The post-Corona Business Model: Machine Learning with tokenized Big Data

After the lockdown of physical businesses, most of those will not reopen due to losses incurred during the lockdown itself. That means that the new so-called “Coronapreneurs” will have to use real-time opportunities to capture “momentary markets”, thus requiring businesses to update customer analytics and advertising. In particular, businesses will need to adapt to a transition from social, mobile, analytics and cloud (SMAC) to Distributed ledger technology (such as blockchain), Artificial intelligence (AI), Extended reality (including virtual and augmented reality), and Quantum computing (DARQ). Personal profiling of consumers by analyzing their social profiles, where they check-in and what products they tag among other parameters will change marketing for these new businesses, which will thrive only if the owners invest to reskill the Next-gen workforce, which is to be trained in 2020 tech trends.

This new type of business model, based on the tech disruption trends, is not anymore based on the classical Lean Canvas view, but rather on a Machine Learning Canvas strategy, and exploits artificial intelligence systems, which, in accordance with the local and international regulations, are even able to incorporate both the neural networks used in deep learning and pre-set symbolic systems, thus creating predictive models that can be easily understood by the employees. These particular hybrid systems are called “deep intelligence”, a name recalling the integration of the technologies just mentioned, and are fuelled by Big Data.

Especially due to the fact that the information acquired about the users is sensitive, deep intelligence, where this information acts as a major input, requires that blockchain is also used, to ensure a secure data recording method and a particularly robust and interoperable data sharing infrastructure, flexible enough to allow instant access to what the machine learning needs to predict the market. At the same time, the blockchain guarantees protection against unauthorized access or intrusion attempts, defining a priori, albeit with the possibility of almost instant modification, a structured system with different authorization levels for the various ecosystem actors, human and machine-like.

To exploit deep intelligence at the maximum of its capabilities, it is essential to process information from different systems and beyond institutional and geo-political borders, carrying out a complete analysis of the users’ data even if under lockdown. The blockchain manages to simplify large-scale processing of data by businesses, working with a wide variety of data formats, custom specifications and ambiguous semantics, furthermore providing AI algorithms and big data technologies standardized inputs and in such a way ensuring the interoperability.

Data is indeed the oil of the new economy. In the context of any given digital application, data is where the value resides: for the companies that are paid to host it; for the platforms that are able to sell advertising against it; and for the users who effectively trade their data for reduced priced services. Data is, in other words, an asset. Like other assets, it can be tokenized and decentralized into a public blockchain. It’s not hard to imagine a future where every meaningful piece of data in the world will be represented by a private key.

Tying tokens to data explicitly creates a world of new options to reconfigure how data can be acquired and used, safely, to educate machine learning predictive systems. Thanks to tokenization, it is nowadays possible to think of a cryptocurrency whose value is based on the request and offer of the traffic of the data generated and collected. In such an ecosystem, data collection supports the currency itself, because the ones who want to buy it are obligated to pay with the coins purchased on the market, growing the trading volume, thus favoring the same owner of the coins.

The market has a very high demand for data: the expectation for the 2020 total value of Big Data exchanged, in the global market, is around 465 billion dollars. Daniele Marinelli, the Italian entrepreneur who has first pioneered in 2015 the sharing business model, is now making this tokenization model of data-driven value sharing an established reality in the new economy, presenting his DTCoin project not only as an innovation but, most importantly, as a real-life aid to the businesses in the post-Corona era, so that they can start building a Machine Learning Canvas without having to worry about where to get data and how to treat it securely.

Not to forget, in fact, is that ever since the European Union’s GDPR laid the foundation for data privacy regulations, all businesses, including new ones, will need to adapt their analytics to similar guidelines in 2020 to protect user information.

By Eloisa Marchesoni is best known as the youngest consultant in the Blockchain and A.I. sector, as well as influential author of articles for the major national and international sector newspapers, in the process of publishing the book “Tokenization processes and new economic paradigms” for Maggioli Editore.

Eloisa is today Token Model Architect n. 1 in Europe, part of the Top 100 Leaders and Influencers of Italy in FinTech and also listed among the World’s Top 50 High Paid Innovation Speakers, acknowledgments that confirm her thriving business as a consultant.

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