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IBM is blazing a trail when it comes to how robots interact with humans. The company recently upgraded its Watson AI with a'Tone Analyzer' service that allows it to understand nuance and tone of text. By analyzing word choice, emoji use, and context the AI is learning to understand how we talk to each other. There are thousands of companies doing work in the AI space right now, but most of it happens in the background. It's one thing to teach an AI how to find what you're looking for on the internet, it's more impressive to give AI manners and train it to be a customer service agent.

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IBM announced on Thursday that it had reached a 10-year research partnership agreement with the university worth nearly a quarter of a billion dollars. The IBM-MIT partnership will also study the intersection between machine learning and quantum computing. Interestingly, this focal area will aid both fields, with AI helping to identify and characterize quantum devices and with quantum computers helping to optimize machine learning methodologies. But those aren't the only commercial fields being investigated, researchers will also look into the "economic implications of AI and investigate how AI can improve prosperity," according to an IBM press release.

Let's pretend that we've been asked to create a system that answers the question of whether a drink is wine or beer. This question answering system that we build is called a "model", and this model is created via a process called "training". The goal of training is to create an accurate model that answers our questions correctly most of the time. But in order to train a model, we need to collect data to train on. This is where we begin.

When it's not busy healing America's broken criminal sentencing system, Watson is creating highlight videos of tennis matches. That's probably one of the things one could say if IBM's AI system were human. The tech titan has just launched a suite of Watson-powered AI solutions for its enterprise customers, and the US Open is already using one of them to generate highlights of its matches. IBM calls the suite "Watson Media," and the US Tennis Association is using one of its features called "Cognitive Highlights." This particular solution finds the most exciting parts of a match by analyzing the crowd's cheers, as well as the players' gestures and facial expressions. It then automatically generates videos of the most thrilling moments, which are then posted on Facebook and published on the US Open apps.

If you want to learn how to use Python notebooks on IBM Bluemix to do machine learning with your SAP data, you may have a look at this blog entry. It provides detailed step-by-step explanations how to accomplish this.

Enter the 21st century building's "digital twin." Think of it as a dynamic, virtual model of the physical structure, powered by the massive amounts of data that a single structure generates around the clock--everything from design specs to equipment parameters and live occupancy data. With IoT-enabled sensors tracking a building's "pulse" and feeding data back into next-generation systems such as Watson, facility owners and managers today are able to reconstruct every relevant metric from a physical structure in a digital environment. Every asset--from the HVAC system to the vending machines--can be monitored and analyzed remotely. But how do you manage those assets over time?

How was Watson trained to understand both culture and music? The creative process was simple. To understand culture, AlchemyLanguage API first uncovered the most pervasive themes in each year. Then, Watson Tone Analyzer read blogs, news articles, and social media to gauge the sentiment around those themes. With this data, Watson arrived at an emotional fingerprint of culture.

Smith: What would you say is the public's biggest misperception about Watson? What is one thing that folks might think that Watson can do that it actually cannot? Harbour: The biggest misperception about Watson is that it's meant to replace humans. Watson works with humans to enhance the abilities of professionals at every level, from highly specialized surgeons to oil drillers, and automates many basic tasks. However, no matter how advanced the technology, some jobs -- specifically, those that rely heavily on empathy, ethical judgment, and social interaction -- will always be performed better by humans.