The research on improving Artificial Intelligence (A.I.) has been ongoing for decades. However, it wasn't until recently that developers were finally able to create smart systems that closely resemble the A.I. capabilities of humans.
The main reason for this breakthrough in technology is advancements in Big Data. Recent developments in Big Data have allowed us the capability to organize a very large amount of information into structured components that can be very quickly processed by computers.
Another technology that has the potential for rapidly advancing and transforming Artificial Intelligence is the Blockchain. While some of the applications that have been developed on Blockchain are nothing more than ledger records of transactions, others are so incredibly smart that they almost appear like AI. Here, we will look more closely at the opportunities for A.I. advancement through the Blockchain protocol.
Supporters of Blockchain believe that it can offer benefits in a large number of industries. The technology has already proved its usefulness in the financial and money exchange markets. The mortgage lending industry can benefit from Blockchain application for loan origination, payment, and trading. Smart contracts allow automated contingencies that will be executed when stakeholders meet their respective obligations of the contract.
Major retail corporations such as Wal-Mart are working with IBM to apply Blockchain in their processes. They aim to improve inventory control and reduce wastage. A Blockchain-based supply chain can help retailers keep track of product batches and maintain a steady supply in stores.
Blockchain can also be useful in the healthcare industry, as it allows patients to create medical history records that are completely secure, yet easily accessible from the Blockchain network. Some even believe that the technology will be used to hold elections in the near future.
Improvements in Artificial Intelligence through Blockchain
Researchers have also looked at ways to utilize Blockchain for improving Artificial Intelligence. Blockchain developers make a good case on why the distributed ledger system is the perfect platform for testing the next generation of developments in A.I.
The existing A.I. testing databases are operating in what can be called the red ocean. There is a lot of competition. Similar technologies and methods are being tested with many businesses competing for the same incremental gains. A Blockchain-based database for A.I. represents the blue ocean of uncontested markets. This is because the technology is still new, secure, and transparent. It has the potential to achieve great things in the future. Some of the characteristics that make Blockchain a good contender for testing and building Artificial Intelligence are outlined here.
Decentralized Control and Data Sharing
The Blockchain works on a decentralized network of nodes, working together to solve complex algorithms. The mining node on the network which finds the best solution first adds the entry to the blockchain ledger.
Artificial Intelligence works on a similar model. When a decision must be taken by an A.I. system, it tests the possible solutions and alternating branches of possibilities that emerge as a result of taking the first decision. Evaluations of all possible alternatives are tested to the end result before the A.I. chooses the best option. What makes Blockchain exceptionally good is that instead of a single, central system testing all possible hypotheses, the task is divided among hundreds of nodes spread around the world, which makes the process much faster.
An A.I system being run on a single, central processor is prone to hacking, as any malcontent only needs to break into a single system to manipulate the instructions. Entries to the blockchain platform must be authenticated by the majority of nodes on the network before they are accepted and processed into the ledger. The higher the number of nodes that are operating on the network, the more difficult it is to hack the system.
While a Blockchain-based A.I. platform would not be impossible to hack, it is still far more difficult to manipulate and break such a system.
In order to be reliable, a system must be trusted by the public in general. Blockchain allows far greater transparency than a closed A.I. system. Records maintained on a Blockchain ledger can be reviewed and audited at any time by authorized people with access to the system. At the same time, users who have not been granted access would not be able to view anything, as the database is encrypted.
Take the case of Blockchain application in the healthcare industry. People with medical complications may not want their medical records to be accessed by unauthorized people. Keeping the medical history in an encrypted format instead of plain English ensures that their records could not be accessed by any individual.
On the other hand, keeping the record on a Blockchain also ensures that medical practitioners would be able to provide quick medical aid in case of emergency by accessing the files.
How Blockchain will Transform Artificial Intelligence
Developments in A.I. technology rely on the availability of data from a large number of sources. Organizations such as Google, Facebook, and telecommunication companies have access to large sources of data which can be useful for testing many A.I. processes. The problem is, this data is not accessible on the market.
This problem can be solved by Blockchain’s P2P connection. The Blockchain ledger is an openly distributed registry. The database becomes available to all the nodes on the network. The Blockchain may be the best thing to end the control on data from a few major corporations by allowing it to be freely available.
Modern A.I. & Data
The development of A.I. depends on access to data in much the same way that the construction of a building depends on materials, stone, and steel. This is because data is consistently needed to test and retest alternative solutions for A.I. As an A.I. system continuously tests these hypotheses, rejects the wrong answers, and builds upon the right solution, it improves its capability to make sense of things. This is what we commonly refer to as Machine Learning.
Machines do not have the same sense of intuition that humans developed over millions of years. In order for A.I to one day reach a similar level of intelligence as humans, it would need to test the data of millions of transactions in a matter of years.
Control Over the Use of Data
This is perhaps the most important and limiting factor in the development of A.I., and the reason why Blockchain would work where centralized databases have not. Think of Facebook or Google. When a user logs into their Facebook account, they don’t have the right to any content uploaded on their platform. The content on the platform belongs to the website.
What makes Blockchain different is that data on the Blockchain is not owned by the operators but the individual wallet holder. This gives each user the ability to share their data on the platform without requiring permission for the network operators.
The future of A.I. development lies on a network that allows free flow of information between connected users and operators. The decentralized nature of Blockchain technology means that this could be the platform where we see the most breakthroughs on A.I.
1 november 2018Praktisch seminar waarin Sander Hoogendoorn u laat zien hoe u microservices kunt inzetten in uw softwarearchitectuur.Het nieuwste architectuurprincipe microservices lijkt veelbelovend: verkorte time-to-market, schaalbaarheid, auto...
5 t/m 7 november 2018Driedaagse workshop over requirements management door James Archer. Opstellen, testen en ondubbelzinnig vastleggen van requirements. Unieke driedaagse workshop over requirements management op basis van de Volere methodiek door Ja...
7 en 8 november 2018 De wereld van business intelligence en datawarehousing hanteert een unieke terminologie en eigen verzameling technologieën, ontwerptechnieken en producten. Voor nieuwkomers kan dit overweldigend overkomen. Want wat betekenen al ...
15 november 2018 API Management gaat enerzijds over het promoten van API’s en anderzijds over het actief ondersteunen van ontwikkelaars bij het gebruik ervan. Tegelijkertijd gaat API Management over het gecontroleerd en centraal beveiligd ontsl...
28 november 2018Workshop met BPM-specialist Christian Gijsels over business analyse, modelleren en simuleren met de nieuwste release van Sparx Systems' Enterprise Architect, versie 14.Intensieve cursus waarin alle basisfunctionaliteiten van Enterpris...
6 december 2018 Iedere organisatie heeft te maken met het integreren van systemen en applicaties. Maar welke technologie zet u in bij welke vorm van integratie? Guy Crets bespreekt de verschillende oplossingen voor integratie. Integratie van IT...
11 en 12 december 2018 Vergaar nieuwe databronnen en benut analytics en machine learning om de concurrentie een stap voor te blijven. Er wordt gekeken hoe machine learning en advanced analytics technieken zoals tekst-analyse, sentiment analyse, gr...
16 en 17 april 2019Een pragmatische en geïntegreerde aanpak van business analyse door gerenommeerd spreker James Robertson. Deze workshop behandelt een framework voor business analyse die u gebruikt wanneer u werkt in een agile omgeving en stori...