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  • Writer's pictureDeep Knowledge Group

Deep Knowledge Group Defines ‘DeepTech’ and Publishes First-Ever Industry-Wide Framework

Definitive DeepTech Industry Framework and Big Data Analytics System Released by Pioneer of DeepTech Analytics

Deep Knowledge Group (DKG), a data-driven consortium of commercial and nonprofit organizations active on many fronts in the realm of DeepTech and Frontier Technologies, which has for the past decade defined numerous terms and concepts across DeepTech and was among the first to track and document the rapid emergence of many of its advanced technology sectors, has published its long-awaited DeepTech Ecosystem Framework and corresponding DeepTech Big Data Analytical System and Dashboard, constituting the culmination of more than a decade of work at the frontier of high-complexity DeepTech data science and advanced comparative analytics.


View DeepTech Industry Framework here: www.deep-innovation.tech/deeptech-framework


View DeepTech Dashboard here: www.deep-innovation.tech/deeptech-dashboard


Having been committed since 2014 to the corporate thesis of DeepTech for social impact, techno-ethical business for social good, and the continual reinvestment of profits into the expansion of our core Data Science, AI, and analytics assets and the refinement of our financial-ecosystemic development projects (which we see as the major tool driving our Group’s further growth as a Data Science driven financial corporation with focus on Longevity and DeepTech), we have known for a very long time that the path toward providing the first-ever comprehensive definition of DeepTech and effective framework for use in intelligent industry monitoring, forecasting, benchmarking, and decision-making would be long and difficult.


The ultimate publication of our long-awaited DeepTech Ecosystem Framework and corresponding DeepTech Big Data Analytical System and Dashboard, undertaken by our dedicated Data Science Division, has required the finalization of dozens of component sector and advanced technology-specific frameworks that are individually themselves of unprecedented complexity.


Fortunately, however, and from a very early stage after our founding, we consider ourselves among a small vanguard of organizations whose mission and vision is truly defined by its Data Science and technological forecasting experts, rather than the other way around. We do not simply use data analytics to support our goals; we use it to define and drive them. In a sense, you can consider that DKG's Board of Directors reports to its data, analytics, and science/technology forecasting specialists, and not the other way around. Internally stylizing itself as the “DeepMind of DeepTech,” the Group considers its Data Science Assets as its most valuable resource, and this year has seen a large number of its long-term projects (including many technology, sector and region-specific Big Data Analytical Dashboards) come to fruition within this domain.

Big Data Analytical Dashboards Developed by DKG Data Science Division


The final fruition of all these advanced DeepTech frameworks and dashboards, marks the beginning of a transition from preparation to practical implementation. From a decade-long period of analysis landscaping, trend monitoring, analytics benchmarking, forecasting, and understanding to the tangible development of the ecosystemic infrastructure required for the Financial Commoditization of DeepTech Industrialization, and its emergence as a fundamentally new asset class.


This practical development begins this year. 2023 is the year when many of the first bricks in the road are laid. Our target milestones for 2023-2024 include many of the entities mentioned in the framework, including the Longevity Industry Index, the Longevity Stock Exchange, the Longevity Investment Bank, the Long-Term Technological Forecasting System, and, of course, a subsequent version of the Big Data Analytical System (which is be updated constantly). Besides these financial and commercial activities, we will also see the beginning of two ongoing DeepTech for Social Good projects: the 5th Industrial Revolution Institute, and the Techno-Philanthropy as a New Paradigm for Global Philanthropy Ecosystem.


Defining DeepTech: The First Comprehensive Basis For DeepTech Industry Analytics, Monitoring, Forecasting, and Benchmarking


Deep Knowledge Group and its subsidiaries have, over the past 10 years, created an intricate set of analytical frameworks comprehensive enough to define and forecast the deepest and most sophisticated industries and the disruptive technologies that drive them.


A technology that affects an industry or market's most basic operations is known as a disruptive technology. This means it displaces a well-established product by creating a new industry or market. Deep Knowledge Group has developed the most practical means of optimizing and coordinating the continued advancement of disruptive technologies and recommends the best methods for its careful, de-risked, and socially responsible delivery to the whole of humanity.


