In this series of articles, we will cover the definition of Deep Tech, its history, early examples and how it is not only defining the 4th industrial revolution but also changing the way problems are tackled and solutions are conceived in the digital era
Anyone who has been involved or following the development of technology or start-ups in the past few years would instantly notice a term that has become more popular with time: Deep Tech. However, given how broadly it is used, it is now incredibly hard to define as a concept, and even more when it does not refer to any technology.
Open Eyes, Open Minds
When we look at the history of technology, we can see how each big moment of revolution came as a direct response to how the “standards” were defined previously. The first industrial revolution widespread the value of applying technologies like engines to traditional practices, but the knowledge to apply was limited. The second industrial revolution is what is commonly deemed as the first true wave of innovation, thanks to the great advancements in chemistry, telecommunications, electricity, and materials science, to the point where multiple discoveries of this time are still the base of today’s lifestyle after enduring two World Wars (Karl Benz’ first automobile, the Bessemer process for steel production, Faraday’s studies on harnessing electricity, etc.)
The following big point of innovation came after WWII, with corporate laboratories leading the charge and achieving advances in R&D (IBM developing the first mainframe computer), chemistry (companies like Dupont publishing more articles in journals than most universities), and pharma, with the advantage of receiving federal funding in many countries. Finally, the third innovation wave began in the 1980s with the appearance of personal computers and saw the shift in focus from science to application of current technologies instead of the development of new ones, fueled by the rise in success of the Venture Capital model.
However, what was the strength of previous innovation waves is now being considered one of its weaknesses, which is the main paradigm of high R&D spending and reaching one of two outcomes: easy production with high-risk market presence or ensured market presence after a long process of high-risk technology development. This mentality was also widespread due to the focus of the overall research spending in electronics and healthcare, which then captured the market in a sort of feedback loop, as projects in these areas were more successful so more investments were made in them, increasing the gap with other sectors.
What “Deep Tech” as a concept brings to the table is a shift in vision and mentality, one that focuses on tackling a problem with available tools and building over multiple viable iterations instead of spending millions of dollars in development before testing. This not only motivates start-ups and entrepreneurs to find new uses and synergies between existing technologies to solve well-defined issues and necessities, which then allows them to develop over the first solution by either coupling other technologies or improving the least efficient aspects of the current ones.
Clear Goals Pave Ways
Studies have shown how the main reason why start-ups tend to fail is the lack of market need or presence, meaning that there is not enough interest on the developed product to make it commercially viable. By focusing directly on the problem, deep tech ventures and start-ups tackle the issue of market presence from the beginning, giving them more time and resources to focus on efficiency, economic viability, and marketing dynamics to increase reach.
This focus on problem-solving is the basis of the “DBTL cycle” (Design, Build, Test and Learn) on top of which every deep tech project is built. The cyclical nature of the process encourages start-ups to constantly look for ways to improve their proposal, which also keeps their solution relevant within the market due constant upgrades and updates that not only make the project more efficient but could also broadening the original scope of the start-up.
The principle of Deep Tech could also be defining by breaking down the innovation process into 4 stages or “moments”:
- The Copernicus Moment on how to frame the paradigm, i.e., what is the problem, and could reality be different?
- The Newton Moment on forging the theory, i.e., how can we make this possible?
- The Armstrong Moment on taking the first step, i.e., can we build it today?
- The Asimov Moment on shifting reality, i.e., what does it take to become the new normal?
As an example, we can take a look at fusion energy. The concept of nuclear fusion could theoretically lead us to a clean and totally renewable energy source, and this motivated a consortium of 35 countries to join forces in 2006 and come up with a $20 billion project to achieve the goal of building the biggest functional Tokamak reactor, the ITER, by 2035. However, a Boston start-up called Commonwealth Fusion Systems (CFS) founded in 2018 has raised only $215 million, less than 2% of the ITER project, and now has plans to build a net-gain reactor by 2025.
With a start-up having a feasible plan to achieve the same goal as a consortium between 35 countries, with a very small fraction of the funding and nearly a quarter of the time (8 years vs 30 years), one can easily note the advantages of the deep tech approach in sectors of all kinds, and other energy-based start-ups in a lesser scale, like those focused on taking advantage of thorium, are proof of the scalability and range of the philosophy.
Year by year we have seen how this line of thought has become more popular, and we will continue to see this model grow and improve on itself as deep tech start-ups keep increasing in viability and market presence, like what happened with Tesla and SpaceX, or as new problems are solved by using combinations of technologies, like most blockchain-based projects in recent times. Overall, it would seem like deep tech is the map to be followed by the projects that have the potential to shape our future, so understanding how it works is the best strategy to prepare for a revolution that could already be going strong, and in the next part of this series we will cover the economic impact these projects have had in the innovation landscape in terms of number of projects that have been successfully funded, the amount of funds raised and how they compare to similar projects with non-deep tech strategies.
Article written by Gabriel Zanko, Tech Advisor, CEO of MobileyourLife (Investment Banking for Deep Technology and Renewable Energy), CEO of Urano Capital ( the future Seed Fund for Deep Technology), researcher and speaker.
Daniel Ramos, Gabriel Zanko, Mobileyourlife – Bogotá, D.C., Colombia
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