Digitalization maturity.

Meta Asset Industry

Overall digitalization maturity classification: low.

  • Industrial Metaverse Algorithm Market
    Digital maturity categorization: low-to-medium

  • Cryptographic Smart Digital Asset Market
    Digital maturity categorization: nascent-to-low

  • Digital Intellectual Property Market
    Digital maturity categorization: low-to-medium

  1. Industrial Metaverse Algorithm Market

  • Currently there exists numerous analytics, simulation, and modeling platforms and software ranging from point-solutions to advanced enterprise platform-based deployments for asset management - all with underlying algorithms to model aspects of real-world performance for various use cases. Creation of high-fidelity algorithms exist across many industrial domains for a variety of purposes - algorithm creation is not the bottleneck. However, the Industrial Metaverse arises from the interaction of algorithms, the output of one powering the input of another (as an example), in the context of closed-loop feedback-reactive networks. Currently, creation of algorithms are siloed by entity, company, platform, software in locked-ecosystems - in the future, democratization of algorithms (approaches such as AutoML, low-code, and others) will re-shape the need for data scientists and engineers to create algorithms.

  • Today, sharing of algorithms or models outside of organizations, platforms, or software is extremely limited. A high-degree of algorithm lock-in exists for reasons around sources of competitive advantage, IP protection, monetization, and lack of common facilitated exchanges to facilitate the transference of algorithms from one entity-to-another. Furthermore, even if one were to hypothetically offer algorithms for sale or purchase to 3rd party entities, controls and protections are very limited around maintenance of downstream IP protection and monetization of utilization.

  • Algorithms that may have been designed-and-developed for one particular real-world use case would require tuning or modification in order to be valid even for a highly adjacent real-world use case. This is the nature of most algorithms. To service this need, it is not sufficient in order to only be able to interact with the algorithm's inputs and outputs, but to be able to re-shape the underlying dynamics of the algorithm itself. In order to facilitate this need, the entire algorithm package may need to be made available - providing source codes and underlying models. Currently, the best examples of algorithm interaction are encompassed with API interface exchanges to facilitate interaction with inputs and outputs (and in some cases, monetization of such utilization). Such API monetization business strategies can be revenue generating, revenue preserving, and allow for either tightly controlled usage, or loosely controlled usage. However, the underlying algorithms themselves are never shared. (How to Drive Your API Monetization Strategy With MuleSoft, 2022)

2. Cryptographic Smart Digital Asset Market

  • Cryptographic Assets are synonymous with the following terminology:

    • Non-Fungible Tokens (NFTs) or Deeds

    • Distinguishable Asset

    • Smart Contracts & Smart Contract Code

    • Decentralized Applications (DApps)

    • Transactions of Information & Value

    • Asset Ownership with Historical Provenance

    • Storage of Value

    • Cryptocurrency & Fiat Value

    • Cryptographic Security

    • Immutability & Tamper Proof

    • Perpetual Commissions or Fees per Exchange

    • Retention of Information Asset Value (adjacent to IP, trademark value, etc.)

    Currently, cryptographic assets or NFTs are governed by the ERC-721 Non-Fungible Token Standard. It represents a standard interface for NFTs, also known as “Deeds” in the standard. The ERC-721 standard allows for the implementation of a standard API for NFTs within smart contracts - including the basic functionality to track and transfer NFTs; it provides a minimum interface a smart contract must implement to allow unique tokens to be managed, owned, and tracked. NFTs are distinguishable and ownership of each must be tracked individually and atomically.

    Currently, the process of creating a cryptographic asset (NFT) is called “minting” (representing the fees or cost of Ethereum ‘gas’ used to deploy the smart contract on the Ethereum blockchain). Minting a NFT represents a transaction deployable to the underlying blockchain. The ability for an NFT to represent an underlying physical asset, digital asset, as well as negative-value (loans, etc.), create a myriad of opportunity streams. The history of NFTs are inextricably linked to the opening up of transactable mechanisms for the exchange of digital art, i.e. the ability to monetize the intangible. As such, most NFT creation mechanisms are tied to this facet of digital art (with potentially other underlying facets of ownership as materialized by Yuga Labs Bored Ape Yacht Club). The top NFT platforms for the creation and interchange of NFTs include: OpenSea, Rarible, NBA TopShop, Binance, Nifty Gateway, and SuperRare among others.

    Other applications today of NFTs are linked to fractional ownership, decentralized autonomous organizations (DAOs), and further tokenization of intangible assets (i.e. Decentraland).

    As of today, no platforms exist for the packaging and minting of algorithms within the confines of structured smart contract code deployed to an underlying blockchain to confer cryptographic transactive properties. Anyone that wishes to do so would have to undertake unique development of an NFT on an underlying blockchain to do so. (ERC-721 Non-Fungible Token Standard, n.d.), (Rodeck, 2022)

  • Currently, there exists no platforms for the creation of custom NFTs with definable properties to facilitate the interchange of cryptographic assets representing digital twin algorithms, i.e. with platform features: smart contract token generation, transactable functionality, storage, transaction history, UI/UX, and more. Today, there does not exist a marketplace to facilitate the packaging of digital twin algorithms as a NFT.

  • Currently, there exists no precedent in terms of company or platform for minting a digital twin algorithm as an NFT.

3. Digital Intellectual Property Market

  • Information assets or digital assets today, including digital twin algorithms, are protected by the very nature that they are typically locked into an ecosystem (platform, application, tool, point-solution, use case, API, etc.) with some-level of access-based restrictions (login & password, single sign-on (SSO), etc.). The usage of the digital twin algorithm is thereby inextricably tied to the underlying platform protections (including cybersecurity) and platform monetization schemes (SaaS, software license fees, usage-based fees, transactive-based fees, etc.). However, if that information asset or digital asset would find itself out of this locked-in ecosystem, protection of that asset would be limited-at-best - and further copying, transmission, usage, modification cannot be controlled.

  • Monetization of digital assets are usually in relation to access to a broader platform, application, tool, point-solution, use case, API, etc. In this way, monetization is not distilled or attributed to the individual digital twin algorithm-level, but yet to the entire product or service. Monetization pathways include various models for pricing including SaaS, software license fees, usage-based fees, transactive-based fees, etc. The closest proxy to the atomic monetization of digital twin assets envisioned by NFTs is via APIs. For example, the Google Natural Language Processing (NLP) algorithm allows for sentiment analysis, entity analysis, syntactic analysis, and content classification. The interaction to and from the algorithm is managed via API calls, where pricing is determined in units based on the volume of requests, with a tiered freemium-structure for the first volume of requests per month, with a per-request fee after this threshold has been reached.

    However, in many cases, adaptation of the underlying algorithm code is needed in order to suit a particular use case. Not all algorithms can be made to be regularized or standardized in order to support only API-based inputs and outputs. In this case, there is limited precedent of protection of monetization streams and tracking ownership. (All Natural Language API Code Samples, n.d.), (Google Cloud Natural Language API: Pricing and Features Comparison With the NLP Cloud API, 2021)

  • While there exists intellectual property management software packages that provide visibility and management to a full corporate IP portfolio, including trademarks, copyrights, patents, and other intellectual property - it falls short of being a singular platform for all digital assets including algorithms. Such an inventorization of information assets or digital assets within an organization would provide a portfolio view, and be the first step towards the valuation of such assets. (How to Protect Your Digital Assets in 2022, 2021)

Digital maturity categorization: low-to-medium.

Digital maturity categorization: nascent-to-low.

Digital maturity categorization: low.