Cloud computing was the first major attack on IT teams. It shattered our role as "procurement gatekeepers" for every new technology purchase, forcing us to find new ways to add value to the business. Now, an even greater threat is coming. Forrester predicts that by 2025, technologies like robots, artificial intelligence (AI), machine learning, and automation will replace 7% (or 22.7 million) jobs in the US alone. It won't just be blue-collar jobs operating factory machinery, either.

Adelyn Zhou is a founder and CMO of TOPBOTS, a platform specialising in connecting large enterprise companies and small businesses to bot and artificial intelligence (AI) service providers and vendors. TOPBOTS helps their clients implement an AI strategy and also lead interactive workshops to train personnel in this new hot field. Here she explains how publishers should be developing chatbot strategy. A chatbot is a computer program that you can talk to using your voice (like Siri or Alexa) or text (as in Facebook Messenger or on Slack). Chatbots and bots vary in their levels of sophistication.

When you ask Siri for directions, peruse Netflix's recommendations or get a fraud alert from your bank, these interactions are led by computer systems using large amounts of data to predict your needs. The market is only going to grow. By 2020, the research firm IDC predicts that AI will help drive worldwide revenues to over $47 billion, up from $8 billion in 2016. Still, Coursera co-founder ANDREW NG, adjunct professor of computer science, says fears that AI will replace humans are misplaced: "Despite all the hype and excitement about AI, it's still extremely limited today relative to what human intelligence is." Ng, who is chief scientist at Baidu Research, spoke to the Graduate School of Business community as part of a series presented by the Stanford MSx Program, which offers experienced leaders a one-year, full-time learning experience.

Earlier, we came up with a list of some of the best Machine Learning books you should consider going through. In this article, we have come up with yet another list of the recommended books for Data Science. Written by Hopcroft and Kannan, this book is a great blend of lectures in the modern theoretical course in data science. This tutorial aims to get you familiar with the main ideas of Unsupervised Feature Learning and Deep Learning. The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages.

Enroll in the course for free at: https://bigdatauniversity.com/courses... Machine Learning can be an incredibly beneficial tool to uncover hidden insights and predict future trends. This free Machine Learning with Python course will give you all the tools you need to get started with supervised and unsupervised learning. This Machine Learning with Python course dives into the basics of machine learning using an approachable, and well-known, programming language. You'll learn about Supervised vs Unsupervised Learning, look into how Statistical Modeling relates to Machine Learning, and do a comparison of each. Look at real-life examples of Machine learning and how it affects society in ways you may not have guessed!

Google has successfully applied deep learning artificial intelligence algorithms to the diagnosis of breast cancer. In a study carried out by researchers taking part in Google's Brain Residency Program – a 12-month educational course in machine and deep learning – an algorithm was trained to detect breast cancer tumours in a dataset of digitised pathology slides provided by Dutch medical institute the Radboud University Medical Center. After'training' the algorithm, researchers were able to achieve a 92% sensitivity in picking out tumour cells from the slides – significantly higher than the 73% achieved by trained pathologists with no time constraint. In addition, the team recreated the accuracy in different datasets taken from other hospitals and scanning machinery. The team did report an average of eight false positive per slide compared to none from trained pathologists.

In the past years, a collection of hardware, software and online service have managed to bring changes and reforms to classrooms and teaching methods. But the true disruption of education is yet to arrive. Artificial Intelligence has proven its role as a game changing factor in an increasing number of fields, causing transformations unimaginable in the past. It's now showing glimmers of how it might forever change the learning process, one of the oldest skills that mankind has mastered. Here's how AI and its derivatives are gradually finding their way into the classroom, and beyond.

In the course of our work with Intel's data science and artificial intelligence initiatives, we often encounter people who are excited about the potential of artificial intelligence, and eager to learn more about the things Intel is doing to drive the industry forward. In many cases, these people have read about Intel's focus on AI, and now they are asking how they can get more involved in this forward-looking field. They often ask how they can advance their data science careers in the direction of AI. In Part 1 of this blog series, we talked about steps organizations can take to cultivate in-house expertise in advanced analytics and data science. In this second part of the post, we will take things down to a more personal level, and talk about steps individuals can take to chart a future that involves creating AI solutions.

In the past years, a collection of hardware, software and online service have managed to bring changes and reforms to classrooms and teaching methods. But the true disruption of education is yet to arrive. Artificial Intelligence has proven its role as a game changing factor in an increasing number of fields, causing transformations unimaginable in the past. It's now showing glimmers of how it might forever change the learning process, one of the oldest skills that mankind has mastered. We're inviting 250 to exhibit at TNW Conference and pitch on stage!

In the past years, a collection of hardware, software and online service have managed to bring changes and reforms to classrooms and teaching methods. But the true disruption of education is yet to arrive. Artificial Intelligence has proven its role as a game changing factor in an increasing number of fields, causing transformations unimaginable in the past. It's now showing glimmers of how it might forever change the learning process, one of the oldest skills that mankind has mastered. TNW Conference won best European Event 2016 for our festival vibe.