Machine learning will be seen touching most supply chain processes, starting right with demand sensing and forecasting to inventory management, manufacturing, warehouse management, and transportation. In the process, we will see a significant improvement in the accuracy of forecasts and efficiencies of these processes. What today takes months for demand planners to achieve in terms of forecast accuracies will be the starting point for the machine learning algorithms, which will learn and self-correct rules based on market conditions.

Marketing and sales seemed to be much easier in the past. Customers simply visited a retail shop, where they could ask a knowledgeable salesperson about a product they discovered in a local newspaper. In recent years, the ubiquity of the internet and a state-of-the-art technology changed everything. Customers became prosumers, well informed about the product before the purchase. And what is even more important, customers frequently use a variety of channels: online and traditional stores, mobile apps, online auctions, price comparison websites, social media and more. Today, in spite of all the available technologies, life is more challenging for both marketers and salespeople.

Data Science Summer School (DS3) is organised by the Data Science Initiative at École Polytechnique, in the quiet and charming outskirts of Paris. The primary focus of the event is to provide a series of courses covering the latest advances in the field of data science. The event is targeted for students (MSc2, PhD), postdocs, academics, members of public institutions, and professionals. The first talk on Monday 10am by Yoshua Bengio (Deep Learning) and the discussion after the special session are available for public attendance freely.

Use of Machine Learning (ML) is a hot topic in cybersecurity, one which will undoubtedly shape the industry for years to come. To see evidence of this we'd have to look no further than the booths at this most recent RSA Security Conference, where ML was promised as a solution for corporate cybersecurity problems. But why exactly will ML play such a prominent role, and how could it prove useful? Oddly enough the answer comes from the recent victory of ML in a game of poker. A competition took place in Pittsburgh last month that matched top poker players against a Machine Learning system called Libratus.

Think about how data applies to the real world. How will data react in a distributed world? One side exists in which technical developers like SQL and Spark but as these come together need to understand streaming data, machine learning, and creating feedback loops to provide more value so the edge is continually getting better. SQL, Java, Python, distributed systems, machine learning, artificial intelligence. Understand how to collect data and learn from it.

Inc has launched a new program to help students build capabilities into its voice-controlled assistant Alexa, the company told Reuters, the latest move by a technology firm to nurture ideas and talent in artificial intelligence research. The e-commerce company said it is paying for a year-long doctoral fellowship at four universities for an undisclosed sum. Working with professors, the Alexa Fund Fellows will help students tackle complex technology problems in class on Alexa, like how to convert text to speech or process conversation. Amazon, Alphabet Inc's Google and others are locked in a race to develop and monetize artificial intelligence. Unlike some rivals, Amazon has made it easy for third-party developers to create skills for Alexa so it can get better faster – a tactic it now is extending to the classroom.

Amazon accidentally took down large swathes of the internet with just one typo. This week, many of the world's biggest websites and services stopped working because of a problem with Amazon Web Services, the platform that the retailer provides to power people's websites. One of its sites went offline because of the issue – and since thousands of websites rely on it, including many of the world's biggest, they immediately went competely offline or stopped working. Websites like Quora, Trello and some of the world's biggest news sites went offline or stopped working properly when the issue happened. It even emerged that people's houses broke down – internet-enabled ovens, lights and front gates stopped working as a result of the outage.

Netflix spent $1 million for a machine learning and data mining competition called Netflix Prize to improve movie recommendations by crowdsourced solutions, but couldn't use the winning solution for their production system in the end. This white paper takes a closer look at the real-life issues Netflix faced and highlights key considerations when developing production machine learning systems.

Upskilling is hard and even though this is the case, the last few years have seen a big increase in the number of people teaching themselves to code, or brushing up on their data science skills, in order to better position themselves and their companies for the future. Managers and employees in almost every industry, and even the Prime Minister, has recognised that to keep pace with a rapidly evolving world, they need to develop new skills tailored to emerging technologies. So what are the skills really needed in the next few years? Artificial Intelligence (AI) can give meaning to data patterns in minutes; humans can take days. Already big in corporate firms, the harnessing of AI to cut down on tasks is growing in popularity and is already a part of daily life for many people.

Baidu Ventures exists on the front-lines of the Chinese search giant's push to brand itself as an artificial intelligence company. In an effort to bridge the AI ecosystems of China and the United States, Baidu Ventures is partnering with Comet Labs, a San Francisco-based fund specializing in machine intelligence. Unlike other venture capital firms looking to diversify into AI, Comet Labs lives exclusively in the space -- providing capital, technical resources and mentorship to its startups. Wei Liu, now head of Baidu's $700 million venture arm, was part of the founding team at Comet Labs before he was poached into the world of corporate venture. "Baidu founded Baidu Ventures to build an ecosystem around AI technology and do investment to help AI startups with money, technology and connections to industrial players," asserted Liu.