watson

February 6, 2018

Chatbots: Some tricks with slots in conversations

If you follow my private blog you might remember that I have been using the IBM Watson Conversation service and DB2. My goal was to write a database-driven Slackbot, a Slack app that serves as chat interface to data stored in Db2. I will write more about that entire Slackbot soon, but today I wanted to share some chatbot tricks I learned. How to gather input data, perform checks and clean up the processing environment.

Continue reading

January 29, 2018

Chatbot Best Practices

One of the most frequent questions clients ask when visiting a Cloud Garage is "Can you build us a chatbot?" This question is reflective of an industry-wide trend towards more natural language in computerised interactions, and also more automation of interactions currently handled by humans. Today, there are currently more than 33,000 chatbots on Facebook Messenger alone. Many businesses are turning to Watson Conversation to help take out cost and improve user satisfaction. Our Hursley Labs colleague Simon Burns has written an excellent series of articles on how to write great Watson chatbots, which you should definitely go read. Think of this blog as a supplement, with our experiences from the field. To address this pressing question, I’ve compiled a set of considerations for you to address when deciding whether a chatbot is truly the solution to your business needs.

Continue reading

November 20, 2017

Webinar: (Case study) GreenQ uses serverless technology to improve city services

As the leanest form of container-based application computing, serverless functions as a service (FaaS) run code exactly when needed, at exactly the right scale, either through direct API invocation or as triggered by specific other events. Functions are powerfully well-suited for managing API connections across clouds, processing IoT data streams, and implementing connections between microservices […]

Continue reading

November 8, 2017

Home automation powered by Cloud Functions, Raspberry Pi, Twilio and Watson

Over the past few years, we’ve seen a significant rise in popularity for intelligent personal assistants, such as Apple’s Siri, Amazon Alexa, and Google Assistant. Though they initially appeared to be little more than a novelty, they’ve evolved to become rather useful as a convenient interface to interact with service APIs and IoT connected devices.

Continue reading

November 8, 2017

Interpreting Spring Social Twitter Data with Watson Tone Analyzer

In this post, I'll show you how to build a basic Spring app with Twitter login using Spring Social. Then we'll use Watson Tone Analyzer to determine the dominant emotion from each of the tweets on the time of the logged-in user. The project we will create will be similar to the Accessing Twitter Data Spring guide, but with a few modifications.

Continue reading

November 6, 2017

Introducing the IBM Cloud Lite account

What if you had unlimited time to tap into a growing ecosystem of AI-infused services and runtimes to build your apps? And what if you could do it at no cost? Today, we're making that possible. We are excited to announce the IBM® Cloud Lite account - a free account that never expires. Ever. Seriously.

Continue reading

November 2, 2017

Analyzing Spring Social Facebook Data with Watson Personality Insights

In this post, I'll show you how to build a basic Spring app with Facebook login using Spring Social. Then we'll use Watson Personality Insights to analyze the profile of the logged-in user. The project we will create will be similar to the Accessing Facebook Data Spring guide, but with a few modifications.

Continue reading

November 1, 2017

Introducing the IBM Cloud Lite account

What if you had unlimited time to tap into a growing ecosystem of AI-infused services and runtimes to build your apps? And what if you could do it at no cost? Today, we're making that possible. We are excited to announce the IBM® Cloud Lite account - a free account that never expires. Ever. Seriously.

Continue reading

October 3, 2017

Lifelong (machine) learning: how automation can help your models get smarter over time

Imagine you’re interviewing a new job applicant who graduated top of their class and has a stellar résumé. They know everything there is to know about the job, and has the skills that your business needs. There’s just one catch: from the moment they join your team, they’ve vowed never to learn anything new again. You probably wouldn’t make that hire, because you know that lifeMachine Learning Brainlong learning is vital if someone is going to add long-term value to your team. Yet when we turn to the field of machine learning, we see companies making a similar mistake all the time. Data scientists work hard to develop, train and test new machine learning models and neural networks. However, once the models get deployed, they don’t learn anything new. After a few weeks or months, become static and stale, and their usefulness as a predictive tool deteriorates.

Continue reading