Machine intelligence has, in recent years, emerged as one of the most exciting new frontiers in technology. It is powering innovative new approaches to tackling issues across almost every industry, from autonomous vehicles to agriculture and medicine. At Atomico we’re big believers that technology is not only capable of solving some of humanity’s biggest problems, but is indeed necessary to do so. Software, however, relies on hardware to deliver its potential. And when it comes to AI, current hardware is proving a poor fit for the task.

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23.05.2017

Fifteen years ago a technology company shipped PCs, operating systems, or word-processing software. Today, technology companies are at the core of most of the world’s major industries. Look at Facebook, Uber or Airbnb, who all leveraged technology to drive fundamental change in the way things are done. Machine learning is at the start of the same journey. Today it is still an emerging technology, used by a small number of cutting-edge companies to improve their products with more accurate insights or better user experiences.

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13.04.2017

Last week, Google DeepMind announced that they had open sourced Sonnet, a software library that draws on DeepMind’s internal best practices for quickly building neural network modules in TensorFlow. This is a great resource, leveraging the collective experiences of some of their 250 highly skilled engineers, released to enable others to more effectively apply machine learning to their problems. In fact, over the last few years, the world’s biggest tech companies (including Google, Facebook, Microsoft, IBM, Baidu, Amazon and more) and university research labs have open sourced at least 2.5 million lines of machine learning platform code (see table below), which equates to over 650 man years or $80m in development costs. These toolkits are now freely available online, and many such as TensorFlow and Paddle are accompanied by significant volumes of training and example materials. As such, they can be viewed as an incredible initial investment into any company looking to use machine learning as an enabling technology for their product.

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This post originally appeared on Medium,  If you look at the six most valuable public companies in the world today, you will notice something striking. Five of them are the tech companies Apple, Alphabet, Microsoft, Amazon and Facebook, founded on the West Coast of the US between 1975 and 2004, three of whom who have achieved this ‘most valuable’ status in the last five years.

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This post first appeared on Medium, and was written to coincide with the Nordic AI festival, taking place on 7 March 2017 in Copenhagen. Bill Gates a couple of weeks ago said something pretty extraordinary: he suggested that a so-called “robot tax” might not be a bad idea. The socialist candidate for the upcoming French election, Benoît Hamon, has made this idea part of his platform. Nobody was talking like this just two short years ago. How has this now become such a prominent topic and entered the mainstream?

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10.07.2016

AI being a discipline that has come of age emphatically in the last few years, significant European acquisitions like DeepMind, Swiftkey and, last week, Magic Pony, make a strong case that the region is at the vanguard of the current revolution.

To discuss how we can continue to build upon this momentum and support the European AI startup ecosystem, earlier this week we gathered a small group of visionary European entrepreneurs, academics and investors for a discussion.

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Visual mapping, like Google’s Street View, has traditionally been a complicated and lengthy process, resulting in significant time lags between the process of collecting the images and those images appearing online.

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We’ve always believed that successful founders can play a vital role in the growth of startups and the development of our ecosystem as a whole. That’s why we set up Atomico, and why we recently announced partnerships with a number of top European entrepreneur-investors to support our next generation of superstar founders.

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Like successful companies, successful ecosystems go through distinct stages. Having conducted one of the most comprehensive studies ever undertaken into European tech, it is clear to us that 2015 has been a breakthrough year in which our major hubs have gone to a new level.

View our report in full:

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