DropDeck’s Three Innovations: Part 1

At the heart of DropDeck lies three primary functions which also serve as the three fundamental innovations that will become the ideal cryptocurrency-based investment platform. For the purpose of this article, we will focus on part one, “Interactive Functionality”.

Part 1: Interactive Functionality

A design that matches the functional needs of the user.

Part 2: Blockchain Marriage to A.I.

Utilizing features of the blockchain that can be integrated with A.I. applications.

Part 3: Blockchain Incentives

Extending the blockchain features to have direct influences to everyday life.


Part 1: Interactive functionality

1. User-Centric Designs

Website interfaces have changed substantially over the last ten years with the replacement of static information that sits there unchanged for ages with no concept of how it is being received by users. That static content has been replaced by dynamic content, which allows content to change with respect to other things that are changing, like a newsfeed. It had been quickly adapted so that user-specific information could be stored in cookies in your browser, reorganized, manipulated, and redisplayed to provide the user-experience with more functionality relevant to the task at hand. This new ability evolved when another way of communicating information, called an API, was being utilized and developed for web applications over time. This API now allowed dynamic content to be functionally dependent on user-input data, like your shopping history, not just from the server or network the website is running from, but from independent websites and independent networks. An example of this is a cryptocurrency exchange being able to connect to many of your cryptocurrency wallets, but your wallet information can safely and securely be displayed on the exchange website. This adaptation of the API is how Amazon capitalized on smarter designs, a smoother interface, and how they are able to offer so many different services on different networks like fulfillment or distribution, a consumer-facing marketplace, web server datacenter management, data storage, and seamlessly integrate them on one consistent platform. This led to one other realization that was directed by user feedback.

2. Relevance

By being able to communicate across networks, integrate data processing between systems without a hitch, having hundreds of millions of customers, and using feedback loops to analyze data, Amazon was able to provide the “Relevant Items” function. This simply worked by aesthetically displaying things like items to one’s current searches, past searches, and includes information from search engines and purchase history. Combining those features with reviews where the users contributed in relatively large quantities, consumer trust has, since the early days, risen dramatically.

Although there may be some deficiencies in the lending and investing platforms, some of them can be sorted out by integrating a user-centric interface with a backbone powered by AI and blockchain technology. Similar to Amazon’s relevance function, DropDeck intends to stack the companies in a more efficient manner that provides the most relevant information with the simplest access with many filters. In addition, the sorting, indexing, and matching of all the available companies and participants allows the behavior-driven scoring of DropDeck’s users to be guided by a rating system that allows its users to trust the overall quality of the potential transaction.

3. Trust Through Ratings… but not so simple!

In the space of fundraising, funders, and backers, a heightened level of trust is absolutely crucial to every move made. However, in some private establishments this would normally be a level of trust that comes with the price tag of their services and is often reassured by a dialogue about proprietary algorithms.

This is why a decentralized rating system, governed by truth (through correct answers receiving the rewards and positive scoring on a score-profile), powered by A.I. applications (to learn which scoring methods are most effective in consequence) would be an extremely powerful platform in the domain of ICOs. The domain of applications outside of ICOs is rather expansive as well, which will be discussed in the future.

3.1. Data Type 1: User-Input

This is information put in by companies and users. For example, a company looking to raise funds may insert quantitative information such as how much money they are looking to raise, budgetary information, timelines, strategies, and other such information. One issue in relying entirely on user-input data is that it can be biased, erroneous, and can be subject to manipulation. The good news is that by putting this sort of information on the blockchain, the inherently decentralized and transparent nature of the blockchain will put strong constraints on the level of bias and manipulation that there could possibly be. Therefore, this ensures at least some level of confidence in the user-input score that can make strong predictions.

3.2. Data Type 2: Passively Ascertained Data

The second data type that can be used to make predictions about user-behavior that can lead to a valuable assessment of trustworthiness is indirect observations of users’ actions. If for example a user with high transactions is shown to pay back every potential debt within the allotted time, it is fair to say that the trustworthiness of that user in terms of repaying debts will be high. If enough behavioral data can be mapped, A.I. algorithms can spot recurring trends and changes in data far more effectively than humans, and so strong predictions can be made using this method as well. The hurdle in this arena is normally considered to be how process-demanding A.I. applications are, but the blockchain’s nature of being able to quickly perform calculations makes it a vital component to solving this issue. When combined with the user-inputted methods, the overall confidence of both data types being used to gauge trustworthiness will be very high, and should only increase in efficiency over time.

3.3. An Introduction to the Blockchain Marriage to A.I.

The ability to adequately collect large data sets and perform calculations on them is an extremely important realization to make the interactive functionality properly user-centric. We have shown that the user interface should be constructed in a way that is conducive to collecting certain types of information that can be relayed back to the user as to respond to his or her needs. This whole feedback process demands a properly constructed design to maximize the effects of using A.I. applications. The consequences to this design is that it will make the user feel confident with the information received while providing them with relevant and useful functionality that corresponds to their individual activities.

It should be apparent that these processes must utilize A.I. applications to make the user interface work, and the most efficient way to maximize the utility of these applications is to integrate them with blockchain technology. In the next article we will explain how DropDeck’s integration of A.I. applications with blockchain technology has very deep consequences to output integrity (making sure information relayed to users is trusted), how the positive feedback loop of user behavior and actions can better their decisions, and how this will be used to construct a concept of credit for cryptocurrencies

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