Artificial Intelligence is at the forefront of almost every new and innovative technology emerging today. Within academia, industry, and, most importantly, the open-source world that bridges the two, AI is the future. The ability to learn, the intelligence in AI, is what sets these systems apart. They strive to replicate the human traits of abstract, deductive and creative thought—the foundation of learning—while exploiting a machine’s rigorous execution.
Until recently the most significant hurdle to the development of Artificial Intelligence was the lack of sufficient data sets to analyze. With the greater and greater integration of technology into everyday life, there is a virtually endless supply of data to exploit. Applied Artificial Intelligence tools continue to be developed to complete specific tasks in fields as varied as finance, manufacturing and quantum physics.
Today, Watson is one of the most famous and advanced projects in the artificial intelligence space. A computer system that is notable for its ability to recognize and answer questions asked in natural language, Watson was developed by IBM as an open-source project, allowing people access to the inner workings of the technology. As exciting as these advances are, there are many other smaller and less prominent examples in use in everyday life. However, there are elements that can raise some concerns relating to the data needed to power and train the ‘intelligence’.
The Need For Decentralized AI Platforms
Despite the promises of the technology, there are numerous issues that need to be looked into in order to truly grow this space.
In recent times, AI has become a worry for many people. Data is a valuable resource and commodity seeing as large corporations have utilized it for nefarious reasons and uses. Facebook, a common sight in headlines relating to online privacy scandals, is an example of a centralized company that uses artificial intelligence and machine learning.
The social network utilizes these technologies to keep track of the vast amount of data flowing through the platform. Information such as location, interests, and even moods can be tracked and recorded. The face recognition feature is also an example of these technologies being used. This data played a role in the distribution of fake news and targeted political ads during the Cambridge Analytica scandal. In this case, an app was used to collect the private details of 87 million users without their knowledge.
Using AI, it was possible to find credulous people and fill them with fictitious news that they are willing to replicate. Of course, they are also used by other companies and across different industries. When users search online using Google for example, the browser and search engine discreetly offer products that users were coincidentally looking for, travel recommendations. Spam filters are able to identify spam emails with increasingly high accuracy rates. All of this is possible through AI algorithms and machine learning.
Access And Democratization
It is no secret that these technologies are expensive, resource-intensive, and time-consuming to produce. This is especially true in a market where businesses are developing in house and behind closed doors. As such, only the biggest companies with the money can afford to put time and money into developing AI and the associated technologies.
Beyond development, there is also the infrastructure that is necessary to power the ever-growing database that allows machine learning to occur. It is for reasons such as this which have lead to the current landscape where only the most prominent, rich companies (e.g. Facebook, Google, Amazon) have been making large strives forward in development. That isn’t to say there are smaller, less prominent players in the market that are driving innovation, however. It is just that there could be a lot more if it was more open and accessible.
Blockchain-based AI Projects On KuCoin
Decentralized AI and machine learning platforms offer a more secure system that can be made available to a wider user base. Privacy can be upheld much more effectively, allowing for a more ethical means to power AI development. At the same time, by enabling more companies access to resources such as developers and technologies, innovation can be increased. Both large and small scale projects will be able to take part. While there are some issues to be overcome, significant progress has been made.
Currently, there are numerous examples of blockchain-based AI projects that are building decentralized platforms. These are a few that are listed on KuCoin.
SophiaTX – Enabling Enterprise Blockchain Solutions For AI
The goal of SophiaTX is to help companies incorporate the blockchain into their business. Due to the flexibility, security, and capabilities of the blockchain, SophiaTX is helping companies to integrate the technology as a part of their digital strategy. In the case of artificial intelligence development, it has identified the blockchain as a suitable platform for providing scalability and the necessary abilities needed to adapt to the market.
The open-source blockchain platform and marketplace offered by SophiaTX enable businesses to utilize the blockchain without relying entirely on their own internal capabilities. As an open-source platform, it contains integration APIs to SAP covering leading ERP, CRM, and SCM systems. This opens up the possibility for more people to access blockchain technology and thus facilitate the development of decentralized AI platforms.
The blockchain and artificial intelligence go hand in hand, as the decentralized nature of blockchain allows for computing at scale. This is why SophiaTX sees the area as one of the key focuses for integration with its blockchain.
Developing A Blockchain Solution
The blockchain is specifically for business operations and can integrate with traditional business enterprise software. Meanwhile, the marketplace is an ideal environment for sharing apps created by developers, experts and consultants that easily integrate with SophiaTX’s blockchain. It provides a comprehensive set of tools that allow developers to build and publish applications that utilize the power of the blockchain This means that AI developments can be developed, sold, and easily integrated into a business’ workflow.
