Artificial intelligence (AI) has increasingly dominated the news agenda in 2017. This was highlighted in November when the UK Government's Autumn budget included a £20 million investment pledge for businesses working in AI. With research from Deloitte showing that 85 percent of UK businesses plan to invest in AI by 2020, it's clear that firms across the board are waking up to its benefits and are starting to take decisive action. More and more brands are making headway with AI in digital advertising, from better audience insights and targeting to campaign measurement. The results are evident in more relevant, targeted and measurable campaigns.

Prince Harry, the fifth in line to the throne, is the guest editor for BBC Radio 4's Today programme on Wednesday. The prince has interviewed former US President Barack Obama and his father, the Prince of Wales, for the programme. The programme is focusing on issues such as the armed forces, mental health, youth crime and climate change - a cause his father also champions. It is the 14th year public figures have been in control of the show's output between Christmas and New Year. Other guest editors this week include a robot, Bletchley Park code-breaker Baroness Trumpington, Tamara Rojo of the English National Ballet and poet and novelist Benjamin Okri.

All across the globe, countries have been building up Artifical Intelligence capabilities due to the possibility that AI could completely transform the nature of work and create better outcomes for businesses and society. An Accenture report estimates that Artificial Intelligence has the potential to add $957 billion, or 15% of current gross value, to India's economy, by 2035. The report outlines how India can benefit from AI. Flipkart, India's top e-commerce player, is already tapping into AI, using the technology in operations ranging from conversational search, visual similarity, better last-mile delivery, fraud-detection, personalisation to warehousing. The technology is expected to help Flipkart serve its existing customers better, and attract new ones as well. The emphasis and importance given to AI is rather one-sided, reports the Financial Express.

The doctor enters and pulls up the electronic medical record. The patient's history is already there. The doctor drags and drops the image, presses the "analyze" button. An actionable diagnosis appears a moment later. If artificial intelligence (AI) were to one day take over much of clinical practice, as some fear or anticipate -- being potentially faster, more reliable, and generally better at certain tasks than humans -- clinical decisions may no longer depend on tired eyes, imperfect risk scores, or lagging guidelines.

Identifying coordinate transformations that make strongly nonlinear dynamics approximately linear is a central challenge in modern dynamical systems. These transformations have the potential to enable prediction, estimation, and control of nonlinear systems using standard linear theory. The Koopman operator has emerged as a leading data-driven embedding, as eigenfunctions of this operator provide intrinsic coordinates that globally linearize the dynamics. However, identifying and representing these eigenfunctions has proven to be mathematically and computationally challenging. This work leverages the power of deep learning to discover representations of Koopman eigenfunctions from trajectory data of dynamical systems. Our network is parsimonious and interpretable by construction, embedding the dynamics on a low-dimensional manifold that is of the intrinsic rank of the dynamics and parameterized by the Koopman eigenfunctions. In particular, we identify nonlinear coordinates on which the dynamics are globally linear using a modified auto-encoder. We also generalize Koopman representations to include a ubiquitous class of systems that exhibit continuous spectra, ranging from the simple pendulum to nonlinear optics and broadband turbulence. Our framework parametrizes the continuous frequency using an auxiliary network, enabling a compact and efficient embedding at the intrinsic rank, while connecting our models to half a century of asymptotics. In this way, we benefit from the power and generality of deep learning, while retaining the physical interpretability of Koopman embeddings.

Federal lawmakers want to have a say in defining artificial intelligence. Researchers are now using TV shows to feed the predictive capability of an AI system. Google said in recent days it's opening an AI-focused research facility in China. And on and on the headlines keep coming, all of which is to say that interest in AI remains acute -- and its presence pervasive -- as 2017 draws to a close. And, based on a few recent developments, 2018 should be another big year of AI-related leaps forward as machines expand their influence over the minutiae of our lives.

In the light of the UK's new industrial strategy and budget, as well as the ODI's recent participation in a House of Lords evidence session around how AI and personal data should be owned, managed, valued and used for the benefit of society, the ODI's Head of Technology Olivier Thereaux examines our work in this area. Artificial intelligence (AI) is currently enjoying a renaissance in industry and popular imagination, and in the most recent UK government budget. AI's popularity can be partly explained by the fact that, for the first time, we have enough large-scale data for training AI systems. There are public datasets for computer vision, natural language, speech and many more non-public datasets within businesses and governments. Recent improvements in hardware are also making it more cost-effective to train and run machine-learning models.

Baba Vanga, a blind Bulgarian mystic who died in 1996, is said to have predicted a huge scientific discovery for 2018: a new form of energy on the planet Venus. With no planned missions to Venus this year, her prediction is not expected to come to fruition. More than 20 years after her death, people are waiting to see if Baba Vanga's prophecies for 2018 will come to pass. They reportedly include the Venus discovery, as well as China passing the United States in economic power, although it is unclear where these statements are coming from. Baba Vanga, whose real name was Vangelia Gushterova, was blinded as a child during a tornado.

Over the past few weeks Fortune colleagues and I have written at length about China's rise as an "innovation superpower," particularly in sectors involving the Internet, e-commerce and mobile payment. We've marveled at the scale of China's two largest tech giants, Alibaba Group and Tencent Holdings, and extolled the creativity and convenience of the multitude of the services they offer. Some of you have written to remind us of Beijing's strict censorship of the Internet. Even so, my view remains that China has emerged as the biggest, liveliest and most sophisticated digital marketplace in the world. But I've also expressed unease in this space about the fact that in China's tech sector, even more than in America's, an enormous amount of market power is concentrated in the hands of a few giant firms, with few safeguards for individual privacy.

In recent years, artificial intelligence has emerged as a concept on the cusp of revolutionizing everything from medical research to workplace collaboration. And while the technology has recently begun touching into government operations in the form of chatbots, a new study finds that states and cities should begin gearing up for big changes -- and big savings -- from AI tech. According to a new report by Deloitte University Press, by automating many of the simple and repetitive tasks government employees perform every day, AI could free up or eliminate millions of hours of labor in the federal government alone. "At the low end of the spectrum, we estimate, automation could save 96.7 million federal hours annually, with a potential savings of $3.3 billion; at the high end, this rises to 1.2 billion hours and a potential annual savings of $41.1 billion," the report reads. Cognitive technologies could help push these cost savings not just by freeing workers from mundane tasks but also by creating more accurate cost projections and overcoming resource constraints, the report notes.