Original URL: http://www.theregister.co.uk/2014/02/07/ibm_watson_africa/

IBM to invest $100m and a decade into using Watson in Africa

Big Blue starts supercomputer project to help healthcare and education intiatives

By Brid-Aine Parnell

Posted in HPC, 7th February 2014 09:01 GMT

IBM is planning to invest $100m and 10 years on getting Africa hooked on its Watson supercomputer system.

Big Blue said that it wants to use the system in "Project Lucy", named after the earliest known human ancestor, to help the continent in key areas like healthcare, education, sanitation and agriculture.

"In the last decade, Africa has been a tremendous growth story - yet the continent's challenges, stemming from population growth, water scarcity, disease, low agricultural yield and other factors are impediments to inclusive economic growth," said Kamal Bhattacharya, director of IBM research in Africa.

"With the ability to learn from emerging patterns and discover new correlations, Watson's cognitive capabilities hold enormous potential in Africa - helping it to achieve in the next two decades what today's developed markets have achieved over two centuries."

The project certainly has some humanitarian aspects to it, but IBM is no doubt also hoping that the investment will get companies and clients on the continent – where economies are growing – hooked in to a Watson-based ecosystem and prove the supercomputer's worth.

The firm said that it would be setting up a pan-African Centre of Excellence for Data-Driven Development and recruiting universities, development agencies, start-ups and clients to "help fuel the cognitive computing market and build an ecosystem around Watson".

IBM is attempting to put Watson, made famous by its win on quiz show Jeopardy! three years ago, at the centre of a new business unit. The supercomputer was originally designed to answer questions in natural languages and make judgements based on its gigantic data banks.

In Africa, Big Blue said that Watson could be put to use crunching big data like food price patterns and poverty numbers and extracting correlations that will help to plan for the future. ®