As AI is increasingly incorporated into our workplaces and daily lives, it is poised to fundamentally upend the way we live and work. Concern over this looming shift is widespread. A recent survey of 5,700 Harvard Business School alumni found that 52% of even this elite group believe the typical company will employ fewer workers three years from now. The advent of AI poses new and unique challenges for business leaders. They must continue to deliver financial performance, while simultaneously making significant investments in hiring, workforce training, and new technologies that support productivity and growth.
The education ministry said Tuesday it has completed its first screening of new textbooks under new teaching guidelines that are planned to be fully implemented from April 2021, approving 106 textbooks in 10 subjects. The average number of pages for a batch of textbooks approved to be used by junior high school students starting in fiscal 2021 rose 7.6 percent from that for current textbooks, the ministry said. The total number of textbook pages exceeded 11,000 in A5 format at the time of applications. The new teaching guidelines place importance on active learning methods, in which students learn proactively through debates and other learning activities, in order to nurture their intellectual ability to find and resolve problems themselves. For this purpose, many of the new textbooks present learning challenges at the outset of chapters and subchapters, and encourage students to have debates in groups after the end of the sections to deepen their understanding.
After attending some recent conferences and participating in a few online discussion communities in the ISTE networks, I've noticed more of an interest in finding strategies, specific tools or other resources for getting students started with coding. A lot of the questions are focused on how to get started with coding in the early years, the elementary and middle school levels, and where to find the best tools. There are definitely a lot of tools out there for educators to choose from. Some are web-based and offer free coding applications and activities for students. There are also many paid options that are more complex, perhaps involving robots, other necessary equipment, materials or starter kits.
Tech giant Intel and Central Board of Secondary Education (CBSE) on Friday signed a memorandum of understanding (MoU) to digitally empower nearly 1 lakh students with Artificial Intelligence (AI) integration in India's education system. Initiatives include the roll-out of an Artificial Intelligence (AI) curriculum framework for grades VIII, IX and X for 22,000 schools, with the aim to empower 1 lakh students within 2020, the company said in a statement. The curriculum is based on'Intel AI For Youth', which is an immersive, hands-on learning programme using experiential methodologies covering both social and technological skills. "AI has become a strategic imperative for worldwide economic growth and will continue to be one of the most crucial technologies of the future," said Shweta Khurana, Director-Programmes, Partnerships and Policy Group at Intel India. "Our collaboration with CBSE is a meaningful step towards enabling our youth to become digitally-empowered and effectively utilise emerging technologies such as AI to solve pressing local and global challenges," Khurana added.
You immigrate to a new country that speaks a different language, and start work with some of the brightest engineers in the world. Now, you're leading teams of people who are 10 or 20 years older than you, working on one of the fastest growing internet companies of the last decade. You have two options: sink or swim. That's the position Simon Eskildsen found himself in early in his career. He left his home in Denmark after high school, and moved to Canada alone to take a pre-college gap year working at Shopify. When he started, Shopify had 150 employees supporting tens of thousands of merchants. Now, it has 5,000 employees and over a million merchants.
NASA has equipped its Mars 2020 rover with everything it needs to explore the Red planet, except for a name – until now. Called Perseverance, the rover's title was picked from a'Name the Rover' essay contest that received 28,000 entries from children ranging from kindergartners to high school. The name was revealed on Thursday during a live streaming and was chosen by seventh grader Alex Mathers who's winning essay compared the rover to the human race. 'If you think about it, all of these names of past Mars rovers are qualities we possess as humans.' 'We are always curious, and seek opportunity. We have the spirit and insight to explore the Moon, Mars, and beyond.
F.A.C.P. is a fulltime, practicing gastroenterologist and internal medicine physician. As an active holistic health practitioner in the field, Dr. Nandi is also the Chief Health Editor at WXYZ ABC Detroit. At the age of 16, he completed his high school education in Columbus, Ohio where he was awarded a full academic scholarship to The Ohio State University and University of Notre Dame. To remain closer to his family, he chose Ohio State. Partha graduated summa cum laude (Top 1% of the class), a member of Phi Beta Kappa honor society, with a Bachelors degree in chemistry and a minor in classical Greek civilization.
When working on intelligent tutor systems designed for mathematics education and its specificities, an interesting objective is to provide relevant help to the students by anticipating their next steps. This can only be done by knowing, beforehand, the possible ways to solve a problem. Hence the need for an automated theorem prover that provide proofs as they would be written by a student. To achieve this objective, logic programming is a natural tool due to the similarity of its reasoning with a mathematical proof by inference. In this paper, we present the core ideas we used to implement such a prover, from its encoding in Prolog to the generation of the complete set of proofs. However, when dealing with educational aspects, there are many challenges to overcome. We also present the main issues we encountered, as well as the chosen solutions. The QED-Tutrix software [15, 19] provides an environment where a highschool student can solve geometry proof problems. One of its key features is that it allows the student to provide proof elements in any order, not limiting them to forward-or backward-chaining. For instance, when solving the simple problem "prove that a quadrilateral with three right angles is a rectangle", the student can provide any element of any possible proof, such as a direct consequence of the hypotheses ("if two lines are perpendicular to a third, they are parallel"), a necessary premise for the conclusion ("a rectangle is a quadrilateral that has four right angles"), or anything in between ("the quadrilateral ABCD is a parallelogram"). A second key feature is the tutoring aspect. When the student is stuck is the resolution, the software is able to provide them with relevant messages. In the previous example, if the student entered "the quadrilateral ABCD is a parallelogram" and is stuck afterwards, the software identifies that they are working on a proof using parallelogram properties, and will provide them messages such as "what is the definition of a parallelogram?" or "is there a relation between parallelogram and rectangle?" These features, the flexibility in exploration and the tutoring, are very interesting from a mathematics education perspective, but come with a cost.
Gaby Ecanow loves listening to music, but never considered writing her own until taking 6.S191 (Introduction to Deep Learning). By her second class, the second-year MIT student had composed an original Irish folk song with the help of a recurrent neural network, and was considering how to adapt the model to create her own Louis the Child-inspired dance beats. "It was cool," she says. "It didn't sound at all like a machine had made it." This year, 6.S191 kicked off as usual, with students spilling into the aisles of Stata Center's Kirsch Auditorium during Independent Activities Period (IAP).
Artificial intelligence--code that learns--is likely to be humankind's most important invention. It's a 60-year-old idea that took off five years ago when fast chips enabled massive computing and sensors, cameras, and robots fed data-hungry algorithms. We're a couple of years into a new age where machine learning (a functional subset of AI), big data and enabling technologies are transforming every sector. In every sector, there is a big data set behind every question. Every field is computational: healthcare, manufacturing, law, finance and accounting, retail, and real estate.