawei and more accelerated their company's healthcare initiatives. As a result, tech start-ups are integrally involved with clinicians, academics, and government entities around the world to activate technology as the virus continues to spread in many other countries and India as well.

The patient-doctor ratio in India is as low as 1,700:1. Also, ~70% of the healthcare infrastructure is in cities, which cater to ~30% of the country's population. With the use of artificial intelligence applications, doctors can offer their services to more patients and reduce the existing gap in demand and supply of medical services in the country. AI-enabled healthcare services can be delivered at lower costs with increased efficiency and an emphasis on diagnostics. Moreover, artificial intelligence enables hospitals to implement patient-centric plans and eliminate unnecessary hospital procedures, making delivery of healthcare services faster in India.

Here are 10 ways, artificial intelligence, data science, and technology are being used to manage and fight COVID-19:

1. To identify, track and forecast outbreaks:

To fight Covid-19 we must be able to track it. By frequently analysing news reports, social media platforms, travel records and government documents, AI can learn to detect an outbreak. Tracking infectious disease risks by using AI is exactly what the Canadian start-up BlueDot provides. The BlueDot’s AI warned of the threat several days before the Centres for Disease Control and Prevention or the World Health Organization issued their public warnings.


Kamran Khan, the Blue dot Founder and CEO says the algorithm doesn’t use social media postings because that data is too messy. But he does have one trick up his sleeve: access to global airline ticketing data that can help predict where and when infected residents are headed next. It correctly predicted that the virus would jump from Wuhan to Bangkok, Seoul, Taipei, and Tokyo in the days following its initial appearance.

2. To help diagnose the virus:

Artificial Intelligence Company Infervision launched a coronavirus AI solution that helps front-line healthcare workers detect and monitor the disease efficiently.They use AI in detecting the disease competently which in turn helps in averting its swift spread.Viruses have made the work of individuals concerned with the healthcare facilities increasingly onerous but this solution helps them by reducing the time taken for CT diagnosis. Jack Ma's e-commerce company Alibaba also asseverates that they have built up an AI-driven system that is accurate up to 96% in diagnosing the virus within seconds.

3. Advanced fabrics offer protection:

An Israeli start-up Sonovia provides healthcare sectors, public and government officials with face masks made from their fabricated anti-pathogen, anti-bacterial fabric which relies on metal-oxide nanoparticles.

4. To process healthcare claims:

The financial transactions of the business field aren't the only one to be monitored but the ones being carried out in the field of medicines and health centres should also be.  This is so because many companies, hospitals and health centres etc. which manufacture and distribute medicines, antiseptics and disinfectants etc.deal with a huge sum of money. These transactions are to be kept an eye on, to prevent any mishap or to prevent someone from taking advantage out of this situation. This requires constant surveillance and with the COVID 19 breakout throughout the world which has been said to be 'pandemic' by the WHO, least contact in person to person should be maintained. With such a huge amount of money involved a blockchain platform which works with peer to peer network can be trusted and the money can be handled safely and so can the patients and hospital staff. The hospital staff can still provide the patients with their needs of medicines and surgical masks etc. without coming in contact with them. They can sit behind the monitor and handle everything easily and safely with a little bit of care.

5. To let drones deliver medical supplies:

Getting vital equipment and medicines from A to B is not always a straightforward process, especially in harsh environments like war zones or during environmental disasters. Consequently, drones are deployed to help speed up the delivery process. Medical Technology rounds up key areas where drones are helping to get medical supplies where they are most needed. Terra Drone is using its unmanned aerial vehicles to transport medical samples and quarantine material with minimal risk between Xinchang County’s disease control centre and the People’s Hospital. Drones also are used to patrol public spaces, track non-compliance to quarantine mandates, and for thermal imaging.

6. Develop drugs:

Google's DeepMind has shared AI-generated predictions about the Coronavirus that could help researchers stem the global outbreak.

Google’s DeepMind division used its latest AI algorithms and its computing power to recognize the proteins that might compose the virus and published the findings to help others develop treatment methods. Google’s DeepMind unit this week offered up data files of its best guess of the structure of some proteins that may be implicated in the Coronavirus.

 Proteins do the vast amount of the work of organisms, and understanding the three-dimensional shape of the proteins in COVID-19 couldprovide a kind of blueprint of the virus behind the disease, which could conceivably aid in coming up with a vaccine. Efforts are underway around the world to deduce the structure of those viral proteins, of which DeepMind's is just one effort. 

DeepMind's protein-probing program reflects decades of work by chemists and physicists, biologists, computer and data scientists and use AI to mine through existing medical information to find drugs that they say might be helpfulto tackle the novel Coronavirus.

