Credits: John Reign Abarintos x Unsplash

Fostering European Deep Tech champions

Introducing Deep.Circle & why collaboration is the new black

In order to define the concept of Deep Tech, let’s go back to its original definition firstly made by Swati Chaturvedi, founder of Propel(x), in July 2015: « create value with solutions to global challenges: climate change, food & resources management, migrations, cyberwarfare… ». At the end of 2017, a report made by TheBostonConsultingGroup alongside with Hello Tomorrow completed the definition by stating that « Deep-tech innovations are defined as disruptive solutions built around unique, protected or hard-to-reproduce technological or scientific advances ». They create value by developing new solutions, not only by disrupting business models. As they are pushing technologies’ limits forward, they face unique challenges.

Deep Technologies, such as Artificial Intelligence, Blockchain, Internet of Things, 3D Printing and Biotechnologies, represent a new wave of innovation. As a consequence, for most of segments ie healthcare, finance and real estate, agriculture: Deep Tech will be a strong driver of innovation and progress over the next decades.

Deep Circle genesis

Supporting the development of future Deep Tech champions in Europe

Europe has a strong technological know-how, boosted by powerful research and development institutions. Deep technologies are progressively reaching a level of maturity enabling concrete applications. However, the collaboration from a business standpoint is not efficient yet. These core strengths need to be unified with a digital and business approach. This way, the perfect ecosystem to attract talents and deliver value for Deep Tech users, business, entrepreneurs, investors, academics, and politicians, can be then created.

AI is considered as part of Deep Technologies, and it is increasingly becoming of high relevance for countries and sectors. Startups and research initiatives are driving technological progress. At the moment, Europe is behind the US and China when it comes to seizing the opportunities of artificial intelligence and automation. Investments in automation technologies and AI are growing rapidly, dominated by digital giants such as Amazon, Baidu, Tencent and Google. As of today, most countries are including AI in their strategic actions plans. In terms of investments, AI investment in Europe summed up around $3 to $4 billion in 2016, compared with $8 to $12 billion in Asia and $15 to $23 billion in North America — according to a global McKinsey market study.

We believe that a business-impulsed initiative, in the form of a « do-tank », can help with Deep Tech related challenges. That’s why we initiated Deep.Circle community in early 2018 with the main goal of support the development of future Deep Tech Champions in Europe.

The Artificial Intelligence Deep.Circle

More than 50 leaders (entrepreneurs, investors, industry leaders, academics, and politics) came from France and Germany to work in groups on six specific questions, related to AI and competitiveness, education and ethics.

In order to foster and promote this collaboration, we organized on June 5th the first edition of the Deep.Circle in Berlin, with the focus on “Taking responsibility for AI in Europe”. More than 50 leaders (entrepreneurs, investors, industry leaders, academics, and politics) came from France and Germany to work in groups on six specific questions, related to competitiveness, education and ethics within AI. The overall mission of the Deep.Circle is to support the development of future Deep Tech Champions and initiatives in Europe.

Out of the working groups, 9 concrete call for action have been highlighted:

