Over 120 million workers will have to be retrained within the next three years due to mass disruption caused by AI and automation. That's according to a new study by the IBM Institute for Business Value, based on input from 5,670 global executives in 48 countries. The issue is not just one of jobs being lost, but the lack of a strong skills base to underpin the emerging technologies, with the institute warning that the time it takes to close a skills gap through training is growing. Interestingly, the report finds that executives see technical core STEM capabilities – along with basic computer and software skills – as significantly less important than they did three years ago. According to the global research, the time it takes to close a skills gap through training has increased ten-fold in just four years. In 2014, it took three days on average to close a capability gap through training in the enterprise; in 2018, it took 36 days.

This story is part of a series on how we learn--from augmented reality to music-training devices. By now you must have heard the good news about our savior, artificial intelligence. It makes you look better in selfies, prevents blindness, and can even turn water into tastier beer. Tech giants and governments say we're living in a golden age of AI. Truth is, most times you hear the term artificial intelligence, the specific technology at work is called machine learning.

So, a few months ago, I was walking down the street in Shenzhen, in the Guangdong Province of southeastern China. I was hungry and looking for lunch. Armed with my credit card and plenty of the local currency, I strode out of my hotel to check out the many street vendors selling delicious-smelling food. Using Google Translate, I was able to order a fried fish dish, but when I went to pay, the vendor refused my credit card. Undaunted I pulled out cash, but that too was refused. The guy pointed me to a large QR code and asked me to pay using the WeChat app. As this was my first day in China, I hadn't yet set the app to pay for things, so I walked away, a little embarrassed. Still hungry, I came to a large junction and saw a promising looking restaurant across a busy street.

Integrify is a growing tech company with a mission. We teach coding to talented and motivated immigrants and connect them with coding jobs through staffing and consulting. In 2019, over 60 students have started in our programs eager to kick-off their tech career in Finland. Over 80% of the graduates are working as developers. In June, we kicked off our first program in Python & Machine Learning with students with a background in software development, data science or mathematics.

When you stop to think about it, the future can be a little daunting. It's filled with AI, automation, 3D printing, virtual reality, IoT, and other concepts that until now seemed like science fiction. But if you understand these ideas, it can also be a place filled with opportunities. For example, by understanding the basics of AI and big data, you could carve yourself out a career as a machine learning engineer. Not only could that land you a very healthy machine learning engineer salary, but it could also help you to shape that very future.

In the next three years, as many as 120 million workers in the world's 12 largest economies may need to be retrained or reskilled as a result of AI and intelligent automation, according to a new IBM (NYSE: IBM) Institute for Business Value (IBV) study. In addition, only 41 percent of CEOs surveyed say that they have the people, skills and resources required to execute their business strategies. The study, which includes input from more than 5,670 global executives in 48 countries, points to compounding challenges that require a fundamental shift in how companies meet and manage changing workforce needs throughout all levels of the enterprise. According to the global research, the time it takes to close a skills gap through training has increased by more than 10 times in just four years. In 2014, it took three days on average to close a capability gap through training in the enterprise; in 2018, it took 36 days.

On 1st October 2019, the UKRI Centre for Doctoral Training in Artificial Intelligence for Healthcare opens its doors to their first cohort. The United Kingdom Research and Innovation Centre for Doctoral Training in Artificial Intelligence for Healthcare (AI4Health) will open its doors to the first cohort of PhD students in October. Director Dr Aldo Faisal and the whole AI4Health Team are looking forward to getting started and turning vision into practice. Imperial College London understand the term "AI" as meaning the development of intelligent systems that embody a practical solution. However, practical solutions involving AI will require a broader approach and the College will drive technical innovation by providing broad training for exploitation of multiple technological strategies within the broader realm of AI.

In one event, an electronics shop close to her university was completely destroyed a few minutes after she left her laptop for repairment. This of one of many events that did not stop Munira from following her vision to improve her skills, empower other women in STEM, and use technologies such as Machine Learning to solve problems in her country and beyond. I want to solve community problems like droughts and also improve many industries in my country using Deep Learning and Computer Vision in the near future. Munira works among 40 other Collaborators in our AI for Good challenge with the UN Refugee Agency to predict forced displacement and climate change in Somalia. Read on your own what extraordinary mindset she has.

The recent surveys, studies, forecasts and other quantitative assessments of the health and progress of AI highlighted the role of AI in cybersecurity defense and in scoring standardized tests, the relationships between data migrating to the cloud and data modernization, lax security standards for IoT devices, and that the U.S. still leads the global race for AI domination but that China is making more rapid progress. Written essays on standardized tests in 18 states in the U.S. are currently graded by natural language processing (NLP) software ("automated essay scoring engines") with only a small percentage of students' essays--it varies between 5% to 20%--randomly selected for a human grader to double check the machine's work [VICE] Based on a 100-point scale, the U.S. leads the global AI race with 44.2 points, followed by China with 32.3 points and the European Union with 23.5 points; The U.S. came out on top in talent, research, development, and hardware, while China led in adoption and data. Airbus Americas has been using AI from AppZen to review expense reports and determine if they are in compliance with company policies; in the first partial year of the technology's implementation Airbus paid off its initial investment of $50,000 and pocketed about $50,000 more; the division expects to save $100,000 this year and at least $200,000 in 2020 in the Americas; worldwide implementation is expected to result in several millions of dollars in savings [The Wall Street Journal]

Learning has been administered by conventional pedagogy for long. However, continuous technological intervention is gradually changing the paradigm of learning and development. The rapid integration of technology in the educational technology (EdTech) sector has made it a promising field to explore. According to a report from KPMG and Google highlights, the Edtech market is expected to cater to 9.6 million users and have a market share of 1.96 billion dollars by 2021. The emerging technologies are influencing the education sector vastly.