Artificial intelligence (AI) and machine learning have emerged as two technologies that could dramatically affect blockchain and all the people, organizations and companies that use this technology. But blockchain is essentially a distributed ledger which is known for its reliability and simplicity, so how does machine learning and AI improve this already-innovative technology? Well, to appreciate the potential role of artificial intelligence and machine learning, it’s essential that you understand exactly how these two technologies are used.

Artificial intelligence and machine learning could dramatically affect blockchain and its users.

Image Source: Pixabay user freephotocc.

Combining Artificial Intelligence and Machine Learning in Blockchain

Artificial intelligence is a technology that captures the imagination while simultaneously giving developers the cold sweats at the prospect of self-programming software. Most think of human-like androids in films such as iRobot when they hear the term AI, but in reality, artificial intelligence is so much more. After all, the applications are virtually limitless. At its core, AI technology processes data and then uses this information to take some sort of action in accordance with an algorithm. Over time, though, the algorithm can evolve, making this technology dynamic and adaptable.

Machine learning algorithms are designed to organize data and identify trends and patterns. At its most fundamental level, the machine learning algorithm is a data processing mechanism that can be programmed to look for specific types of patterns or events. Predictive analytics engines can be used in conjunction with machine learning technology to make predictions or recommendations based on the data.

This information is ultimately used to fine-tune everything from search engine algorithms to weather forecast models and cybersecurity applications. Artificial intelligence technology is programmed with a specific goal or objective in mind, such as identifying and guarding against cybersecurity threats. Then, machine learning could be used to monitor the frequency and nature of cybersecurity threats, in addition to identifying the traits and characteristics of hackers, malicious bots and viruses. Predictive analytics technology may be used to evaluate each possible threat, offering a prediction as to whether the threat is real. Finally, the AI platform processes the trends, patterns and potential threats, implementing updates to the cybersecurity application to guard against the most probable threats.

Of course, the concept of a self-programming application can be a bit terrifying, so, much to the relief of developers worldwide, AI interfaces can be programmed to recommend modifications or changes which must ultimately be approved and implemented by a human. It’s even possible to program the system to automatically implement changes that meet particular criteria while requiring human approval for all other alterations.

Blockchain’s Connection to Machine Learning and Artificial Intelligence

It’s clear that AI and machine learning technology could really transform our techsphere. But how does this relate to blockchain? Well, an increasing number of applications are tapping into the power of blockchain, including security applications which use this technology to record security breach events and data surrounding potential threats.

Cryptocurrencies—which were the first to invent and utilize blockchain—use this platform as a decentralized transaction ledger. AI and machine learning can be added to the mix in order to identify, flag and intercept fraudulent transactions or identify and refer miners to blocks with an especially high volume of transactions. Machine learning and AI could also be used to help with the maintenance of blockchain as a decentralized, distributed infrastructure that leverages computing power from countless locations worldwide. It’s conceivable that artificial intelligence and machine learning could be useful for maximizing blockchain performance while maintaining security and stability across blockchain’s many nodes.

These uses for AI and machine learning become increasingly relevant as cryptocurrencies gain momentum and as more developers integrate blockchain technology into cutting-edge applications and high-tech infrastructures. If you’re ready to make the most of blockchain, it’s prudent that you seek a development team that has experience with these complementary technologies. That’s precisely what you’ll get when you turn to the team at SevenTablets. Our developers have worked with a wide array of emerging technologies such as augmented reality, virtual reality, artificial intelligence, natural language processing, machine learning and predictive analytics.

Based in Dallas, SevenTablets works with clients throughout Texas—including Austin and Houston—and beyond. We invite you to contact our team today if you’re ready to discuss your project.


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Venkatesh Kalluru

Venkatesh Kalluru

Chief Technologist, Head of Engineering at SevenTablets
Venkatesh “VK” Kalluru is a technology and business expert with executive and hands-on experience in automating multi-million dollar enterprises and a strong record of success in creating robust information technology architectures and infrastructures. VK brings proven ability in using IT to solve business issues to the SevenTablets team.

VK studied computer science at Jawaharlal Nehru Technological University in Hyderabad, India and earned a Master’s Degree in computer science at George Mason University.
Venkatesh Kalluru