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Is AI the future of big data?

Back in January, it was predicted that AI would be one of the top tech trends for 2016. In fact, there have already been some very exciting developments in machine learning this year, suggesting a promising future for the technology.

Google’s driverless vehicles have been much discussed in recent months, for instance. As the prospect of self-driving cars taking to the road becomes increasingly likely, governments are looking into regulations on the subject; even Uber and Fiat are in talks to discuss a potential collaboration.

While this is fascinating in terms of society’s progress, it is hard to relate to on a human level – how can robots and machine intelligence possibly affect most individuals’ daily lives?

When AI is combined with big data, this is where we can start to witness the tangible, everyday transformation of how we live and work.

Interested in AI? By 2025, 30% of jobs will be taken over by robots: find out if yours is at risk.

Intuitive BI machines

Real-time, automated business intelligence is where the industry is now headed; big data will drive innovation according to Mike Olsen, software firm Cloudera’s CSO. Using AI techniques such as data pattern recognition, soon we will be able to train machines to create detailed reports based on real-time fluctuations in industry trends.

If we were able to teach computers to interpret data intuitively, as we do, we could enact real change. We could fix problems before they happen; we could adapt more effectively to our clients’ shifting needs. AI could transform the way we conduct business and empower decision makers.

This is not to say that data analysts should be concerned for their job security; totally unsupervised machine learning is still a long way off, with 70% of machine learning currently requiring at least partial human input.

AI: an effective substitute for human intelligence?

Recommended adverts are a perfect example of this – despite retaining thousands of pieces of information about a consumer, AI cannot accurately predict their likes and dislikes, leading to irrelevant suggestions.

As it stands, despite impressive progress, machines still cannot process data instinctively enough to appear authentic and human.  Incorporating machine learning into data analysis techniques could be the answer.

Data analysts of the future

Learning to work with machine intelligence might require some retraining for the data analysts of the future, yet it could be worth the expense: as a rare commodity in a tech-dependent economy, these AI skills could see their incomes soar.

With this in mind, for data experts, the rise of automation could be seen as a career challenge – an opportunity to be a pioneer in a changing market.

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