The Benefits of Combining ML and Blockchain
In the next five to ten years, these two technologies are going to be heavily implemented in business. Even now, innovative and tech-savvy industry leaders see significant value in using blockchains with artificial intelligence.
Let’s have a look at ways you can use the combination of ML and blockchain to your company’s benefit.
• Enhancing security: Information in a blockchain is well-protected thanks to inherent encryption. A blockchain is perfect for storing highly sensitive personal data like medical notes or personalized recommendations. Data is what artificial intelligence needs continuously and in high volumes. Currently, experts are busy building algorithms that will allow ML to work with encrypted information without exposing it.
There’s also another angle to security improvements, however. While the blockchain is secure at its base, additional layers and applications are vulnerable (consider breaches of DAO, Bitfinex, etc.). Machine learning will help to improve the deployment of blockchain apps and predict possible system breaches.
• Untangling the way ML thinks: Regardless of how great ML is, people won’t use it if they don’t trust it. One of the issues that has put the brakes on broader adoption of ML is the impossibility to explain decisions made by the computer. With the possibility to record the decision-making process, ML can gain public trust much sooner.
By using the blockchain for artificial intelligence, we can make the way computers think more transparent. A distributed ledger can store every decision made by AI, data point by data point, and make them available for analysis. With a blockchain, you can also be sure that the information is tamper-resistant from recording to examination.
• Accessing and managing the data market: This point is tightly connected to enhanced security. Since a distributed ledger can store large amounts of encrypted data and artificial intelligence is able to manage it effectively, new use cases emerge. You can securely store your personal data in the blockchain and sell access to it. As a result, data, model, and ML marketplaces arise.
Big players like Google, Facebook, and Amazon have access to large volumes of data that can be useful for ML processes, but all of that information is unavailable to others. With a blockchain, smaller companies and startups can challenge the tech giants by accessing the same pool of information and even the same ML potential (we’ll talk about the ML marketplace Singularity NET later on).
Another perk of using artificial intelligence with the blockchain is improving the way we work with data. Computers process encrypted information by going through multiple combinations of characters in search of the correct one to verify a transaction. Similarly to a human hacker, ML learns and sharpens its skills with every successful code crack. But unlike a person, artificial intelligence won’t need a lifetime to become an expert. With the right training data, it can happen almost instantly.
- • Optimizing energy consumption: Data mining is a very energy-consuming process. This is one of the major struggles of the modern world, and Google has proven that machine learning can deal with the issue. Google has managed to reduce energy consumption used for cooling their data centers by 40% by training the DeepMind AI on historical data from thousands of sensors within a data center. The same principle can be used for mining, leading to lower prices for mining hardware.
- • Improving smart contracts: There are certain technical flaws in the blockchain that can be exploited by hackers (Figure 2.37). This was proven not so long ago. Put simply, smart contracts aren’t smart enough. Yet, they’re programmed to
FIGURE 2.38 Formal verification.
release and transfer funds automatically when certain conditions are met. To do that, network consensus must be reached on the blockchain. Smart contract code is public and can be reviewed, so anyone can patiently and thoroughly go through every line of code in search of loopholes. The ML helps to verify smart contracts and predict vulnerabilities that can be exploited.
• Formal verification of smart contracts: Plus, artificial intelligence can deal with contracts itself by reviewing conditions and generating and dynamically adjusting smart contracts (Figure 2.38).
Applications of ML and Blockchain
- • Automation in manufacturing: As a part of the manufacturing procedure, companies are now relying on smart contracts and Bitcoin blockchain- based processes to enable transparency, production, security and compliance checks. Instead of planning traditional fixed machine maintenance schedules, machine learning’s predictive algorithms are being used to design flexible plans. Product testing and quality control also have progressively become automated.
- • Food and logistics: The ML and blockchain are progressively reducing end-to-end supply chain challenges in the food industry by enabling transparency and accuracy. With blockchain coming into play, tracing food sources and management of related financial transactions has become possible.
Recently, IBM collaborated with Twiga Foods and launched a blockchain- based microfinancing strategy for food vendors. But the mission wouldn’t have accomplished without the application of ML techniques. The IBM scientists purchase data from mobile devices, analyzed and then implemented ML algorithms to determine credit scores and predict creditworthiness.
• Energy and utilities: In the energy and utilities industry, blockchain is helping in facilitating energy exchanges. For example, IOTA, an energy- based company, has recently implemented blockchain energy production and consumption in a peer-to-peer fashion. Smart energy microgrids are also increasingly becoming a popular way of creation of sustainable energy resources. L03 Energy, a NY-based company, is also using a blockchain- based innovation for enabling energy generation, conservation, and trading for local communities.
What Fields Leverage the Combination of Artificial Intelligence and the Blockchain?
All of the above are theoretical benefits of combining a blockchain and AI. Now, let’s move to real-life cases. Different industries are already testing the waters of using blockchain and ML together in one project. It’s still too early to pop the champagne, but the first tries look really promising.
Porsche is officially the first automaker to test the blockchain in vehicles. It partnered with the German startup XAIN to implement blockchain technology in its brand-new sports car. Using their smartphones, drivers will be able to record traffic data, which has been received from connected vehicles, on a blockchain. The solution will also allow owners to grant temporary access to a car and receive notifications about who accesses it, where, and when. And let’s not forget about the increased security and auditable and usable data for predictive maintenance and autonomous driving.