Machine learning now the top skill sought by developers

ZDNet

Developers want to learn the data sciences. They see machine learning and data science as the most important skill they need to learn in the year ahead. Accordingly, Python is becoming the language of choice for developers getting into the data science space. Those are some of the takeaways from a recent survey of more than 20,500 developers conducted by SlashData. The survey shows data science and machine learning to be the top skill to learn in 2019.


Artificial Intelligence: The future and your current reality

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Artificial intelligence (AI) has a future tech reputation that can probably speak for itself, but did you know just how much of an impact it already has on your current life? Keeping spam out of your email box may be one of the more obvious (and welcome) AI integrations. If you're social media savvy, you probably don't take the appearance of coordinated advertising across most platforms to be coincidental. You might later raise an eyebrow when the ads you're seeing on the Internet seem relevant to a conversation you had with someone over a messenger application, but you're pretty sure the people you talk to on website chat boxes are actual people. Or, maybe all of these things are part of an AI-infused reality you've grown to know and accept.


Designing the Future -- Tools for AI-Powered Service Platforms

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We live in a society under construction, and we are on the brink of an infrastructure paradigm shift. This is not sensationalist click-bait: it's the logic conclusion of some simple measurable observations. Here is why: Communication, energy, and transport (which are the basis of our economy and society at large) are changing rapidly -- and to the core -- due to breakthroughs in several technology fields. This shift is known as the second, third or even the fourth industrial revolution, depending on who you talk to. Either way, it is per definition a revolution if communication, energy, and transport are changed drastically simultaneously.


Hey.ai, an AI startup founded by ex-Googlers, launches personal analytics platform Technology Startups News Tech News

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Whether you post every cup of coffee to Instagram, model, vlog, or occasionally watch a YouTube video, there is a new artificial intelligence startup that enables you to analyze your content and interactions by people, time, or even sentiment. Hey.ai is a new consumer analytics and insights platform that helps users to discover interesting insights about themselves based on the social data. Today, Hey.ai, announces the public launch of its personal analytics platform. Founded by Hari Rajagopalan and the team that previously co-founded Chatbase at Google's Area120 incubator, Hey.ai helps you to make sense of your data. The platforms also helps you discover potentially offensive or dubious content you or your friends may have created.


AI Transforms Industrial IoT

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If you've been studying artificial intelligence and its growth, you'll know that the industry is well past its nascent stage now. There is significant maturity in its growth, and companies from diverse backgrounds are realizing the impact of incorporating data and AI into their ecosystems. In a bid to understand the dynamics of this data-centered growth, I teamed up with Hewlett Packard Enterprise (HPE) to do an analysis of their international survey on the present and the future of AI within the industrial sector. What percentages of companies are working on AI? How can AI transform industrial IoT for the better? Will it prove to be a job killer for us humans?


This AI thinks like you to solve problems

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The Lincoln Laboratory group was able to close the gap between performance and interpretability with TbD-net. One key to their system is a collection of "modules," small neural networks that are specialized to perform specific subtasks. When TbD-net is asked a visual reasoning question about an image, it breaks down the question into subtasks and assigns the appropriate module to fulfill its part. Like workers down an assembly line, each module builds off what the module before it has figured out to eventually produce the final, correct answer. As a whole, TbD-net utilizes one AI technique that interprets human language questions and breaks those sentences into subtasks, followed by multiple computer vision AI techniques that interpret the imagery.


Next recession to usher in wave of artificial intelligence

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The European Union needs to brace itself for the prospect of a new wave of technology and productivity resurgence in ten to fifteen years' time, spearheaded by the implementation of AI and robotics innovations. This was the message introduced by Stefan Crets, Executive Director of CSR Europe, who, opening the high-level event, said that digitisation required a new agility in the workplace and a new way of collaborating. "The future of work is determined by the actions we take today and the choices we make. What we want to do is exchange experience, pull the expertise together and find the best practices." Economist Mirko Draca, co-author of a London School of Economics (LSE) report commissioned by Huawei, entitled'The evolving role of ICT in the economy,' said that a new wave of automation had started.


Review: Artificial Intelligence in 2018 – Towards Data Science

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Artificial Intelligence is not a buzzword anymore. As of 2018, it is a well-developed branch of Big Data analytics with multiple applications and active projects. Here is a brief review of the topic. AI is the umbrella term for various approaches to big data analysis, like machine learning models and deep learning networks. We have recently demystified the terms of AI, ML and DL and the differences between them, so feel free to check this up.


Scientists grow functioning human neural networks in 3-D from stem cells

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A team of Tufts University-led researchers has developed three-dimensional (3-D) human tissue culture models for the central nervous system that mimic structural and functional features of the brain and demonstrate neural activity sustained over a period of many months. With the ability to populate a 3-D matrix of silk protein and collagen with cells from patients with Alzheimer's disease, Parkinson's disease, and other conditions, the tissue models allow for the exploration of cell interactions, disease progression and response to treatment. The development and characterization of the models are reported today in ACS Biomaterials Science & Engineering, a journal of the American Chemical Society. The new 3-D brain tissue models overcome a key challenge of previous models -the availability of human source neurons. This is due to the fact that neurological tissues are rarely removed from healthy patients and are usually only available post-mortem from diseased patients.