Over the past few years, the interest in the DeepTech sector (that is, innovative companies engaged in providing solutions based on substantial scientific and engineering developments) has been growing, both by governments and private investors. In 2020, the total volume of venture investment in European startups reached $9 bln, or 24% of total investments. According to the global venture capital firm SOSV, every fifth unicorn is engaged in developing DeepTech technologies. According to a survey by the CB Insights tech market intelligence platform, DeepTech startups signed over 2,200 deals all over the world in 2019, attracting a record $26.6 bln in investment.
In recent years, DeepTech projects have seen a series of milestones. Thus, in 2009, Google and NASA achieved quantum supremacy: they claimed that their processor was able to perform a calculation in three minutes and 40 seconds that would take today’s most advanced computer, Summit by IBM, approximately 10,000 years. The CRISPR-Cas9 genome editing technology won a Nobel Prize in 2020, and Crispr Therapeutics reached a market capitalization of $11 bln. DeepMind made a major scientific advance by finding a solution to the protein folding problem (AlphaFold), while the MuZero program marked a new milestone for self-learning AI (MuZero can master games such as go, chess and Atari games without knowing their rules). OpenAI released GPT-3, a language model that uses deep learning to produce human-like text. These are just a few examples.
Many could consider these examples not representative enough. However, we are currently witnessing the world’s first mRNA vaccine that was created using deep learning. DeepTech is becoming an increasingly remarkable trend and has a profound positive impact on dealing with global social and business tasks.
According to a forecast by ARK Investment, a major fund that makes investments in prospective areas, due to deep learning soon we will see an industry with capitalization exceeding that of the internet and digital solutions taken together, within the next 15–20 years. This will result from deep learning technologies to be engaged in coding activities, and will take solutions for autonomous transport management, research of new medications, advisory models, and interactive programs that involve human language, to a brand new level.
Last year, the sustainable trend for growth slowed down amidst the coronavirus pandemic, which has caused considerable macroeconomic and social changes; rapid advancement was demonstrated by В2С and В2SMB companies that target mass markets rather than by DeepTech startups. Concurrently, it became evident that digital technologies will provide for a new infrastructure in a post-pandemic world, and the role of DeepTech companies will only grow.
Analysts estimate that by 2024 most social and economic processes will shift to digital forms. This will accelerate the growth of DeepTech projects on the basis of gathered and digitized data, with drivers including a demand for a more advanced level of user experience, a greater use of smart devices, increased investments in healthcare, the use of networking and cloud business applications, and a growth of M2M technologies.
Yet, this sector is highly cost-consuming and requires substantial capital expenses as only expensive specialists are able to write complex codes. The technology’s relevance can be proven only through substantial investments, with the cost of a mistake being high even for the venture industry. Online education services are far less expensive, while efforts to launch DeepTech projects and introduce them in the market could cost tens of millions of dollars.
Difficulties arise as regards building a team, which is normally put together at a research institution. Researchers cannot promote their own product; they need marketing and advertising experts in order to achieve business success. But the Russian market is too small for DeepTech projects, while expansion into international markets requires a thorough analysis of their current state as well as assessment of the company’s opportunity for entering them with a limited budget and within a limited time frame.
In Russia, a DeepTech company can be sold at a high price mostly to international strategists as Russian ones chiefly target B2С and B2SMB markets rather than extended life cycle projects. This is always complicated as you have to prove to your customers the technology can become globally successful and your team is capable of scaling it up outside Russia. The other question is how a Russian startup’s team can be integrated into the life of an international strategist. So far, there are few such success stories, but they are there.
By Vladimir Sakovich, CEO, Skolkovo Ventures
Data is taken from Almanac of Deep Technologies, Skolkovo Foundation, 2021