Over the past few months Google, Microsoft and Facebook have taken major decisions to make their artificial intelligence APIs openly available to all. IBM have opened their Watson API on a 'freemium' basis and Elon Musk launched the OpenAI project with a star-studded list of backers; Palantir CEO Peter Thiel, LinkedIn founder Reid Hoffman and Y Combinatorpresident Sam Altman.
These hugely powerful tools, which are used, developed and backed by the world's most advanced technology companies, are now available to anyone with the skills to use them.
Whilst these announcements haven't quite drawn the media attention of an iPhone launch, their significance and reach may be far greater.
The point is this: using these toolkits, individually or combined, anyone can integratetransformational AI or machine learning platforms - which are as sophisticated as anything currently on the market - to their business at on a pay as you go or free basis.
So what does that mean? It means that any task currently performed by a costly black box AI platform such as identifying where to drill for oil, predicting disease outbreaks, optimising scientific experiments to develop new products or predictive maintenance can now be done in-house for the price of a data scientist's salary or consultancy fee, using these openplatforms and without losing any control or oversight of your data.
This is very important for a lot of the world's businesses and they need to take it seriously. If its true potential is realised it will unleash a new generation of innovative startups that apply the latest AI techniques to disrupt the establishment.
Open AI and big business: an opportunity and a threat
Most big companies have a data strategy to help them make better decisions faster. In many cases these large, data heavy organisations rely on these enigmatic black boxes to turn their data into insights. These come with a high price tag and often involve allowing valuable data outside of their company walls and potentially out of their control.
Now, with the right people and expertise they can build their own tools to their specification whilst maintaining complete control of their valuable data. It could save them a lot of money and opens many new opportunities to use data in a more bespoke and business focused manner. And because they retain control, it allows them to better understand not just the hidden patterns in their data, but the reasons for those patterns and how to better convert that data into knowledge and actionable insight.
But this also presents a threat to the established order of things.
The high costs associated with black box platforms has meant only larger enterprises could afford them. But now small companies have access to the AI and machine learning previously only available to the big players.
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