The variety of use cases for the SophiaTX blockchain make it a promising prospect. As more businesses see the benefits of adopting blockchain into their workflow, more will be able to access the growing library of developments, both AI-related and otherwise.
SophiaTX recently announced the launch of E-XBRL, their first product and real-world application of the SophiaTX blockchain.
DeepBrain Chain – Accelerating Artificial Intelligence’s Advancement
Another company looking to solve the problems facing the democratization of Artificial Intelligence is China’s DeepBrain Chain. Using the NEO platform, they are focusing on a key factor that prevents the majority of small developers from entering the AI market: Costs related to computing hardware in the industry can be very high.
By creating a low-cost and privacy-protecting AI computing platform, DeepBrain Chain aims to provide high-quality computing power to developers around the globe as well as expanding into the market of AI apps and tools themselves.
Using a decentralized platform, a network of miners has been created, organized into different sized nodes to share the computational load. These nodes can come in the form of large, dedicated, GPU server clusters, the idle servers of medium-sized businesses and GPUs owned by individuals. This network of miners distributes the burden of hardware costs while also reducing the cost to the specialized developers.
Incentives for miners come from two paths with payment in the form of DeepBrain Chain’s own crypto utility token. 70% of a nodes’ income comes from the mining rewards function; the remaining 30% is paid by AI companies utilizing the network. This unique allocation of costs allows smaller firms to experiment with different tools while avoiding the monumental computing costs associated with these technologies.
Focusing On Convenience
The other issue that the project will address is the issue of data accumulation. These massive data sets have to come from somewhere: most companies that are exploring AI technologies have to either continuously annotate low-quality data or purchase high-quality data from providers. However, privacy becomes an issue in these transactions. Their network functions using smart contracts that separate the purchaser from the supplier and ensures privacy for all parties.
DeepBrain Chain’s core team has garnered attention across the industry as well as winning several awards and distinctions. Despite the fact that they released a program called “Skynet,” their innovations in load sharing and privacy protection are making waves in the AI sphere.
A very interesting development has also arisen in the form of a partnership between DeepBrain Chain and SingularityNET: a mutually beneficial relationship between these two could see the landscape of Artificial Intelligence progress in significant ways.
DeepBrain Chain is cooperating closely with ASUS, providing technical support and helping them to trial the DBC network.
Alphacat – Accessible Cryptocurrency Investments With Robo-Advisors
Alphacat has a much more specific objective. They aim to democratize Fintech using the blockchain.
In the past decade, the use of “financial technologies” to gain an edge in the investment game has increased. As these tools continue to develop they are proving themselves to be profitable aids for investing. However due to factors like the capital and level of expertise required to utilize these tools the average investor has not been able to cash in on the benefits they offer.
Another issue facing the evolution of Fintech is the lack of a space for developers to test and list new tools. Currently, AI developers have to seek employment in-house for large financial institutions limiting their creative output as well as their ability to benefit from their inventions directly. Alphacat has created a network to provide investors of all experience levels a means to access Fintech while simultaneously offering developers a space to display and offer their innovations.
The Alphacat Ecosystem is made up of three components. The ACAT Terminal collects, organizes and stores massive amounts of data, while the ACAT Engine is comprised of thousands of AI robots that utilize these datasets. The ACAT Store serves as the marketplace to access these robo-advisors. The ACAT token is the NEO currency used in all transactions within the ecosystem as well as being traded on other platforms.
AI Development Marketplace
Participants in the Alphacat marketplace fall into three groups: Architects, Surveyors, and Ordinary investors. Architects are the developers and financial experts creating the tools that make up the ACAT Engine and eventually end up in the ACAT Store. After using ACAT tokens to stake their invention, architects are incentivized through reward functions based on the amount of use their tool gets.
Surveyors are professional investors that evaluate and, for a fee, distribute promising new tools to receive rewards as the tools gain popularity. Finally, the Ordinary investors are provided with a simple to use yet effective aid in their crypto investments.
Developed by a team of Wall Street veterans and former Google AI developers with an extensive list of partners and investors, Alphacat is bringing the advances of Fintech into focus in the crypto market. With the continual growth of cryptocurrencies and broader public interest, Alphacat, by providing everyday users with the tools to make informed investment decisions, is setting the standard for things to come.
Alphacat is continuing to develop the ACAT Store, a key part of the ecosystem, with new features and a PC version in the works. A total of 89 applications are now listed, made up of a mixture of Alphacat developed and third-party developed applications.