And DeepTech, a term for technologies that accelerate the development of other sectors – ranging from Artificial Intelligence (AI), robotics, and blockchain to advanced material science, photonics, electronics, BioTech, and quantum computing – is by definition the most disruptive technology sector of all. Indeed, the ‘Deep’ in DeepTech is one of the central pillars of our decision to name our consortium Deep Knowledge Group in the first place, and its general principle and nature can be seen throughout almost all of our activities.


In order to effectively execute analytics, forecasting, benchmarking, monitoring and strategic decision making in the face of DeepTech’s inherent mega-complexity, technological intersectionality and multidimensionality, Deep Knowledge Group has developed an Industry Classification Framework (ICF) for DeepTech, which makes it possible to compare DeepTech entities internationally and focuses on the technological aspect of each company's business activity.

The classification system assigns each company to its industry according to the source of its revenue. For example, a company developing a digital platform will be classified according to the way it makes money, e.g., providing paid remote medical consultations, collecting subscriptions for access to educational courses, or acting as a broker in ride sharing activities. In this, we focus not on the platform itself (a website or mobile application) but on the main sources of the company's revenue.


Disruptive DeepTech Identification Process

As a primary driver of technological progress and the most efficient engine for the social good, DeepTech is a common theme throughout DKG’s analytics, investment, financial industry activity and philanthropic portfolios, and DeepTech financial commoditization – building ecosystemic infrastructure for DeepTech’s accelerated development – is a central piston, if not the core driving engine, of our overarching strategic agenda.


To this end, we used the SWOT (strengths, weaknesses, opportunities, and threats) analysis parameters to help assess the internal factors that might affect the DeepTech Industry as a whole, specifically focusing on its strengths and weaknesses, as well as external factors such as its opportunities and threats. The SWOT parameters also characterize any form of segmentation and classification in the multidimensionality of the industry.


These SWOT parameters form the basis of Deep Knowledge Group’s Big Data analytical dashboards, developed over a decade of deep systemic analytics, and include the following products of Deep Knowledge Group’s dashboard suite:


A Decade of World-Leading Global Analytics


These dashboards are only the latest culmination of Deep Knowledge Group’s work in DeepTech analytics, and 2022 alone witnessed the culmination and launch of a wide range of component projects which paved the way for the unveiling of our new DeepTech Ecosystem Framework and corresponding DeepTech Big Data Analytical System and Dashboard.


From a substantial expansion of our workforce across analytics, Data Science, finance, media, business development, philanthropy, and executive management to the continued strengthening of our UK, Switzerland, and other European branches and the expansion of our new branch in the UAE, 2022 has been a year of unquestionable growth, consolidation, refinement, and development for DKG. The year has placed us in an excellent position to put our expanding ambitions into practice and efficiently implement our strategic agenda for 2023 and beyond.


The multitudinous component analytics necessary to formulate our DeepTech framework were developed over many years in order to gain both the deep industry understanding and tangible, practical tools for industry analysis, monitoring, forecasting and benchmarking needed in order to effectively and productively build the core investment and financial industry ecosystemic infrastructure required for DeepTech Financial Commoditization: the platforms, indices, exchanges, financial instruments, and derivatives necessary for massively accelerating the rate of DeepTech Industry development, maturation and stabilization (and ultimately, the delivery of their primary benefits for consumers, citizens and national economies) – a goal that has been a major objective of DKG over the past 5 years.


The definitive and decisive long-term goal of DKG is to foster and accelerate the tangible, market-ready maturation of DeepTech Industrialization as the primary driver of social impact in the 21st century and as the fundamental engine of the 5th Industrial Revolution. It is the only ROI we will settle for in our mission to develop, deploy, and accelerate the advancement of DeepTech for the good of global society.


It is with this mission in mind that DKG decided in 2022 to establish DeepTech and Longevity Industry Financial Advisors to act as the practical vehicle for the development of legal, financial, and ecosystemic frameworks and instruments to support the accelerated development of DeepTech and the establishment of an integrated financial infrastructure for the further growth and stabilization of these frameworks in order to expedite the emergence of DeepTech as a new asset class in itself.

We look forward to sharing the continued fruits of these developments throughout the coming year. We also look forward to sharing our classification frameworks, which we made and shared in the hope of providing a stronger basis for the stabilization, maturation, and growth of the DeepTech Industry and to help other stakeholders unleash its full potential.


