Not a day goes by without an important figure from the technology world acknowledging the immense potential of large-scale machine learning applications in virtually every industry. The award-winning researcher and scientist Professor Pedro Domingos of University of Washington recently mentioned “Algorithms increasingly run our lives. They find books, movies, jobs, and dates for us, manage our investments, and discover new drugs.” He then went on to add “The race is on to invent the ultimate learning algorithm: one capable of discovering any knowledge from data, and doing anything we want, before we even ask.”

Machine learning’s impending impact on jobs that so far were considered exclusive to highly skilled humans will likely remain a controversial yet unavoidable topic for the foreseeable future. Take for example Early Stage Startup Investing. Silicon Valley venture capitalists have had a big hand in funding startups that are strategically leveraging machine learning to radically disrupt old world industries like hospitality and transportation services. This has helped create the much celebrated “Unicorns” that are defining the pace of innovation in our evolving digital consumer economy, where it makes more business sense to optimize the utilization of existing assets than to own and operate them outright.

As brilliant as this strategy has been, the utilization of machine learning to drive decision making in early stage investing itself has remained mysteriously absent. A controversial recent article by Arlo Gilbert very succinctly articulates on this “dirty secret” of Silicon Valley, which stubbornly remains very human and relationship driven. As Gilbert puts it “A computer doesn’t worry about its next fund.”

Given the backdrop of a typical exponential technology, it is not too far-fetched to think that this kind of freedom from existing human biases combined with increasingly powerful predictive models crunching increasingly sophisticated new sources of structured and unstructured data may force the VCs hands to have a stance on whether they should embrace automatic start-up investing sooner than they realize. This also happens to be exactly what Kirk Kardashian of Fortune has investigated in his recent article titled “Could algorithms help create a better venture capitalist?”

At the heels of these developments, Telefónica’s global entrepreneurship and innovation network Telefónica Open Future_ (TOF_) and BigML are proudly partnering to build the World’s First Automated Early Stage Investing Platform to help usher a new way of technology investing. To make this a reality, the alliance will take advantage of PAPIs conference events series as they offer the best platform to introduce new predictive applications to the world:

• In all future PAPIs CONNECT events as well as the annual PAPIs conference, there will be a new startup battle section devoted to best startups actively working on state-of-the-art predictive apps.
• Both the invited startups as well as the eventual winner will be automatically selected by TOF_and BigML’s new algorithm. The winning startup will be offered an investment by one the TOF_ funds thereby making PAPIs the world’s first event where an algorithm automatically selects the contestants and the winner.

Machine learning innovators gathering in Sydney for this year’s International Conference on Predictive APIs and Apps are uniquely positioned to ride this new wave of change. The event is taking place in Sydney on 6 & 7 August 2015 and it is bringing together leaders from Amazon Machine Learning, BigML, Google Prediction API and Microsoft Azure ML on the same stage. As such, PAPIs events participants and followers who have a machine learning driven startup idea or a relevant ongoing project can now gain additional exposure and perhaps also secure a seed round investment from an established technology player with the foresight to go against the grain in true maverick fashion. As the original sponsor of PAPIs, BigML is looking forward to meet with our future contestants.