Children who learn computer science skills such as coding gain a multitude of benefits in other areas, including problem solving, creative thinking and mathematics, according to a new study by OKdo. For a new report titled Broader Benefits of Learning to Code, the global tech company gathered survey responses from almost 7,000 UK teachers and parents (with children aged 5-16), in which 96% of teachers claimed to have seen first-hand evidence of how computer science lessons can help to improve both hard and soft skills, as well as IT abilities, in children. Overall, eight in 10 (82%) of teachers said computer science education boosts pupils' problem solving capabilities. On top of this, two thirds (68%) agreed that it helps them develop expertise in mathematics, while six in 10 (60%) claimed that lessons in the subject also positively impacts creative thinking in young people. Over a third (35%) felt that teaching coding can boost children's organisational and time management skills, with 34% also feeling that participating in the subject can improve young people's ability to work as part of team.

To most of us, a 3-D-printed turtle just looks like a turtle; four legs, patterned skin, and a shell. But if you show it to a particular computer in a certain way, that object's not a turtle -- it's a gun. Objects or images that can fool artificial intelligence like this are called adversarial examples. Jessy Lin, a senior double-majoring in computer science and electrical engineering and in philosophy, believes that they're a serious problem, with the potential to trip up AI systems involved in driverless cars, facial recognition, or other applications. She and several other MIT students have formed a research group called LabSix, which creates examples of these AI adversaries in real-world settings -- such as the turtle identified as a rifle -- to show that they are legitimate concerns.

The world of academia is generally not known for being on the cutting edge of technology. However, as technology rapidly advances, historians and researchers can utilize both artificial intelligence (AI) and deep learning to make their jobs easier. Artificial intelligence is the ability for a machine to imitate intelligent human behavior. Deep learning, a subset of machine learning, is the intermediary between machine learning and neural networks. Deep learning provides a fast and relatively easy way to process massive amounts of data, much of which would be tedious and time consuming for a human to process; because of this, pattern recognition is one of deep learning's greatest strengths. Historians are finding that the practical applications of deep learning can help them work with large amounts of information much easier.

Machine Learning (a type of artificial intelligence (AI) that allows software applications to become more accurate in predicting outcomes without being explicitly programmed4) is the intersection between Computer Science, and Math and Statistics and all you need to know are the input variables and how to interpret the output. Machine Learning Algorithms are created using various techniques and programming machine learning algorithms is the job of a Data Scientist. Traditional Research is the intersection of Math and Statistics, and Subject Matter Expertise. This is the kind of research that is not dependent on any technology. Traditional Software is the intersection between Subject Matter Expertise and Computer Science.