But first, let’s take a look at the framework structure.


DeepTech Industry Classification Framework At a Glance


The following principles form the basis for selecting companies for the DeepTech Industry Classification Framework.


Framework Structure


The framework has three layers with increasing levels of specification: supersectors, sectors, and industries. While industries are mostly classified at the discretion of the Data Science Division of DKG, the supersector and sector structure we use is similar to the national industry taxonomy for the purpose of standardization.

Allocation of Companies to Industries


In the ICF, a company is allocated to the industry that most closely matches the source of all or most of its revenue or, in the case of a young company, the source of its planned revenue. We primarily use the audited financial statements or directors’ reports of a company in order to classify it. If the annual report is not available, we use the description provided in the company’s listing prospectus. If neither of these is available, we use the business description provided on the company’s website.


Distribution of Companies by Industry Sector

An illustration of the applied framework from the “InvestTech Market Solutions DeepTech Market Overview 2022”


A corporation that operates in two or more industries is assigned to the industry that generates the highest proportion of its revenue according to the company’s most recent report and accounts.


Investment holding firms are not included in the ICF.


DKG works to keep the classification of companies stable by ignoring what it sees as brief changes in the operations of particular enterprises.


In unusual cases, the classification may take into account other characteristics if DKG believes that neglecting them could lead to a classification that is inaccurate.


Classification and Processing Methods


For automatic classification of companies, DKG is using neural text classification, a subfield of natural language processing. We use a pretrained model SciBERT, a language model for scientific text. This model is pretrained on 1.14 million papers taken from Semantic Scholar and implemented in the Python programming language (Transformer library). We further trained this model on the preliminary classified dataset of companies mapped to corresponding industries, using companies' descriptions from Crunchbase, websites, or other sources available as inputs. A trained model is able to automatically classify a large set of companies and dynamically track the evolution of each DeepTech industry in time.


Structure of Sectors


When creating industry classifications, we can’t avoid the existing industry taxonomies developed by the national and international statistical agencies. Some international classifications include the Bloomberg Industry Classification Standard (BICS), the Global Industry Classification Standard by MSCI (GICS), and the Industry Classification Benchmark by FTSE Russell (ICB). Among national classifications, we distinguish the Statistical Classification of Economic Activities in the European Community (NACE), the North American Industry Classification System (NAICS), and the United Kingdom Standard Industrial Classification of Economic Activities (UKSIC).


In our framework, we use elements from both classification groups and adapt them to provide a broad overview of technological development in each market sector and their potential to disrupt the classical business models.


Since technological development is the main focus of all companies in the framework, we don’t distinguish a separate technology sector but instead classify the companies according to the markets they serve. Our general classification structure of the sectors is similar to the national classification for the following reason: For a company that aims to disrupt the business model, the model itself is more relevant than its final market. For example, a company that revolutionizes the manufacturing process and a company that applies cutting-edge technologies for fast and cheap delivery – although they may both work with the same group of projects – do very different types of business and should be classified accordingly.


SWOT Parameters

To deliver maximum value to the final user, it is important to provide a clear understanding not only of the existing industry but also the position a company holds inside that industry. For this reason, we at DKG have developed quantitative, multidimensional, and multilayered SWOTs – indexes of hundreds of precisely structured metrics and parameters grouped into specific categories, able to measure the efficiency and forecast the perspective of each company.


Two large groups can be distinguished among the factors considered: general factors and industry-specific factors. While general factors cover such company features as governance quality, the scientific and engineering background of the team, financial position, marketing strategy, etc., the industry-specific parameters relate to the efficiency metric for a particular business.

Both metric categories and metrics are assigned weights, or importance factors, in proportion to their perceived impact in determining the strength of a given company’s activities and prospects, tuned to the specifics of the general domain in which they operate.


Naturally, metrics that directly relate to the DeepTech-specific activities of a certain entity are given the greatest importance factors, which are cumulatively integrated to form a classification system capable of benchmarking the DeepTech-related activities and prospects of DeepTech institutions globally.


Formation of Industries


Deep Knowledge Group classifies industries by looking at the real companies operating on the market. Typically, we require at least five companies to work on the same kind of technology to consider it an industry fit for our framework. However, in exceptional cases, DKG may allow industries containing less than five companies or even a single company. This mainly relates to cases in which a company or companies can be said to have founded a new prospective industry. This allowance is made in order to capture the quickly changing nature of the technological landscape and act early on this base.


