CHIBA – A compact driverless bus on Tuesday slowly shuttled a dozen passengers on public roads near the Makuhari Messe convention center in the city of Chiba to give them a sense of the steering wheel- and pedal-free future of transport. One of the passengers, Noriyuki Sakayanagi, was amazed at the distance the bus traveled without a human driver. "It wasn't scary" to ride the bus on a public road, said Sakayanagi, who was attending the first day of CEATEC 2019, one of Japan's biggest international digital trade shows that this year marks its 20th anniversary. Sakayanagi, a 39-year-old company worker, added, "I thought more improvement in detecting traffic lights may be needed and the brakes were not so smooth." CEATEC organizers said this year's four-day event has brought together 787 exhibitors from a broad spectrum of sectors -- not only information technology and electronics but also finance, housing, travel and health care -- with a vision toward a supersmart society designed to further economic growth and solve social problems.

Artificial Intelligence and Machine Learning (AI & ML) and Sentiment Analysis are said to "predict the future through analysing the past" – the Holy Grail of the finance sector. They can replicate cognitive decisions made by humans yet avoid the behavioural biases inherent in humans. Processing news data and social media data and classifying (market) sentiment and how it impacts Financial Markets is a growing area of research. The field has recently progressed further with many new "alternative" data sources, such as email receipts, credit/debit card transactions, weather, geo-location, satellite data, Twitter, Micro-blogs and search engine results. AI & ML are gaining adoption in the financial services industry especially in the context of compliance, investment decisions and risk management.

In this article, I will share my findings while attempting to use neural networks to describe the content of images. Images greatly contribute to a website's SEO and improve the overall user experience. Fully optimizing images is about helping users, and search engines, better understand the content of an article. The SEO community has always been quite keen in recommending publishers to invest on visual elements and this has become even more important in 2019 as Google keeps on revamping Google Image Search by adding new filters and new functionalities. There are several aspects that Google mentions in its list of best practices for images but the work I've been focusing on, for this article, is about providing alt text and captions in a semi-automated way.

Artificial intelligence (AI) has taken the world by storm, becoming a marketing buzzword and hotly commented subject in the press. Over the last few years there have been several important milestones in AI, in particular in terms of image, pattern and speech recognition, language comprehension and autonomous vehicles. Advancements such as these have prompted the healthcare, automotive, financial, communications and many more industries to adopt AI in pursuit of its transformative potential. How can AI benefit law enforcement and why might this be dangerous? Law enforcement is an information-based activity.

Until recently, artificial intelligence (AI) was a distant, dreamy concept that we dusted off annually during Christmas reruns of Bladerunner. However, in recent years, it's gradually crept into our lives in very tangible ways. From the Google Home device in the corner of your kitchen to automated supermarket tills, we're beginning to see AI being put to exciting uses in disciplines that require high-level thinking. And the creative industry has been no exception. However, as creative bots start to become more widespread, many are left wondering whether AI can ever have the creative freedom or intelligence needed for unique and valuable innovation.

Reliance Jio has announced a new Artificial Intelligence (AI) based Video Call Assistant (Bot) at the ongoing India Mobile Congress (IMC) 2019. The new service aims to transform customer support and customer communication systems. According to the company, the assistant can be accessed via a 4G phone call, and customers don't need to install any app. The customer engagement video assistant solution has been developed by Jio in partnership with US-based company Radisys, a Reliance Industries Ltd subsidiary that provides open telecom solutions to service providers worldwide. The company says that with this new launch it will addressing the current customer pain points like endless call-hold music or seemingly never-ending IVR wait times.

A KPMG report has said that 5G technology has the potential to add 0.35-0.5 per cent to India's gross domestic product (GDP) by 2025. The report further said that India Inc has the potential to unlock $48.69 billion (Rs 3,408 billion) in four years through the deployment of 5G. The government has set a target of becoming a $5 trillion economy by 2024-25. In 2018-19, the Indian economy stood at $2.72 trillion. "We estimate that the 5G contribution to annual GDP will likely be in the range of 0.35-0.5 per cent by 2025. The absolute value unlocked is expected to be highest in the retail sector, followed by finance and then the technology sector," said the report released at the India Mobile Congress 2019.

Editor's Note: See Joris and Matteo at their tutorial "Opening The Black Box -- Interpretability in Deep Learning" at ODSC Europe 2019 this November 20th in London. In the last decade, the application of deep neural networks to long-standing problems has brought a breakthrough in performance and prediction power. However, high accuracy, deriving from the increased model complexity, often comes at the price of loss of interpretability, i.e., many of these models behave as black-boxes and fail to provide explanations on their predictions. While in certain application fields this issue may play a secondary role, in high-risk domains, e.g., health care, it is crucial to build trust in a model and being able to understand its behavior. The definition of the verb interpret is "to explain or tell the meaning of: present in understandable terms" (Merriam- Webster 2019).

Python is the most popular and widely used language in Data Science, Machine Learning and Deep Learning. Most of the companies with the likes of YouTube, Google, Netflix etc are using Python to gear up there offerings to their customers. In this article, we will help you with how to start with Python in data science? So far, in this series of data science tutorial, we have covered the following topics: 1. What is data science and why do we need this now?

The application of machine learning in economics is the cool thing. Machine learning uses algorithms and statistical models that perform tasks based on patterns and inferences. It is not really a new idea, but its application in economics is going to increase significantly as seen by the recent working paper by a team of RBI economists, which looks at machine learning for economic forecasting. To get an idea on machine learning in economics, one should go back to the Jean Monnet lecture by Susan Athey, Professor, Economics of Technology, Stanford University. Her lecture'Machine learning in economics' was delivered at the 4th ECB Annual Research Conference on September 5-6.