1. Data strategy for AI in Europe: The first step should be to define the core pillars of a European AI framework as part of an overall data strategy, leveraging key European values and improving data sharing.
2. Organization of a “COP 21 for AI” in Paris or Berlin in 1st half of 2019 with a strong ethical footprint. Topics such as “green & resource efficient AI”, “industrial data”, and “urban data” should be explored as potential drivers of European AI. Being the objective to ratify the cornerstones of a European AI framework.
3. The creation of a European Linguistic Data Consortium dedicated to AI and leveraging the different languages of Europe as a strength. Today AI developments are frequently limited to English language. The consortium is inspired by the US, where a Linguistic Data Consortium (LDC) was created in 1992, financed by the US Government as an independent and agile structure. The mission of a European LDC for AI should be the creation, collection, and distribution of data for research and development purposes on the different languages in Europe.
4. DeepTech Lab / Augmented schools, that would offer Open Source and Virtual Learning courses. Modular agile learning should emphasize European values and soft skills such as collaborative working, critical thinking, entrepreneurship, social thinking. These structures should work in collaboration with other actors from industry, politics etc.
5. Promote and make accessible DeepTech Bootcamps@Schools. For young children (6–10 years), tech should be an example of diversity. Girls and boys show the same interest for technical topics and coding until age of 10. Coding should be learned as a second language, starting from 6 years old. These Bootcamps, not only focused in coding but in deep technologies, should be boost spreading its reach from schoolkids located in urban areas to the countryside.
6. Launch of a “CERN for AI” initiated by France and Germany, with a clear research- to-market focus, to retain and attract also talents from abroad, and jointly work on the key challenges in AI with close cooperation with European startups and industry.
7. Incentivization of decentralized initiatives led by sectors and/or industry consortiums, i.e. specific arrangements to share data and the creation of data pools / platforms. This can be achieved through the launch of small-scale challenges for specific types of actors. In addition, this will also incentivize data sharing. A first step in the short-term could be the organization of an AI Challenge with a strong participation of FR-DE actors, such as startups, research institutes and corporates.
8. The creation of a European DeepTech LaunchPad with a clear innovation to business focus and inspired by the Airbus A3 innovation hub in The Silicon Valley and the proposed project organization of the J.E.D.I. initiative (Joint European Disruptive Initiative). The Launchpad should focus on AI first and organize challenges around related topics in cooperation with industry as potential users and also potential “exit paths” for startups. Speed to market is key to succeed in a competitive environment. As a result of the discussion it is recommended to “prototype” already in 2018 ambitious challenges to identify the Next Big Thing focusing on AI. First topics for AI challenges have been suggested: How to achieve better AI with limited data? How to turn the European data roadblock into an advantage?
9. The creation of a “European Vision Fund” for DeepTech inspired by SOFTBANK/EBRD. The fund should also set the basis to accompany tech companies along their lifecycle, i.e. from early to late stage financing. It should create the ground for European “exits”. It should be an agile structure, with a professional and autonomous investment committee, which would also be independent from governments. The professional experienced investment team should include business and technical profiles. It should be able to support startups along the whole lifecycle, from seed to later stages and also have industry LPs as potential exit partners. A first stage fund of a minimum of 2–10 billion Euro should be launched between France and Germany, with a special focus on AI. France and Germany should contribute 50%, and the other half should come from Industry LPs, European Investment Fund and other private industry investors.

Collaboration is the new black

There is a clear need to speed up Go-to-market for Europe’s future champions so that they can compete on a global paying field. Promoting our values, adapting our education system and setting the basic toolbox for an attractive Deep Tech ecosystem are three crucial steps in this direction.

All these calls for action are pointing out the need for more collaboration among European countries. If an AI strategy for the whole Europe may be too ambitious to start with, initiating with collaborations between specific countries, can lead the way forward. We believe that France and Germany, with their respective looking forward leaders, Emmanuel Macron and Angela Merkel, can set the pace. Collaboration between different types of actors is the second must-have. Europe has a strong research basis, however, somehow disconnected from the market players.

A first step to set the pace for more collaboration relies on its ability to set a common definition and understanding of Artificial Intelligence, paving the way for aligned European data standards and promoting “innovation to market”. Second priority will be to adapt our educational model to current mutations. These foundations are essential to foster an attractive ecosystem for AI in Europe.

Today countries are leveraging artificial intelligence and in extenso technologies as a soft power tool. Europe has no “data giant” able to rival with Alphabet, Facebook or Tencent so far. There is a clear need to speed up Go-to-market for Europe’s future champions so that they can compete on a global paying field. Promoting our values, adapting our education system and setting the basic toolbox for an attractive Deep Tech ecosystem are three crucial steps in this direction.

June 5th aftermovie
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