When Artificial Intelligence and Social Media Marketing Collide


Both artificial intelligence and social media marketing are getting a lot of attention nowadays because of their huge benefits and growth potential. This feature can be used in various ways by the brands for developing their social media marketing strategies to further increase the reach and success of their social media marketing campaign. There are many creative social media marketers who are awesome at creating awesome contents. The various AI tools help them to collect the valuable insights from the data collected through various social media platforms to get incredible insights on the customer taste and preferences.

Teaming humans with robotic AI will remake modern manufacturing


"Through 3D printing, fast automation, artificial intelligence, advanced IT systems," Weber said. His lab recently trained a Baxter assembly robot to understand and respond to natural language commands. Researchers from MIT's Computer Science and AI Lab (CSAIL) recently revealed their similar efforts, which they've dubbed ComText -- as in "commands in context". The current problem is that robots generally see the world at a relatively low level -- in pixels and sensor readings -- but humans see it as related concepts, connected to form reasoning and higher order thinking, Paul explained.

Drones and the Age of Automation


Deep Learning or DL is a subfield of machine learning which makes use of artificial neural networks, a mathematical system inspired by the way neurons function in the human brain. AI is fast becoming an integral part of the drone industry by enhancing the intelligence of the drone systems with respect to flight operations, data management and most importantly traffic management. DL as already discussed earlier is an AI technique that gains knowledge through training a neural network, a computer system that's designed to process information like the human brain. It provides a complete end to end solution where it will design the optimum flight path for the drone in order to capture the most complete data for any use-case, fly the drone across this flight path and generate and analyze thorough 3D models based on the data captured.

Machine Learning as a Service โ€“ MLaaS


To help fill the information gap on feature engineering, MLaaS hands-on can help and support beginning-to-intermediate data scientists how to work with this widely practiced phenomena. Explaining or gaining common practices and mathematical principles to help engineer features for new data and tasks. MLaaS these days provides full automation of essential, yet time-consuming activities in predictive model construction, such as fast variable selection, variable interaction modeling, and variable transformations or best model selection. Conclusion โ€“ At end and at heart we all now the dirty secret no matter how good the algorithm is, no matter how good I as data scientist, no model can perform magic if direction, intension, time and goal is not set.

Understanding the Written Word Using Machine Learning and Natural Language Processing (NLP)


Removing stop words ensures that NLP is only applied to words that add meaning to the sentence and thereby improves the speed at which NLP routines can be executed. Natural Language Processing: how can machines identify topics that people are talking about? The service has returned JSON, in the Key Phrases node, the key phrases "staff", "wonderful experience" and "rooms" have been identified. For example, in 2016, DeepMind, (Googles artificial intelligence company) formed a partnership with Moorfields Eye Hospital in London.

Understand these 5 basic concepts to sound like a machine learning expert


The truth is, you've been training machine learning models for years now, probably without realizing it. We are not at the point in technology where a machine learning platform will achieve 100% accuracy with identifying bananas in pictures. There are lots of different ways a ML platform can implement training sets to predict things. NL -- Neural networks is one of these ways a machine learning model can predict things.

Lawyers are turning to machine learning to ease caseloads


Adaption is not only necessary to remain competitive in terms of offering alternative channels, the use of digital technology can also assist with the amount of work involved with the legal process. To assist legal teams with this data review process artificial intelligence platforms can be used. In addition, intelligent machines can be used to assess decisions made by judges, to work out how case law is set and what the decision of a particular judge is likely to be. According to a review by Forbes, the use of machines to assess legal cases can reduce the hundreds of hours required to trawl through case notes considerably.

How artificial intelligence is revolutionizing healthcare


Your.MD is an AI-powered mobile app that provides basic healthcare. The chatbot asks users about their symptoms and provides easy-to-understand information about their medical conditions. Health assistants save patients a trip to the doctor for more trivial diseases. With the help of machine learning algorithms, Morpheo is assisting doctors by automating the identification of sleep patterns.

Making Machine Learning Accessible: 3 Ways Entrepreneurs Can Apply It Today


Unlike traditional models, which require specific rules and feature sets to extract meaning from data, deep learning models autonomously draw conclusions and create their own classification rules from unstructured data. Given enough time and data, deep learning models can make sense of virtually any unstructured data set. Now, thanks to the 2.5 quintillion bytes produced per day -- much of it publicly available via Google and YouTube -- and massive improvements in cloud computing technology, deep learning isn't just viable -- it's inevitable, and it's profitable. It uses a four-pronged approach, including data crawling, natural language processing, machine learning and artificial intelligence, to help business leaders optimize prospect data and sell more efficiently.

IBM and WGV Hackathon at Watson IoT Munich Center


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