Matrix – Leveraging AI To Deliver on the Promise Of Blockchain
The Matrix project is another exciting example of the potential for Artificial Intelligence in the crypto world. Billing itself as the dawn of “Blockchain 3.0” it aims to use AI to innovate.
Most notable is the goal of using Deep Learning AI to create smart contracts without the need for programming knowledge. This innovative technology allows a user to create a smart contract using only the essential elements: input, output and transaction conditions. The project then uses this abstract description along with a code generator to utilize a deep neural network and produce an executable program.
Matrix also uses its AI tech to increase the security of smart contracts. Along with semantic and syntactic analysis, it makes use of an AI-based detection engine for transaction model identification as well as a deep-learning platform for ongoing and dynamic security and verification improvement.
Improving The Application Of Blockchain
The issue of slow transaction time is addressed by creating a “delegation network” where certain nodes are selected to represent groups of other nodes. Utilizing a combination of PoW and PoS this network reduces the transaction time by consolidating the number of nodes involved. A TPS of 100,000 will be supported on the online version of Matrix.
Along with transaction latency, Matrix will be a highly “flexible” blockchain. Flexible in that it will offer access control and routing services allowing for flow from a private chain into a public one and vice versa, without sacrificing the security and data regulation required of government and industry groups. It also uses a reinforcement learning framework to update transaction parameters dynamically and evolutionarily continually.
Finally, Value Added Mining is a Matrix concept that utilizes the Markov Chain Monte Carlo computation, currently used in many Big Data applications. This means that as the equations are used in real-world scenarios, they can also be used to mine ‘MAN’ tokens. This is a huge step considering that 70% of the world’s computing power is currently used to mine Bitcoin and other cryptocurrencies. With a world-class team behind this project, the potential is real.
The second major update to the Matrix AI network has taken place, with new features such as fixed/flexible stakes and verification masternode pools now going live.
Kambria – Empowering Innovation In AI And Robotics
For Kambria, the aim is to empower decentralized platforms to innovate. Specifically, it targets ‘frontier technology’, including the likes of AI and robotics. These industries are very much at the forefront of innovation and their use cases in the real world are becoming more apparent.
Artificial intelligence and machine learning are potentially very lucrative and so it is understandable that companies are looking at ways to adopt these technologies to improve their respective industries. Kambria is looking to facilitate that shift using its decentralized open innovation platform. The goal is to foster a collaborative ecosystem where companies and developers can work together and share technologies to accelerate their development. This ultimately makes their development easier, faster and cheaper.
AI, in particular, is an area impeded by siloed development, which is why Kambria puts a particular focus on the industry. One way it incentivizes developers to join the platform and work on AI projects is through bounty challenges as well as ensuring the platform is easy to use. Having a user-friendly design can greatly improve uptake. Educational programs and hackathons are another way the talent pool can be developed. Once the community is in place, more projects and developments can occur, with the goal of achieving mass market adoption of these new technologies.
Kambria's Unique Approach To AI
What sets Kambria apart from other similar projects is the way it fosters both development and adoption of AI and Robotics. It takes it all the way from the conceptual stage, through the manufacturing process, and to the distribution stage, all without the need to rely on third parties. Companies are set to benefit greatly as they no longer need to fund costly research and development in house, instead being able to license technology from the platform for use.
With a team experienced in engineering with backgrounds in robotics and AI, Kambria looks to be the perfect environment for the technology to flourish and see widespread adoption.
Helping it on its way to increase understanding and education in robotics, Kambria has teamed up with Data Application Lab. The partnership will focus on building joint AI & Robotics Labs in major Chinese universities and updating the curricula and training.
The Growing Ecosystem Of Blockchain Use Cases
The continuing role of Artificial Intelligence in all facets of industry, especially in the world of crypto, is undeniable. The only question is who can identify and exploit the openings in the market. As seen so far, the possibilities for different combinations and applications of AI are limited only by the imaginations of those with the tools to create. Undoubtedly, there will continue to be more complex and more useful examples of this seemingly limitless technology in the future.
While advances are small and may not be perceived, it is clear that the world is witnessing a technological revolution, with these early adopters fueling the growth of the blockchain AI industry.
Find more interesting projects on the People's Exchange.
Japanese Times. (2019, January 10) Trump campaign firm Cambridge Analytica pleads guilty in Facebook data grab. Retrieved from: https://www.japantimes.co.jp/news/2019/01/10/business/trump-campaign-firm-cambridge-analytica-pleads-guilty-facebook-data-grab/#.XL_RUOgzaUl
Rodriguez, J. (2018, September 19) Everything You Need to Know About Decentralized AI. Retrieved from: https://towardsdatascience.com/everything-you-need-to-know-about-decentralized-ai-3abdb052324b