Posts Tagged ‘watson’

Watson Rock, Paper, Scissors

Sunday, June 26th, 2016

A simple hands-on activity to let kids train a machine learning classifier to be able to play Rock, Paper, Scissors.

Screen Shot 2016-06-26 at 13.59.20

I’ve written and spoken before that I think we should do more to introduce children to the idea of machine learning. And I’ve tried introducing my two kids to it, such as by making a Code Club-style game with them: we built a system to play Guess Who, that they trained both to understand what you say and to recognise the characteristics of faces from photos.

This weekend, we tried out another idea – Rock, Paper, Scissors from a web app, using the web cam to see your moves, and training a system to recognise your hand signs.

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The skills implications of Cognitive Computing

Wednesday, April 29th, 2015

STEMtech is a conference about the education of science, technology, engineering and maths. The attendees are an interesting mix of people from education and policy makers, as well as people like me from industry.

This year, they invited me to do a talk. My slides are shared but they’ll make no sense by themselves. What follows is roughly what I think I said.

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How to use the IBM Watson Relationship Extraction service on Bluemix

Sunday, January 25th, 2015

Before Christmas, I wrote about how I used the Watson Relationship Extraction service on Bluemix to pick out the things mentioned in news stories, as part of a mobile app we built on a hackday. I’d still like to do something more with that app, but in the meantime I should at least share how I did the Relationship Extraction bit.

From the official doc for the service:

From unstructured text, Relationship Extraction can extract entities (such as people, locations, organizations, events), and the relationships between these entities (such as person employed-by organization, person resides-in location).

This is provided as a hosted service on IBM Bluemix where any developer can sign up and give it a try.

It’s available as a documented REST API, but as part of using it in the hackday, I needed to write a bit of code around that, just to prepare the request and parse the response. I think it’ll save me time to reuse this the next time I want to build something with the API, so I’m sharing it as a standalone package.

In this post, I’ll walk though how you can use it, with a small app that grabs the contents of a BBC News story and picks out the names of people mentioned in the story.

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Watson News Companion

Friday, December 12th, 2014

newscompanion screenshotWe recently ran a hackathon at work: people within IBM were invited to try building a mobile app aimed at consumers using Watson services. It was a fun chance to try out some new ideas, as well as to build something using our APIs – dogfooding is always a good thing.

I worked on a hack with David which we submitted on Wednesday. This is what we came up with, and how we built it.

The idea

A mobile app that will help users to digest the news by explaining references in stories and providing greater context.

Background

It’s difficult to find the time nowadays to properly read and understand what’s going on in the world. We rarely have the time to sit and read through a newspaper. Instead, we might quickly read news stories online from our smartphones and tablets. But that often makes it difficult to understand the broader context that a story is in. There might be references in the story to people, places, organisations or events that are unfamiliar.

Watson could help. It could be an assistant as you read the news, explaining unfamiliar references and the broader context.

Features

Our Watson News Companion demo is a mobile news reader app that:

  • anticipates questions and suggests areas where it can help improve understanding
  • provides answers to questions without needing the users to lose their place in the story
  • allow the user to dig deeper with their own follow-up questions


A video walkthrough of the hack

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Talking about IBM Watson (again)

Thursday, July 17th, 2014

As I mentioned in May, I was lucky to be able to go to Thinking Digital this year and talk about what we’re doing with Watson.

I’ve just noticed that they’ve made a video of my talk available. I haven’t dared watch it (does anyone like watching videos of themselves?), but I figured I should share it anyway!

Thinking Digital 2014

Saturday, May 24th, 2014

This week I went up to Newcastle for Thinking Digital.

It was the seventh Thinking Digital, but my first.

I’d seen a bunch of references to it being the UK’s answer to TED, the tickets aren’t cheap, videos from previous years look slick and professional, it’s held in The Sage which is a hugely impressive venue, they manage to get a great line-up of speakers, and the logistics in the run-up to the event were more organised than any event I’ve been to before.

So… I was expecting a cool and geeky, if faceless, serious, formal, and intimidating event.

I’d read it completely wrong. It’s absolutely a professionally run event. And there was no shortage of cool geekiness. But, more than that, the organizer, Herb Kim, has created a real sense of community in it. There’s a feeling of almost familial warmth amongst attendees who come year after year after year.

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Demonstrating IBM Watson for healthcare

Saturday, February 9th, 2013

I work on a computer system called IBM Watson – I might have mentioned it once or twice before?

Yesterday, IBM unveiled the progress that we and our partners have made with Watson in healthcare at an event in New York.

IBM Watson: New Breakthroughs Transform Quality Care for Patients

I didn’t get to go, but I did keep half an eye on what was happening through twitter. Here are some of the tweets that caught my eye.

 

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What has Watson been doing this year?

Thursday, December 27th, 2012

IBM Watson is a computer system created to answer questions – questions posed in unstructured, free, natural English language.

It answers using knowledge that it builds for itself by reading and understanding the contents of books and other documents.

It learns how to identify answers by being trained, learning from experience how to interpret the evidence in it’s knowledge.

I wrote a (long and rambling) post in January about work that had been done on Watson since it was unveiled to the world.

Here’s a quick overview of a few things that’s happened since then.

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