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Deep Knowledge Group GP Participates in “AI in the Boardroom” Panel Discussion at ICGN Amsterdam 2020

Dmitry Kaminskiy Discusses How AI is Changing the Nature of Corporate Decision Making and How Data Science is Driving Deep Knowledge Group’s Long-Term Strategic Vision
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Tuesday, February 12th, 2020, Amsterdam: Deep Knowledge Group General Partner Dmitry Kaminskiy participated in a February 2020 panel discussion, titled “Robots in the Boardroom: will artificial intelligence lead to more board effectiveness”, alongside alongside Marcel Prins (COO, APG Asset Management) and Jaap Winter (Partner, Phyleon Governance & Leadership and Professor of International Company Law at the University of Amsterdam), at ICGN Amsterdam 2020.


The panel discussion, chaired by Dr. Andreas G. F. Hoepner, Professor of Operational Risk, Banking & Finance at the Michael Smurfit Graduate Business School and the Lochlann Quinn School of Business of University College Dublin (UCD), focused on several main topics, including:

  • How AI is funding increasingly prominent use in the activities of corporate strategic decision making

  • The potential for AI to not only support directors and executives, but actually replace them

  • Whether the boards of public companies are actually ready in practice for these changes, and how they can be better prepared for the inevitable future of corporate governance utilizing AI

  • How these developments affect interactions between the boards and the investors of publicly-traded companies

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During the discussion, Kaminskiy focused upon how AI will acquire an increasingly fundamental role in corporate decision making, as well as some of the specific conclusions that he came to realize from his experiences in 2014, when Deep Knowledge Ventures decided to incorporate AI into its investment strategy in a very fundamental way, by designing and implementing an AI system built to identify prospective investment targets and semi-automate due diligence processes.


Ultimately, he summarized the positive and negative realizations that came out of that experiment, discussed how it gave the fund (and its parent company, the international consortium Deep Knowledge Group) a fundamental understanding of what AI is and is not capable of, and forced the firm to develop progressive approaches for InvestTech that it still uses to this day. Kaminskiy also summarized how, in the longer-term, the fund’s 2014 experiment with AI had a deep and systemic impact upon the long-term vision and mission of Deep Knowledge Group by giving it the foundational tools, skillsets and understanding necessary to focus on progressive DeepTech and Frontier Technology sectors like AI in Healthcare, Preventive Medicine, precision Health and Longevity.  


Major KeyPoints from Kaminskiy’s Panel Discussion Contributions

  • First of all, when Deep Knowledge Ventures decided to utilize AI as the fundamental driver of its investment strategy, it was an “Act of Faith.”

  • At that time very few people in the investment community knew at all what “artificial intelligence” means in practice.

  • In reality, the decision reflected a dedication and full commitment to develop a data driven investment strategy based on objective facts and logic, unbiased, and entirely separate from human emotions

  • We gathered a significant team of around 50 data scientist, machine learners, advanced IT-specialists and created a Big Data analytical system empowered by machine learning techniques, named Validating Investment Tool for Advancing Life Sciences – VITAL

  • The idea was to create automated system for data aggregation, due diligence processes, and ab alternative methodology for assessment of our investment strategy for early stage seed round investments

  •  By the technological criteria of those times the system was quite capable, particularly in data aggregation and by some other specific parameters

  • But eventually the further development of the system led us to several quite surprising insights:

    • 90% of startups are failing, which is no secret

    • 92% of drug candidates are failing in clinical trials, which is also well known

    • However, the system in 99% of cases showed a negative prognosis

    • That is explainable by the fact there are 10 times more data about failed startups than successful startups

    • Therefore, such systems can be much more capably applied for risk assessment, and may be applied, for example, to develop shorting strategies for hedge funds

  • The major conclusion that came from the development of this system was very different - the success of Venture funds within BioTech sector has almost nothing to do with its capacity to identify promising startups or to make intelligent due diligence, but mostly with the capabilities of a select number of venture funds to lobby and artificially accelerate exits and liquidity events

  • The same, by the way, can be said of most other sectors. In general you can consider that much of the Silicon Valley investment space is driven by HypeTech – i.e., by Hype. Whereas the major secret of successful venture funds is based on capabilities to create that Hype, overvalue startups and then to sell them to acquirers (i.e., to big corporations).

