Industries Thriving In Productivity From Blockchain + AI (Part-II)
One single vulnerability is all attacker need …
Blockchain can be represented in pithy words as
a chain consist of digital “blocks” that contain transaction records. Before and after it, each block is connected to all the blocks. This makes it almost impossible to tamper with a single record because the block containing that record as well as those connected blocks to it will need to be altered by a hacker to evade suspicion. Cryptographic algorithms protect the records on a blockchain. Nodes in the network use their private keys allocated to the transactions they make, which serve as a personal digital signature. The signature done with the private key will become invalid if a record is changed and the peer network will know that something must have happened.
Blockchains are decentralised and distributed through updated continuously and synchronised peer-to-peer networks. Since they are not centralised or fixes in a central location, there is no single point of failure for blockchains, and it is difficult to modify them from a single system. It will take huge volumes of computational power to reach each instance (or at least a 51% majority) of an individual blockchain and modify them all at the same time.
What defines AI?
Artificial Intelligence is the implementation of human intelligence in computers programmed to think or make decisions like humans and to try to mimic their actions. The terminology can also refer to any computer that exhibits features associated with a human mind, like learning and problem-solving.
AI can simply be seen as intelligence displayed by machines that could be used in a beneficial way ( e.g., performing tasks, making decisions, assisting differently challenged people, improving the human standard of living). In general, AI describes when a computer can learn from information (data), produce a certain degree of knowledge, and then use the knowledge gained to do something. Machine learning and advanced strategies such as deep learning are part of AI.
The amalgamation of blockchain and AI technology
AI is the centralised mechanism for all purposes. To achieve a trustworthy business result, an end-user must have extreme confidence in the central authority. Blockchain can produce the confidence and trust often needed for end-users to embrace and rely entirely upon AI-based business processes by decentralising the three main elements of AI, i.e. data, models, and analytics. AI can enrich by providing data, models and analytics with confidence.
1) Securing the data with AI and blockchain
Many of the most remarkable AI technology services in the world, like Amazon, Apple, Facebook, Google, are centralised. But, among them, everyone has encountered challenges in building trust. As in the digital rights management system, a blockchain ledger can be used, allowing the data to be “authorized” on the terms, conditions and length to the AI provider. The ledger will serve as an access control system that records evidence and permission from which a corporation can access and use the data of the customer. In the current scenario, recommendation system has the intensely personal data of the user and to keep it secure blockchain data security can be used.
2) Verifying the provenance of the reliable ai trained, model
Blockchain technology provides a way of trusted machine learning data and the authenticity of training models. This question-answering system that we develop is considered a model, and it is created through a process called training. Training helps to create a useful model that correctly answers our questions most of the time. We can monitor the provenance of the training data with the blockchain as well as see an audit trail of the facts that contributed to the prediction.
3) Blockchain Attempting to explain decisions about AI
Blockchain can explain the provenance, reliability, understanding, and descriptions of specific findings and decisions. If decisions and correlated data points are registered on a blockchain through transactions, the Blockchain’s inherent attributes will make it much easier to audit them. Blockchain is leading technology which provides trust to network transactions, and therefore infusion of blockchain into AI decision-making
processes may be the required element to achieve the integrity needed to trust AI-derived decisions and performance completely.
4) AI will make it easier for everybody to monitor, interpret and provide a choice for approving the node in the blockchain
AI algorithm can be used to check over all the monetary transactions that are dishonest and so that transaction can be blocked or investigate further before adding the node to the blockchain and may save from many different attacks possible on the blockchain.
5) AI can navigate blockchains a lot more easily than humans
With the help AI algorithm, we can check over all the types of brute force approach before deciding the hash value for the blockchain and manage the security.
6) Energy consumption savings
Due to the decentralised nature of blockchain, the processing of AI algorithm will not be dependent only on one server, and so because of its energy consumption can be optimised.
Case studies on industries thriving on
Blockchain+AI
1. HealthyTail:
HealthyTail is a company that shares pets health data between scientists, breeders, and pet owners.
Here, the pet owners share the data regarding their pets’ health disease issues through the blockchain platform. Their blockchain allows pet owners to earn back the money spent on genetic testing by sharing the data. That data is used by pharma companies to develop and deliver new personalised drugs for their pets. These data are also used for training an AI-based model for further classification of relevant drug manufacture for the pet diseases. The core of HealthyTail is blockchain-based storage and compute platforms for genome-wide association studies. HealthyTail also pioneers services on HealthyTail core platform — such as genetic diagnostics, genetic-assisted breeding, breed certificates, personalised medicine.
Below given is their business model, where the financial model expects the following costs and revenue:
Find more insights and facts HealthyTail here
2. BurstIQ:
BurstIQ was founded with one mission: to enable this next era of health. BurstIQ is the leading provider of blockchain-enabled data network solutions for the healthcare industry. The company’s private, permissioned data network allows health systems, payers, digital health companies, pharma & life science companies and governments to unlock the full potential of health-related data. The unique platform uses blockchain, Big Data, machine intelligence, and granular data ownership and consent to build longitudinal profiles of people, places, and things and empower the interactions between them. The platform connects any data from any source in a global network of businesses, researchers and people — all connected directly to each other. The result is a global, secure data network that allows health systems, payers, digital health companies, pharma & life science companies and governments to collaborate, share, analyze and unlock a deeper understanding of the diverse factors that influence health.
Their core technical specifications include: Cloud Enablement, Cyber Security, Agile Transformation, Big Data and Analytics, Digital Health, Blockchain, Digital Currency, Data-driven Research, Healthcare, Machine Intelligence, Deep Learning, and Artificial Intelligence
Explore more information about BurstIQ here
3. EUKLID:
Euklid company has new way to manage savings and investments through thousands of different algorithms. It is based on concrete data processed with Artificial Intelligence technologies.
It is transparent and secure, because it’s based on blockchain a technology which lies at the heart of Bitcoin time stamp and encryption system, that guarantees clients a constant monitoring and an absolute certainty that nobody can manipulate his account.The algorithms are based on the most advanced technologies that reached remarkable results through extensive experimentation and are secured by Euklid LTD exclusive proprietary mathematical models.
Their algorithms includes:
• Like fingerprints
• Horizontally arranged
• Bio-computed
• Adaptive to change
The collective psychology of the economic agents that works on specific stock or index leave a fingerprint not recognizable by human eye, but only by Artificial Intelligence models.
Their algorithms are specifically trained to recognize conservative and innovative behaviours, selecting from chaos and randomness, catching the result of mutual dynamic interaction. The algorithms have not a sequencing horizontal arrangement of the trading rules that is opposed to a vertical arrangement, which implies that, by principle, the same result cannot happen twice, rethinking time by time what are the current trading rules.
They are based on biocomputing, a science linked to maths, physics and biology. Biocomputing allows to perform calculations involving the storing, retrieving, and processing of data.
The optimization process is ensured by:
• Swarm Intelligence, that catches the logic of a moltitude of informations moving in an apparently disordered manner.
• Neural Networks, interconnecting information through artificial neurons and processes utilizing a linked calculation approach;
• Genetic Logic, an adaptive system that changes its structure based on external or internal information flowing through the net during its learning process.
Their algorithms work like Nature: select and reproduce the fittest model as an evolutionary process.
You can search for more information about EUKLID here
Summary:
The two extreme sides of the technology continuum are blockchain and AI: one supporting centralised knowledge on specified operating information networks, and the other supporting decentralised applications in an open-data setting. However, if we discover an intelligent way to create them operating along, the overall positive externalities may well be intensified.
Do visit the first part of the article from the link given below:
