Content tagged with "Watson"

I was very excited to be invited along with some other IBMers to the Blackgang Pi event run by Dr Lucy Rogers on a semi regular basis at the Blackgang Chine theme park on the Isle of Wight.

Blackgang Chine is a theme park on the southern tip of the Isle of Wight and holds the title of oldest theme park in the United Kingdom. We were lucky enough to be invited along to help them modernise some of their animatronic exhibits, replacing some of the aging bespoke PCBs and controllers with Raspberry Pis running Node-RED and communicating using MQTT/Watson IOT.

EDIT: Hello readers, these articles are now 4 years old and many of the Watson services and APIs have moved or been changed. The concepts discussed in these articles are still relevant but I am working on 2nd editions of them.

Last time we discussed some good practices for collecting data and then splitting it into test and train in order to create a ground truth for your machine learning system. We then talked about calculating accuracy using test and blind data sets.

Last week, my colleague Olly and I gave a talk at a data science meetup on how IBM Watson can be used for data science applications.

We had an amazing time and got some really great feedback from the event. We will definitely be doing more talks at events like these in the near future so keep an eye out for us!

I will also be writing a little bit more about the experiment I did around Core Scientific Concepts and Watson Natural Language Classifier in a future blog post.

EDIT: Hello readers, these articles are now 4 years old and many of the Watson services and APIs have moved or been changed. The concepts discussed in these articles are still relevant but I am working on 2nd editions of them.

Introduction

I’ve recently been playing with trying to build a Watson powered home automation system using my Raspberry Pi and some other electronic bits that I have on hand.

There are already a lot of people doing work in this space. One of the most successful projects being JASPER which uses speech to text and an always on background listening microphone to talk to you and carry out actions when you ask it things in natural language like “What’s the weather going to be like tomorrow?” and “What is the meaning of life?” Jasper works using a library called Sphinx developed by Carnegie Mellon University to do speech recognition. However the models aren’t great – especially if you have a british accent.

Introduction

Being able to deal with typos and incorrect spellings is an absolute must in any modern search facility. Humans can be lazy and clumsy and I personally often search for things with incorrect terms due to my sausage fingers. In this article I will explain how to turn on spelling suggestions in retrieve and rank so that if your users ask your system for something with a clumsy query, you can suggest spelling fixes for them so that they can submit another, more fruitful question to the system.

Introduction

Retrieve and Rank (R&R), if you hadn’t already heard about it, is IBM Watson’s new web service component for information retrieval and question answering. My colleague Chris Madison has summarised how it works in a high level way here.

R&R is based on the Apache SOLR search engine with a machine learning result ranking plugin that learns what answers are most relevant given an input query and presents them in the learnt “relevance” order.

Please don’t cringe too much at my technical explanation of Watson – especially those of you who know much more about WEA and the original DeepQA setup than I do! This was me after a few days of reading the original 2011 and 2012 papers and making copious notes!

At the beginning of the month, I was lucky enough to spend a month embedded in the Watson Labs team in Austin, TX. These mysterious and enigmatic members of the Watson family have a super secret bat-cave known as “The Garage” located on the IBM Austin site – to which access is prohibited for normal IBMers unless accompanied by a labs team member.

During the week I was helping out with a couple of the internal projects but also got the chance to experiment with some of the new Watson Developer Cloud APIS to create some new tools for internal use. However, I can share with you a couple of the general techniques that I used since I think they might be useful for a number of applications