The oil price crash of 2014 and the global'digitalization and disruption' drive coincided in a rather bizarre way to push the oil industry to seek cost cuts through innovation and new technologies. Big Tech was only too pleased to help Big Oil, seeing a new revenue stream in an industry long thought to be of the'dinosaur' type that was too slow to embrace new ways of doing things. Many oil and gas firms, especially the world's biggest, are already using data analytics, cloud computing, digital oil fields, digital twins, robotics, automation, predictive maintenance, machine learning, and even AI. The technology giants have seized the opportunity to sell such services to Big Oil, and top managers at Amazon Web Services, Microsoft Azure, and ABB Group, to name a few, flocked to this week's top energy industry event CERAWeek by IHS Markit in Houston to pitch their solutions to a wider audience. "A great wave of innovation and technology is transforming the industry and reshaping the energy future," said Daniel Yergin, conference chair and vice chairman of IHS Markit.
Before I explain what Q Learning is, I will quickly explain the basic principle of reinforcement learning. Reinforcement learning is a category of machine learning algorithms where the systems learn on their own by interacting with the environment. The idea is that a reward is provided to the agent if the action it takes is correct. Otherwise, some penalty is assigned to discourage the action. It is similar to how we train dogs to perform tricks, give it a snack for successfully doing a roll and rebuke it for dirtying your carpet.
A display of robots that mimic the bio-mechanics of animals for locomotion. Mimicking animal forms of locomotion may be more appropriate for traversing rough terrain, and interacting in human environments. Animal movements covered in this video include Robotic Snake, Robotic Dog, Robotic Dragonfly, Robotic Kangaroo, Robotic Cheetah, and Robotic Bird.
We recently announced the strategic alliance between Jidoka and BigML, where we explained the integration of RPA with other technologies such as Machine Learning. With this integration, Jidoka can provide Machine Learning capabilities in their RPA process automation platform. To explain the advantages and possibilities offered by this integration, today we present a practical example of the application of both technologies, Jidoka's RPA and BigML's Machine Learning: the automation of an e-mail classification process, a use case that will be presented by Jidoka's CEO, Víctor Ayllón, at the #MLSEV, our first Machine Learning School in Seville, which will be held on March 7-8 in Seville (Spain). Imagine for a moment that you are responsible for the customer service department of a large company. You and your team receive on a daily basis a very large number of customer emails that are addressed to different departments of the company.
Co-founder of Google Brain and former Chief Scientist at Baidu, Andrew Ng, has unveiled an AI Transformation Playbook. The guide to successfully adopting AI in enterprise draws on insights gained from leading AI teams at Google and Baidu. Andrew Ng claims that, "it is possible for any enterprise to follow this Playbook and become a strong AI company." However, it is primarily intended for larger enterprises with a market cap/valuation from $500 million to $500 billion. The AI Transformation Playbook is distributed freely on the Landing AI website.
Access to skilled workers is already a key factor that sets successful companies apart from failing ones. In an increasingly data-driven future - the European Commission believes there could be as many as 756,000 unfilled jobs in the European ICT sector by 2020 - this difference will become even more acute. Skills gaps across all industries are poised to grow in the Fourth Industrial Revolution. Rapid advances in artificial intelligence (AI), robotics and other emerging technologies are happening in ever shorter cycles, changing the very nature of the jobs that need to be done - and the skills needed to do them - faster than ever before. At least 133 million new roles generated as a result of the new division of labour between humans, machines and algorithms may emerge globally by 2022, according to the World Economic Forum.
Learn how to solve challenging machine learning problems with TensorFlow, Google's revolutionary new software library for deep learning. If you have some background in basic linear algebra and calculus, this practical book introduces machine-learning fundamentals by showing you how to design systems capable of detecting objects in images, understanding text, analyzing video, and predicting the properties of potential medicines. TensorFlow for Deep Learning teaches concepts through practical examples and helps you build knowledge of deep learning foundations from the ground up.
The Redmond, Washington-based tech giant is competing with Alphabet Inc.'s Google, International Business Machines Corp. and a clutch of small, specialized companies to develop quantum computers – machines that, in theory, will be many times more powerful than existing computers by bending the laws of physics. Two recent articles caught my eye. The first was in Financemagnates.com It was an interview with Michael Bancroft of Bloomberg TV, in which he spoke of the spreading popularity of blockchain technology, not just for protecting cryptocurrencies but for a growing number of uses including cybersecurity. He said that before too long, "what we're likely to see is blockchain being employed for cybersecurity… [in] governments who are looking to secure important files and records safe from hackers."
Geeta Manjunath turned entrepreneur in the backdrop of a tragedy. In 2017, a cousin she was really close to succumbed to breast cancer at a relatively young age. Breast cancer is the most commonly occurring cancer in women and the second most common worldwide. Gopinath, who has a PhD in computer science from the Indian Institute of Science, applied her scientific mind to the issue. Ubiquitous screening and early detection vastly reduces fatality from cancer.
The Facebook chatbot, Tabatha, part of the company's global "Think. Breathe" asthma awareness campaign, was created to help people understand the impact asthma has on their daily lives in a private environment. Artificial Intelligence driven, Tabatha is designed to help those with asthma to self-identify symptoms, learn more about their risk and prepare for a doctor visit. Tabatha was the first disease awareness resource able to measure not only to what extent the information motivated people to learn more, but also whether they intend to take action and see their doctor.