Artificial Intelligence is set to change the dimensions of anything and everything in the coming days. Machine learning techniques are going to handle a lot of things with far better excellence and accuracy than the humans. Media industry was buzzing when US-based The New York Times and China-based Southern Metropolis publications made use of the robots to run pilot programs. However, an India-based company NewsBytes has worked on a bot called Yantra which by using the machine learning technology will deliver contextual news and reports to the users. The AI-engine of the company termed as'Brahmastra', their in-house engine uses natural language processing techniques and has an inverted'Question-Answering' system developed by the company which has dedicated questions and different sets of answers.

Watson won't be wearing anything fancy to the Grammys this weekend, but that's not going to keep it from judging everyone else's outfit. For the 60th anniversary of the music awards, the Recording Academy is partnering with IBM to bring its artificial intelligence to the red carpet. On Sunday night, IBM will deploy its AI platform to analyze videos and photos of nominees and attendees as they arrive at the ceremony in New York. In addition to identifying each person, Watson will be able to understand styles, learn about this year's fashion trends and compare them to those of previous years. People will then curate those findings, along with a selection of the many photos and videos taken by photographers, and upload them to the Grammys website for fans to learn more about their favorite musicians along with those honored decades ago.

Recent tech news report that IBM's Watson has already been employed as a dress designer, a chef, and a movie director. But what is it exactly? IBM Watson is a question answering computer system capable of answering questions posed in natural language based on cognitive computing. To replicate a human's ability to answer questions, Watson accesses 90 servers with a combined data store of over 200 million pages of information, which it processes against six million logic rules. You might also want to watch official IBM's video about how Watson works: Please press the clap button and help others find this story. Did you know you could give up to 50 claps?

The scale and time pressures involved in effectively meeting HR goals today can feel insurmountable, even in moderate sized organizations. However, across industries, emerging technologies like artificial intelligence are helping to relieve this burden, freeing up time for HR professionals to focus on strategic initiatives. Analysts predict that AI augmentation will recover 6.2 billion hours of worker productivity by 2021 and that one in five workers engaged in mostly non-routine tasks will rely on AI to do a job by 2022. But you shouldn't wait until then to prepare your team for AI in HR – there are steps you can take now. AI works like most objective and analytical human minds, but at a scale and speed that humans alone cannot match.

Discover new ways to build intelligence into your iOS apps. With IBM Watson Services for Core ML, it's easy to build apps that access powerful Watson capabilities right from iPhone and iPad, so you can provide dynamic, intelligent insights that improve over time. Your apps can quickly analyze images, accurately classify visual content, and easily train models using Watson Services.

One of IBM's first partners Harman will demonstrate Watson Assistant at the event through a digital cockpit aboard a Maserati GranCabrio, though the companies didn't elaborate on what it can do. In fact, IBM already released a Watson-powered voice assistant for cybersecurity early last year. You'll be able to access Watson Assistant via text or voice, depending on the device and how IBM's partner decides to incorporate it. So, you'll definitely be using voice if it's a smart speaker, but you might be able to text commands to a home device. Speaking of commands, it wasn't just designed to follow them -- it was designed to learn from your actions and remember your preferences.

Visual Question Answering (VQA) is an increasingly popular topic in deep learning research, requiring coordination of natural language processing and computer vision modules into a single architecture. We build upon the model which placed first in the VQA Challenge by developing thirteen new attention mechanisms and introducing a simplified classifier. We performed 300 GPU hours of extensive hyperparameter and architecture searches and were able to achieve an evaluation score of 64.78%, outperforming the existing state-of-the-art single model's validation score of 63.15%.

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The feature appears to work by asking the app to play an artist, album, song, genre or playlist. Hunter found it by pulling up Spotify's search screen. In the bottom right-hand corner, there was a microphone button. Hitting it brought up entirely new voice options. This venture makes sense, given Spotify's hardware ambitions.