Tech/DeepTech Industry Scope and Landscape


In this framework, we introduce the dichotomy between “Tech” and “DeepTech” industries on the basis of the technologies the companies develop or use. To make this difference clear, we provide the definitions and a few examples of these two groups.


DeepTech industries are the industries that are the main beneficiaries of microprocessor computational power growth, which makes the collection and processing of Big Data feasible and allows for the training of complex self-learning algorithms and the application of them to a wide range of problems. These technologies often involve the use of fields such as Artificial Intelligence, Machine Learning, biotechnology, and nanotechnology. DeepTech industries focus on solving complex problems and developing innovative solutions with the potential for a significant impact on society and industry, revolutionizing the way the economy functions today. The intensive application of AI to autonomous systems, cybersecurity, and natural language processing constitute only a small portion of this rapidly growing group of industries.


Tech industries, on the other hand, are the industries whose business is closely connected to the most advanced technologies but cannot be allocated to the DeepTech sector. Examples include advanced materials and state-of-the-art machinery production. The Tech industries group is huge and encompasses a wide range of technology-related products and services. These include companies that manufacture hardware, such as smartphones and computers; software companies that develop applications and operating systems; and companies that provide technology services such as website design and development, cloud computing, and cybersecurity.


The scale and landscape of the Tech and DeepTech industries can be very different as these sectors cover a wide range of products, services, and technologies.


The Tech industries group is constantly evolving and includes companies of all sizes, from small start-ups to large multinational corporations. Tech companies can operate in a variety of industries, including information technology, communications, and consumer electronics.


The DeepTech industries group is also diverse and includes companies that focus on developing technologies that are based on advanced scientific and technological principles. Like the Tech industries, the DeepTech industries include companies of all sizes and are constantly evolving.


Tech and DeepTech companies are often located in urban areas with a strong technology presence, such as Silicon Valley in the United States or the Shenzhen–Hong Kong–Guangzhou region in China. These areas tend to have a high concentration of Tech and DeepTech companies, as well as a skilled workforce and infrastructure to support technological innovation.


As technologies are becoming more essential for business operations, the boundaries that defined the limits of opportunity in the past are dissolving and becoming irrelevant. For this reason, Tech and DeepTech companies can be found in many other places around the world as these industries are global in nature. More insights on this topic are provided in a recent article in Gulf News by Deep Knowledge Group General Partner Dmitry Kaminskiy titled “Concept of Silicon Valley is no longer tied to any geography.”


The Importance of Artificial Intelligence


The use of AI in manufacturing, agriculture, healthcare, transport, and energy is being highlighted specifically among DeepTech companies. Many countries are directing their policies toward encouraging the use of AI in public services.


AI is a key component of DeepTech and often underpins the technologies developed by DeepTech companies. AI refers to the ability of computer systems to perform tasks that normally require human intelligence, such as learning, problem-solving, and decision-making. It has the potential to transform many different industries and sectors, and DeepTech companies are at the forefront of this transformation. The DeepTech industry is often closely related to AI development, and many DeepTech companies are actively developing AI-based technologies.

An illustration of the applied framework. Our region-based distribution of the DeepTech companies (below) identifies the innovative geographical clusters with significant growth potential. The results may serve as the basis for strategic expansion in new markets or for a proper assessment of the competitive environment.


Number of Established Companies by Region

An illustration of the applied framework. North America is firmly in the lead regarding the number of DeepTech-focused companies, with Asia and Oceania coming in at second place and Europe following closely behind. We expect the number of Asia-based companies to continue to grow, with an increasing number of public offerings among them.


Cumulative Funding of DeepTech Supersectors, Billion US$

An illustration of the applied framework. The total funding in DeepTech to date reached $1.83 trillion by the end of 2022. The highest amount of funding interest is found in ICT/IT, transportation, and advanced manufacturing, together constituting more than $1 trillion in funding.


All of these fluctuations on a large scale support the need for a consistent and comprehensive framework that can adapt to fast-changing statistics. Curating and presenting relevant data is also essential to minimizing noise and retaining a competitive edge in investment analytics and Big Data.


