You may have heard that we are currently on the cusp of the fourth industrial revolution – a time where the barriers between physical, digital, and biological sectors will be eliminated by Artificial Intelligence. And though a lot of us may be experiencing some Boston Dynamics level creep factor, it's something that we are going to have to face and adapt to. You may be thinking that this will be a technology focused issue – something that HR and recruiters won't have to worry about. However, they will actually need to be as close to this cutting edge as possible. HR will be instrumental in this evolution.

HowNow, the modern learning platform designed to help today's workforce drive self-directed learning and develop business-critical skills, has now raised more than $3m in funding, following the close of its pre-series A funding round, led by Fuel Ventures. Founded by Nelson Sivalingam with co-founders Kuvera Sivalingam and Ashish Kumar in 2016, HowNow is an integrated learning platform that autonomously curates learning resources, business intelligence and market insights that live in dozens of different internal and external sources, and makes it available everywhere employees work. The AI-powered learning platform is used by SMEs and large Corporates to onboard, upskill and enable employees. The company's investors now include the likes of Mark Pearson (founder of MyVoucherCodes); Andy Murray OBE; Michael Whitfield and Chris Bruce (founders of Thomsons Online Benefits); Bernie Sinniah (former managing director at Citi Bank); and Alwin Magimay (a former partner at McKinsey). Using Machine Learning and Artificial Intelligence, HowNow is able to personalise learning for employees based on their role, experience, learning preferences, skill requirements, business goals and their context.

My specific focus in this work will be threefold: firstly, to present a coherent and comprehensive state of play with current technologies and research, secondly, to build out case studies of how these areas are influencing and changing Organisations globally, across a range of sectors, and finally, to identify specific actionable insights and areas for individual (and Organisational) experimentation. In the Learning Science module, which i have just about finished, i included a whole section on the'Hyperbole Filter', alongside sections on'What Science Can Do For Us', and'What Science Cannot Do For Us'. I will attempt a similar stance for this piece. I anticipate that i will develop this over the next six months or so, alongside some other work, and will #WorkOutLoud as i do so. As an aside, the Learning Science work is taking shape into the Learning Science Guidebook, which i intend to publish as a full free eBook before the end of this year.

The University of Helsinki is an international scientific community of 40,000 students and researchers. It is one of the leading multidisciplinary research universities in Europe and ranks among the top 100 international universities in the world. We are an equal opportunity employer and offer an attractive and diverse workplace in an inspiring environment with a variety of development opportunities and benefits. As a part of the Faculty of Science, the Department of Computer Science (https://www.helsinki.fi/en/computer-science) is a leading unit in Finland in its area and responsible for the teaching and research in computer science at the University of Helsinki. The number of professors at the Department has grown in recent years and there are now 29 professorships.

Schools are not providing the adequate skills to succeed in a world where artificial intelligence will transform the future labour force, according the new research from ESCP Europe. In order to prepare our future generation for a world that will revolve around technologies such as AI, major steps need to be taken in order to coincide this change with the educational structure and understand how the current system is not giving children the personal and professional technological development required says the accompanying report. According to Terence Tse, Professor of Digital Transformation at ESCP Europe: "Our modern-day educational system is outdated, unfitting and no longer works - it only teaches a very rigid set of theories and skills. This is grossly inadequate for the needs of children who will be working in the age of the 4th Industrial Revolution and beyond. "The majority of the jobs our current education system is preparing our children for will be irrelevant by the time they are adults and most will end up in jobs that don't even exist yet.

Abu Dhabi is gearing up for the next phase in advances in science and technology by announcing plans to open the world's first University of Artificial Intelligence. Academic experts and businesspeople from China, America and the UK will help to steer the state-of-the-art institute when the campus officially opens to graduate students in Masdar City in September 2020. Abu Dhabi made the announcement as part of a national strategy set up in 2017 that makes Artificial Intelligence the centrepiece of the UAE's focus on developing a "knowledge-based economy". The university has partnered with the Abu Dhabi-based Inception Institute of Artificial Intelligence, who will advise on the academic curriculum. The university has also been named after the capital's political leader, crown prince sheikh Mohamed bin Zayed Al Nahyan.

For Adam Jasinski, a technology director for a school district outside of St Louis, Missouri, monitoring student emails used to be a time-consuming job. Jasinski used to do keyword searches of the official school email accounts for the district's 2,600 students, looking for words like "suicide" or "marijuana". Then he would have to read through every message that included one of the words. The process would occasionally catch some concerning behavior, but "it was cumbersome", Jasinski recalled. Last year Jasinski heard about a new option: following the school shooting in Parkland, Florida, the technology company Bark was offering schools free, automated, 24-hour-a-day surveillance of what students were writing in their school emails, shared documents and chat messages, and sending alerts to school officials any time the monitoring technology flagged concerning phrases.

If you think your data is clean, perhaps you have not looked into it yet; if you think your data is messy, it's even messier. Nobody cares how you did it; just do it correctly. People do not care how much you know until they know how much you care (about them and their business). In 2-3 years, nobody will talk about Big Data anymore. It always pays off to be damn good at numbers, Excel, and PowerPoint (and yes, presentation skills); Tableau is a big plus. Downloading some code and data and running them does not make you a data scientist. The same is true for doing data science courses. Participating in Kaggle competitions does not make you a data scientist, although it can help you learn from others. Winning Kaggle competitions does not necessarily make you a good data scientist. ETL is always needed - be good at it and learn a good tool for it (Talend is a good one). Also, learn scripting languages for ETL. Deep learning is cool, but it's still cool if you don't use it when you don't need it, and in 99% of cases you don't need it. Algorithms are commodities, your data is not. Ideas are commodities, execution is not. Deep learning expertise will soon become a commodity; problem-solving skills won't.

Google search is advancing a reading grade. Google says it has enhanced its search-ranking system with software called BERT, or Bidirectional Encoder Representations from Transformers to its friends. It was developed in the company's artificial intelligence labs and announced last fall, breaking records on reading comprehension questions that researchers use to test AI software. Pandu Nayak, Google's vice president of search, said at a briefing Thursday that the muppet-monickered software has made Google's search algorithm much better at handling long queries, or ones where the relationships between words are crucial. You're now less likely to get frustrating responses to queries dependent on prepositions like for" and "to," or negations such as "not" or "no." "This is the single biggest positive change we've had in the last five years," Nayak said--at least according to Google's measures of how ranking changes help people find what they want.

"Words that will Inspire" is an analysis on 2,500 TED talks using text analytics and machine learning on R to find the factors that make some talks more popular than others. What was the motivation for doing this project? I am part of a meetup group called Data Scientist speakers in London that meets regularly to practice data science talks and receive feedback to improve public speaking. Every year at the club we have a competition to see who can come with the best data science story. I joined this competition and wanted to make participate with something special: I wanted to combine my data science skills to analyse famous speeches or talks and use these insights to build an entirely new one.