"The artificial intelligence and data science courses are not available in many colleges and this will help to attract students to government …

HYDERABAD: Data acquisition, Python and neutral networks are few topics that students of classes 8 and 9 will be exposed to as part of the artificial intelligence (AI) curriculum, which many Central Board of Secondary Education (CBSE)-affiliated city schools are set to adopt from academic year 2020-21. Early this year, the CBSE had proposed to offer AI as a skill-set to keep up with the changing technology. Following this, the CBSE recently released the AI curriculum facilitator's handbook, which details various topics such as AI ethics, problem scoping, data acquisition, exploration and modelling. Curated by Intel, the curriculum will not only make students inquisitive but will also teach them basic tools that are required to develop AI-based solutions. For example, in Unit 1, students will be asked to prepare a dream smart home by including any gadgets or devices that they think will make their homes unique.

Quantitative asset management company WorldQuant, in partnership with global online learning company Udacity, has launched a new Artificial Intelligence for Trading Nanodegree program. Students enrolled in the programme will analyse real data and build financial models by learning the basics of quantitative trading, as well as how to analyse alternative data and use machine learning to generate trading signals. Udacity and WorldQuant have collaborated with top industry professionals with prior experience at leading financial institutions to ensure students are exposed to the latest AI applications in trading and quantitative finance. By learning from industry experts, students will advance their finance knowledge, build a strong portfolio of real-world projects and learn to generate trading signals using natural language processing, recurrent neural networks and random forests. Graduates will gain the quantitative skills currently in demand across multiple functions and roles at hedge funds, investment banks and fintech startups.

On Thursday, Udacity announced a new AI-based Nanodegree. Developed in partnership with WorldQuant, an international asset management firm, "Artificial Intelligence for Trading" will help learners bring machine learning to financial trading. Until recently, most banks have relied on historical data to map out future market trends. Computer modeling and machine learning algorithms, however, allow analysts to test millions of different scenarios to determine which will lead to the best outcomes. The course comprises of two three-month terms.

NEC has partnered with dotData, a Silicon Valley venture in the automation of data science, to deliver artificial intelligence and data analytics solutions to the Sumitomo Mitsui Financial Group (SMBC Group) for its financial solutions. NEC has secured an exclusive license of dotData platform to provide this software across Japan. Since 2016, Sumitomo Mitsui Banking Corporation, NEC and the dotData team have been actively working to integrate AI into banking operations to develop new service offerings. As a result of this successful collaboration, the SMBC Group has decided to use dotData platform across the five group companies. Using dotData platform, the SMBC Group wants to deal with issues such as the marketing of various financial products, including credit cards and housing loans.

Zebra Medical Vision, an artificial intelligence (AI) health start-up, has partnered with Google to offer its algorithms on the search giant's cloud. The Israeli firm has created AI algorithms to read medical scans and detect anything untoward before humans can. Currently, its software can spot issues such as liver and lung disease and it is working on capabilities to recognise breast cancer and lung cancer. Zebra recently announced that all of its algorithms will be available to use for US$1 per scan. So, each time a hospital uses the algorithm to study a medical scan it will be charged US$1.

Slowly but surely, artificial intelligence (AI) is advancing. Where it stands in comparison to human intelligence is difficult to say because people excel across a broad set of intellectual tasks, while AI tends to be narrowly focused. But machines keep getting better at tasks like sifting through vast quantities of data, understanding natural language, and recognizing objects in images. Over the weekend, scientists from a Silicon Valley company called MetaMind described their efforts to advance the state of the art in a research paper, "Dynamic Memory Networks for Visual and Textual Question Answering." The paper explains improvements in memory and input modules for a system called a dynamic memory network (DMN), a general architecture for answering questions about text and images.