This week's publication of the Pandora Papers–which the International Consortium of International Journalists based on a trove of private data leaked from offshore tax havens–showcased the alarming extent of fraud and corruption in the world. While big data tech like graph analytics and machine learning can help to a shine light on bad actors, we'll always be playing catch up, fraud hunters tell Datanami. The sheer numbers behind the Pandora Papers, which the ICIJ published on October 3, 2021, are staggering. The ICIJ was provided with 11.9 million documents, including text files, PDFs, images, emails, and spreadsheets, from 14 offshore tax havens, totaling 2.9 TB of data. The documents contained information about 27,000 shell companies created to protect the assets of 29,000 beneficial owners, including 130 billionaires and 330 politicians from 90 countries.

President Xi Jinping wants China to dominate artificial intelligence by 2030. But all it seems the Middle Kingdom's new AI entrepreneurs want to talk about ancient history. Take Kai-Fu Lee, for example. The founder of Face was born in Taiwan and emigrated to America when he was eleven. After earning a Ph.D. from Carnegie Mellon in the 1980s, he worked his way up at Apple, Microsoft, and eventually, Google. In his book AI Superpowers, he likens Chinese entrepreneurs to "gladiators" fighting in a new techwar arena, where it's "kill or be killed."

Despite efforts to tackle corruption around the world, progress is still frustratingly slow, according to the latest report from Transparency International. Its annual Corruption Perception index reveals some alarming trends. It shows public service corruption is still a huge problem for two-thirds of the world's economies. The report uses a scale of zero to 100 to rank countries: zero is highly corrupt and 100 is very clean. New Zealand comes out on top but with a score of 89.

Almost every word has more than one meaning. Modern search engines solve this problem using knowledge bases. Yago was one of the first knowledge bases, developed by scientists at the Max Planck Institute for Informatics in Saarbrücken and the Télécom ParisTech in Paris. Last week, the researchers received an award for their work on Yago from the most important scientific journal in the field of artificial intelligence. Today, they are releasing Yago's source code.

Machine Learning is being applied to almost everything these days, and the results are immaculate. With the introduction of Machine Learning APIs, developers don't have to train their own Machine Learning Algorithms, rather they can use these Machine Learning API's to create most interesting applications. Recently, I red an article in which Ben Hubl applied Microsoft Cognitive Service Emotions API to do emotions analysis of video of Hillary and Trumps last debate. I was amazed to see the accuracy of results, and the way graphs of emotions were shown per frame of the video. This inspired me to do video emotions analysis of a Prime Minister Nawaz Sharif address to the nation after Panama Papers were published.

Whether you are based in Washington or Beijing, automation anxiety is something that could be keeping you awake at night. What will the future of work look like if more and more companies replace humans with machines? The leaders of two of the world's biggest economies, US President Donald Trump and China's Xi Jingping, met this week to discuss business and trade. They oversee a workforce of 900 million people. In the past, Trump has blamed China for taking US jobs.

DEVELOPING: A contractor who threatened to set off a bomb at the headquarters of Fox 45 Baltimore Thursday afternoon, forcing police to evacuate the building, walked outside before a sniper shot him as cameras rolled. The suspect, a man in his 20s, was still alive but refused to cooperate with officers, police spokesman T.J. Smith said. Reporters said they saw him kick off some of his clothing. When he walked out of the building, he was wearing a white panda suit, a surgical mask and sunglasses. Robot trying to get suspect to show his hands.

The biggest leak in history has connected more than 70 current and former world leaders to tax evasion schemes that channel billions of pounds into secretive off-shore accounts. This is how the data was analysed. The Panama Papers show that law firm Mossack Fonseca helped hundreds of clients, with connections to some of the most powerful people in the world, launder money, dodge tax and potentially avoid sanctions. The papers themselves were leaked to news organisations by an unknown person and have been shared with more than 100 news organisations and 400 journalists – the investigation has been ongoing for almost a year. The process of making the raw data accessible for journalists involved converting it to digital formats, high-performance computers, and algorithms to find well known names among the thousands of details. While the actual leaked documents have not been published -– the International Consortium of Investigative Journalists (ICIJ) say the full list of companies linked to the papers will be revealed in May – how much data they contain is known.

The latest buzz about Panama Papers has shaken the world. As we all know the Panama Papers is a set of 2.6 TB of data that includes 11.5 million confidential documents with detailed information about more than 214,000 offshore companies listed by the Panamanian corporate service provider Mossack Fonseca. The Panama Papers has set an excellent example for the world about the importance of data science when it comes to analyzing big data. This leak makes us realize that appropriate approaches are needed to handle the challenges of data management for the present and the future. Let's take a deep dive into the Panama Papers and dig down the secret behind the biggest leak ever This leak contains 4.8 million emails, 3 million database entries, 21.5 million PDFs, around one million images and 320,000 text documents.

The numbers are mind-boggling: 11.5 million documents in total, comprising 4.8 million emails, 2.1 million PDFs, 1.1 million images and 320,000 text files. To put it in context, the amount of data in the Panama Papers leak was 2,000 times the amount in the WikiLeaks State Department cables in 2010. Trying to sift through data like this manually would be a Sisyphean task, so technology was required. Enter the little-known Australian company Nuix. The software company has worked with the D.C.-based International Consortium of Investigative Journalists (ICIJ) for over four years, giving them free access to their software that can take huge troves of unstructured data and turn it into an indexed and searchable database.