Safeguarding the Social Dividends of DeepTech and Accelerating DeepTech Financial Commoditization and Industrialization


Having provided a detailed summary of our approach to DeepTech Industry analysis, we have only scratched the surface of our in-depth analytical framework of this fascinating industry and its ever-multiplying challenges and opportunities.


Nonetheless, we could not be more excited about finally sharing all these glimpses of our analytical framework with the world. We want to stress again that we made this framework to ensure the stabilization, continued growth, and maturation of DeepTech and to cement the DeepTech sector’s role as the foundational stepping stone toward the 5th Industrial Revolution.


Progressive investors and financial professionals are taking advantage of DeepTech products and services, but their full potential for the delivery of benefits for citizens, societies, and national economies alike lies in the industrialization and financial commoditization of DeepTech.


This vision of the near future is rooted in the notion of technocracy and the recognition that technological progress is the decisive factor behind the stability, sustainability, and overall growth potential of national economies, as well as the primary driver of quality of life and the most efficient tool for nations to realize opportunities, neutralize challenges, and execute nearly all national strategic priorities at the intersection of population health, access to technology, geopolitical stability, education, and the economy.


As this growth and stabilization continues and DeepTech’s complexity keeps multiplying, so do our analytics. They must be constantly enhanced and upgraded by our increasingly ambitious and expanding Data Science Division, so this will not be the last publication (or final edition) of our DeepTech Ecosystem Framework, nor the last enhancement of addition to the full scope of functionality seen in its corresponding DeepTech Big Data Analytical System and Dashboard.


Deep Knowledge Group will continue to develop and deploy reliably sophisticated and multidimensional Big Data analytics and AI-driven technological forecasting and benchmarking of DeepTech, Longevity, and related industries, laying the foundation for defining, analyzing, and understanding the coming DeepTech Revolution.


However, more than this, Deep Knowledge Group also remains decisively committed to establishing the core investment and financial industry infrastructure needed to execute Longevity Financial Commoditization. DKG's innovations to develop the technological, financial, and ecosystemic frameworks and novel instruments to accelerate the development of DeepTech Industrialization and Financial Commoditization complement the establishment of an integral financial infrastructure system for the further growth, stabilization, and commodification of DeepTech.


The pursuit of this truly ecosystemic approach, and the integral fusion of sophisticated analytics with investment, internal entrepreneurship, and financial industry activities to stabilize, optimize, and accelerate DeepTech and Longevity industry development, is the foundation and basis for DKG’s commitment to ensuring that all necessary components of the 5th Industrial Revolution (5IR) are in place before the year 2030, and its mission to do as much as possible to personally and practically pave the way for its emergence.


Indeed, fostering and accelerating the tangible, market-ready maturation of Longevity and DeepTech Industrialization as the primary drivers for 21st-century social impact and as the fundamental engines of the 5th Industrial Revolution is the definitive and decisive long-term goal of Deep Knowledge Group and the only ROI it will settle for in its mission to support, develop, deploy, and accelerate the advancement and emergence of DeepTech for the good of global society.


One of the earliest practical applications of this long-standing and deep-rooted vision, initiated with and built upon the foundation of our newly-launched DeepTech Industry Framework, was the 2022 launch of a new social enterprise, 5th Industrial Revolution Institute, which will conduct sophisticated long-term technology forecasting and help ensure stable 5IR technology development via AI-driven SWOT analyses to identify and neutralize risk factors. The institute will embody and carry forward DKG’s characteristically ecosystemic approach, utilizing the integral fusion of sophisticated analytics with investment, internal entrepreneurship, and financial industry activities to stabilize, optimize, and accelerate DeepTech and Longevity industry, technology, and infrastructure development, and safeguard the foundational basis for the 5th Industrial Revolution. Keep a keen eye out for news, practical developments, and the first fruits of this highly strategic project in 2023.


As always, DKG remains open to dialogue, partnership proposals, and other forms of collaboration and cooperation on DeepTech topics with like-minded individuals and organizations across finance, investment, technology, science, governance, policy, and philanthropy, and is keen to engage with and support other individuals and organizations as dedicated to safeguarding the acceleration and stabilization of DeepTech Industrialization as we are.


If you have something that you think might be of interest to us, let us know via our contact form or at info@dkv.global

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