IBM Watson Developer Cloud (WDC) services put the power of machine learning technology in the hands of developers to extract insights from unstructured data (text, speech, and images). To serve developers and enable them to tackle a wide spectrum of applications ranging from general consumer applications to various enterprise-specific applications, the IBM Watson team offers several pre-trained services as well as a rich set of customization capabilities. For the pre-trained services, the IBM Watson team has taken on the responsibility of acquiring the right data to train these services, generating trained machine learning (ML) models and providing out-of-the-box functionality for developers. Natural Language Understanding (NLU), Personality Insights (PI), Tone Analyzer (TA), Speech-to-text (STT), Language Translator (LT), and Visual Recognition (VR) are some of the pre-trained WDC services. Developers like these services because they're intuitive, easy-to-use, require no extra ML training effort and work well for applications tackling a general domain such as enriching web URLs, image tagging or analyzing sentiment of social media posts.

For this tutorial, we're going to power TJBot with APIs from Watson Developer Cloud. We'll start by putting a voice interface onto TJBot, then give it the ability to converse and understand your emotional tones. In part 2 of the tutorial, we'll transfer the code onto a Raspberry Pi and put the whole thing into the physical TJBot itself. For the sake of simplicity, we'll keep the conversation simple.

Using deep learning to harness and explore large datasets has become increasingly important for businesses in every industry. There are many companies and services trying to make this a tenable problem, and yet, more people are still required to munge together home-grown solutions to meet their specific needs. Fortunately, there are many tools and resources in the market today that make building cognitive apps more doable. Here are nine interesting tools and resources I've seen and/or worked with recently to build cognitive apps: 1. Deeplearning.net: Deep Learning is a new area of Machine Learning research, which has been introduced with the objective of moving Machine Learning closer to one of its original goals: Artificial Intelligence.

We all remember Watson from Jeopardy, right? It's not just Jeopardy that Watson is used for. Watson is famous for its cognitive computing system. Cognitive computing is another name for artificial intelligence. In other words, Watson learns.

We all remember Watson from Jeopardy, right? It's not just Jeopardy that Watson is used for. Watson is famous for its cognitive computing system. Cognitive computing is another name for artificial intelligence. In other words, Watson learns.

We all remember Watson from Jeopardy, right? It's not just Jeopardy that Watson is used for. Watson is famous for its cognitive computing system. Cognitive computing is another name for artificial intelligence. In other words, Watson learns.

IBM Watson Provides Self-Service AI for Developers By Darryl K. Taft Posted 2016-05-07 Print In what IBM calls "self-service AI," the company enables developers to easily tap into the power of its Watson APIs to build cognitive apps. When IBM initially launched its Watson cognitive computing platform, one of the first questions on a lot folks' minds was, "When can I tap into the power of Watson?" IBM responded by opening up Watson to developers via the Watson Developer Cloud, which offers Watson services and APIs as well as useful documentation and tutorials, starter kits and access to the Watson developer community. IBM started slow and continued to evolve its Watson strategy for developers. The company started with just a few Watson partners and offered just a handful of Watson services.

Rob has worked for IBM for almost two decades, first as Fellow and Chief Architect for the Service Oriented Architecture (SOA) foundation. His current project is Watson, the company's cognitive computing technology that aims to change the way machines interact with humans at the linguistic, emotional and semantic levels. "Cognitive Computing" is like intelligence amplification for humans If we were to put "cognitive computing" into a category, it would probably look more like "intelligence amplification" (IA) rather than Artificial Intelligence (AI). This is the idea that machine learning can amplify human knowledge, capabilities, and aid day-to-day procedural decisions. IBM Watson, located at the company's research center in Yorktown Heights, New York (via Wikipedia) "Watson processes information by understanding natural language, generates hypotheses based on evidence, and, because it becomes more capable and precise, Watson will help leaders and organizations make better, more confident decisions."

Solutions architects are the experts on our team at understanding and implementing Watson technology. They have developed this expertise by providing technical support to our partners through multiple mediums. Through their work, they have a deep understanding and point of view about the Watson APIs, but also the cognitive landscape at large. I interviewed solutions architect, Chris Ackerson on his thoughts on Watson and cognitive computing, as well as his specific tips and resources. Where do you see the Watson APIs growing in 2016 and beyond?