Opportunities in machine learning

I continue to be intrigued by the potential that machine learning can contribute to internet offerings and human effectiveness in a broader sense. Clearly this isn’t idle thought as we’ve invested in this theme more than once. As we are all starved of time just keeping lines of communication open who has time to consistently process high volumes of data and drive improved insights & understanding.

The deeper the insights the more potentially valuable the technology. In the UK are we resourcing up for a world where data scientists will be increasingly valuable. On the surface these are roles that would appear to be hit by science funding constraints, which would be a shame. Behavioural learning frontiers need to continually be challenged; if globally we continue to push geographic boundaries and are making significant discoveries (http://bit.ly/TWIDeS) this should not be beyond us!

We are consistently looking to see how machine learning can be more broadly applied within technologies in the development of new markets and the disruption of existing ones.

Business software – yesterday, today & tomorrow

“The most important, and indeed the truly unique, contribution of management in the 20th Century was the fifty-fold increase in the productivity of the MANUAL WORKER in manufacturing. The most important contribution management needs to make in the 21st Century is similarly to increase the productivity of KNOWLEDGE WORK and the KNOWLEDGE WORKER.”

Peter Drucker

Yesterday’s business software focused on capturing data and reporting it upwards.

Today’s business software captures knowledge, data, sentiment and actions and plays it back, predominately upwards, but also sideways and downwards in an organization. It does it in real time and is cognizant of relationships beyond the organizational chart.

We are interested in tomorrow’s business software that will continue to evolve beyond what today’s software offers in striving for improvements in knowledge worker effectiveness.