The company BenevolentAI uses AI systems to build drugs that can combat the world’s toughest diseases and is presently helping support. Within weeks of the outbreak, it utilized its predictive capabilities to propose existing drugs that might be useful. 

Meanwhile, a Maryland-based biotech company, Insilico, used AI to come up with new molecules that could serve as potential medications, and it will now synthesize and test 100 of the compounds.

7. Sterilization, delivery of food/supplies and execution of other such tasks using robots:

Robots being unsusceptible to the virus are deployed to perform several tasks such as cleaning, sterilizing and delivering food and medicines to reduce the amount of human-to-human contact. Examples are the UVD robots from Blue Ocean Robotics which uses ultraviolet light to autonomously kill bacteria and viruses. In China, Pudu Technologydeployed its robots that are typically used in the catering industry to more than 40 hospitals around the country.

8. AI to identify non-compliance or infected individuals:

 ‘Smart helmets’ are used by the officials in Sichuan province to identify people with fever. China government’s surveillance system uses facial recognition and temperature detection software from SenseTime to identify people who might have a fever and be more likely to have the virus. The Chinese government has also developed a monitoring system called Health Code that uses big data to identify and assesses the risk of each individual based on their travel history, how much time they have spent in virus hotspots, and potential exposure to people carrying the virus. 

9. Supercomputers working on a coronavirus vaccine:

To curtail the accelerated spread of Corona virus and at the same time minimize the number of individual being prone to it, several supercomputers have been deployed, which aims to develop a Corona virus vaccine. Technologies like the cloud computing resources and supercomputers of almost every major tech companies such as Tencent, DiDi, and Huawei are being used by researchers to fast-track the development of either a cure or vaccine for the virus. The major objective is that the rate at which these systems run calculations and provide model solutions is greater than standard computer processing.

10. Chatbots to share information:

Tencent’s WeChat, where people can access free online health consultation services through chatbots has proved to be an essential communication tool for service providers in the travel and tourism industry to keep travellers updated on the latest travel procedures and disruptions and to the people who use public transport for office work.

Technology has always been a boon to the civilisation. The above examples clearly are a witness to this fact and can be used to maintain optimism in this situation of panic. IEEE SB NITP would like to remind everyone that our organizations are leaving no stone unturned to fight the novel Covid-19 and therefore we should fully cooperate with the guidelines as issued by the government and the WHO.

Please visit https://www.who.int/emergencies/diseases/novel-coronavirus-2019 for protective measures, mask usage and disposal, effective ways of washing hands, what to eat, myths and lot more.

Stay safe readers!

VIRUS IN WESTEROS

A crossover of Game of Thrones with reality, an IEEE SB NITP original.

To,

Gilly,

“The freedom to make my own mistakes was all I ever wanted.”

I was warned and ignored by everyone there in the Westeros, but was adamant to discover when I went beyond the wall after the upcoming of a soldier of the ancient Night's Watch order who survived a war led by a group of wildlings seeking help from the Castle Black.

Everyone was against me, even you Gilly. But, one dark night, I rushed from Winterfell to Castle Black. I am writing this because I am not sure if I will live or not, but I want anyone who reads this might tell the truth to the seven kingdoms of the Westeros and warn them as the world is overflowing with horrible things, but they’re all a tray of cakes next to death. No, I am not talking about the white walkers but sudden mass deaths caused beyond the wall due to some disease.

As far as I have read and searched, this is something unknown and its cure is unknown. I have been continuously interrogating the left ones. Some say they saw their friends dying, eyes bleeding and coughing blood droplets out of their dried mouths.

It came down to one wildling drinking the soup of a sick, dead bat. The sickness has seared through the men like blood through cloth. There has been no stop to this madness. 

I don’t know what to do and what to pretend. Everything was fine but during my last interrogation, I saw it myself. That moment I felt terror, a win or die at this Game of Thrones. 

While going through the Stranger Things at the Westeros, I guess, I got my hint, four days later. I discovered it to be a special disease outbreak due to a virus spread in the water streams beyond the wall. 

The victims die within two - three weeks the book says. Seven hells! Even I have been drinking and using the same water from the past four days. I think I will suffer the same fate. But, I want you to be safe. 

The book further says to sprinkle ‘Shade of the Evening’ from Qarth and then use it. But it has been my finding that the wildings who have isolated themselves out of fear haven't got this sickness. 

I don’t know if this works or not. I don’t know if this is truth or not. But we are all in danger. The wildlings have completely disappeared. It is deserted beyond the wall. 

I just wish, I could see you Gilly, one last time.

Goodbye,

Yours lovingly,

Sam.

IEEE SB NITP wishes for the safety of everyone amidst these circumstances and reminds to follow all prevention guidelines as issued by medical experts.