Stepping out into a world that is more and more connected, we sometimes come to a crossroad and wonder if our lives are being improved by this technological advancement. We have debated, and continue to debate if modern medicine technologies are leading to the bionic man or just allowing for an extended and more fulfilled life. In the latter case, technology, since the evolution of man has allowed us to withstand the environment, disease, or even ourselves in order to achieve what some may call revolutionary. And, today with AI platforms becoming available to build the next generation of technology for humankinds’ evolution, we may soon see the transcendence that we understood was only in cinema.
IBM Watson can be seen as the next generation of artificial intelligence, but it is currently only at the precipice of what is possible. At first you think, “oh I remember Watson on Jeopardy”, the infamous computer that competed against humans in an everyday quiz show… but in reality, it is more advanced than you could ever imagine. IBM has taken on the task of improving the base of Watson, and injecting it with a cognitive framework that transforms real-time unstructured data into structured analytics that can be used to set the foundation for building the next generation of intelligent products and solutions. This will mean the evolution of robotics (and I don’t mean Terminator), where Aldebaran robots are managing your local clothing store from greeter to sales person or even cashier. Although, this may have an impersonal feeling it could make the day at the mall much more efficient.
An initial step in this technology evolution for IBM Watson resides within language. The words that we produce both verbally and written are all forms of code that make up the way we communicate our sentiments at any level. Understanding communication sentiment is extremely important for businesses that are trying to connect with consumers, but most of what the data that companies house works off of structured information similar to “likes” on Facebook or re-tweets on Twitter. Watson uncovers sentiment from “natural language”, which can include linguistic differences, in order to reach a level of cognitive understanding. The combination of Watson’s cognitive analysis for natural language with a company’s smart data can, and has allowed for product advancement. One example is MediaWen, a company using IBM’s Bluemix services in their video dubbing in order to create subtitles available in multiple languages with speech to text natural language recognition.
The marriage of these data types is also being used in a region of California, where infrastructures have been put in place to detect sentiments in Twitter messaging, and predict everything from changes in traffic to public health. Data mining everyday “Tweets” in real-time to identify escalations in the type and tone of language to provide early detection to city or statewide issues, where the right services can identify solutions or prepare for what is to come. Remember all those times when a “Critical Mass” was scheduled in San Francisco and slowed your commute home? Well… that may not happen in the future because Watson is troubleshooting in order to predict traffic problems from Critical Mass in SF or any other traffic indicator for that matter.
The intersection of the connected world is here, and it is touching every facet of the physical and digital world, enabling a more efficient ecosystem.
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