  •  However there were also very positive outcomes  that resulted from our experiment:

    • This fundamental dedication to Data Science forced us to embrace a cycle of accelerated evolution as a fund, especially in terms of the development and use of data-driven InvestTech solutions in particular

    • We also gained very deep expertise in the AI industry itself and a comprehensive understanding what AI can do and what it cannot

    • We created and gained the core capabilities necessary to operate as a progressive fund specifically focused on so-called DeepTech and Frontier Technologies

    • DeepTech can be considered as operating on the specific frontiers of industries where the success of startups depends purely on science and advanced technologies. and could not be replaced by notorious financial engineering technologies

    • The best known example of DeepTech company is DeepMind acquired by Google, which gave Google a strong technological advantage and helped them to become a leading world corporation in terms of AI strength

  • We identified two sectors of DeepTech on which we decided to focus:

    • AI for Drug Discovery and Advanced R&D in Healthcare

    • Longevity, in sense of applying DeepTech technologies for Preventive Precision Medicine and the extension of health period of life

    • In these two sectors we now have world-leading expertise through the activities of two of our analytical subsidiaries – one named Deep Knowledge Analytics for AI in Pharma and Drug Discovery, and the second named Aging Analytics Agency for Longevity, Precision Medicine and Economics of Aging Population

    • These two analytical departments in particular give us the foundation and capacity for stating that we do indeed live up to the name of our fund – Deep Knowledge Ventures

  • And on the matter of InvestTech techniques in particular, we developed an absolutely novel approach on how to structure a new type of fund, the so-called Venture Index Hedge Fund for DeepTech sectors. In actuality it is a hybrid technology which combines features of venture, hedge and index funds, where we are investing as venture fund, but making bets not a promising individual companies but on entire industries and, at the same time, not locking up the money of our LPs for 3-5 years (a very typical timeline for Venture Funds), but rather providing them with a liquidity mechanism, typical for case of hedge funds.

    • In Q2 2019 we are launching an AI in Drug Discovery Index Fund, and in Q3 Longevity.Capital investment fund.


About Deep Knowledge Group
Deep Knowledge Group is an international consortium of commercial and non-profit organizations focused on the synergetic convergence of DeepTech and Frontier Technologies (AI, Longevity, MedTech, FinTech, GovTech), applying progressive data-driven Invest-Tech solutions with a long-term strategic focus on AI in Healthcare, Longevity and Precision Health, and aiming to achieve positive impact through the support of progressive technologies for the benefit of humanity via scientific research, investment, entrepreneurship, analytics and philanthropy.


About Longevity.Capital
Longevity.Capital is a hybrid investment fund specifically focused on the Longevity Industry, backed by seasoned professionals who have been active in both the investment banking and Longevity industries for 25+ years, long before the sector was recognized as a serious prospect by the overwhelming majority of investors. The fund employs advanced InvestTech solutions for investment de-risking, including portfolio diversification across the full scope of the Longevity industry (biomedicine, finance, tech), and formulates its investment strategy based on sophisticated industry intelligence and comparative analytics provided by the world-leading Longevity Analytics entity Aging Analytics Agency, which uses hundreds of quantitative and fact-based parameters to identify prospective investment targets for the fund, utilizing multidimensional analytical frameworks as complex as the industry itself.


About Dmitry Kaminskiy

Dmitry Kaminskiy is Founder of Deep Knowledge Group. He is General Partner of Deep Knowledge Ventures, Founding Partner of Longevity Capital, Founder of Aging Analytics Agency, Founder of Deep Knowledge Analytics, Co-founder of Longevity Bank, Longevity FinTech Company, and Neurotech Analytics. He is author of Longevity Industry 1.0: Defining the Biggest and Most Complex Industry in Human History. He is the Head of International Development of the Secretariat for the UK All-Party Parliamentary Group for Longevity, Managing Trustee of the Biogerontology Research Foundation, and serves on the Advisory Board of the Longevity AI Consortium at King's College London. Dmitry is based in London.

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