Blockchain and AI are two of the most disruptive technologies available today. As these technologies continue to develop, whole industries will be transformed. However, a lack of access to open source projects can hinder the development and use of both AI and blockchain.

Data, one of the most important aspects of developing AI, must be collected to train these systems. This article will discuss the future of data processing in AI and how blockchain technologies can help bolster secure data storage and access to the technology.

Many consumers now possess an awareness of these technologies but are unclear how they will impact their lives in the near future.

The emergence of Blockchain and AI for Secure Data Storage

In order to understand how blockchain and AI can be leveraged for secure data storage, we first have to understand how blockchain works. Today, many people are most familiar with cryptocurrencies, which are one potential use-case for blockchain.

Essentially, cryptocurrencies, like Bitcoin, are stored on a secure public ledger. Many people are unsure whether or not Bitcoin is safe and secure, but 64% say Bitcoin is safe to buy, according to recent statistics. 

Machines then work together to process transactions and verify the integrity of the entire ledger or blockchain. In short, a massive network of machines, working together, continuously verifies the accuracy and integrity of transactions, as they occur.

This means that the entire system itself is secure. Detractors of blockchain may argue that it is insecure because people lose Bitcoin or have it stolen. However, using safe options for storing your Bitcoin can help mitigate these types of problems.

In any case, blockchain technology represents a more secure method of storing data because the data is distributed across a network and is continuously verified by all the machines on the network.

Data is the backbone of AI projects

The reason this type of storage is significant for AI is because AI systems depend on data in order to function properly. Most AI works through a process called machine learning. YouTube’s video curating algorithm is a great example of this. 

YouTube uses its AI systems for a variety of purposes, but the key here is that the AI takes in data and then learns from that data. For example, one way that YouTube uses AI is to curate search results. By feeding the AI data on viewing trends and also on what is age and content appropriate, the AI can learn what type of content to serve up when you search for “funny cat videos.”

Open source projects are more secure and benefit everyone

However, one problem with this system is that YouTube’s AI and how it stores its data are all closed source. This means that the only people who have access to these systems are YouTube!

One of the main ways that Bitcoin maintains its security is because all of its transactions are public. Essentially, anyone can look up and see whether or not a Bitcoin transaction is real.

Open-source computing software operates similarly. The theory is that when code is available for anyone to peruse, security flaws and how unstructured data is used become more apparent and thereby allow developers and communities to work together to create a better, more secure project.

Open source projects already run the world

The poster child of open source projects is Linux. In fact, Linux is so successful that over 96.4% of the top one million web servers in the world run Linux. There are countless other applications for Linux as well, from Android phones to televisions.

Last year, an upset occurred in the open-source world when the University of Michigan was banned from contributing to the Linux kernel. The ban was enacted after researchers intentionally introduced security vulnerabilities to test the security of open source projects like Linux.

The swift ban on contributions from the university and the fact that the security vulnerabilities never made it to a public distribution demonstrate how open source projects ultimately ensure greater security.

Putting blockchain and AI to work for secure data storage

One way that open source technologies can be put to good use is by incorporating them into blockchain and AI. Because AI is dependent on data, blockchain is the perfect technology to be united with AI.

For example, healthcare companies could unite blockchain with AI in order to manage patient data and analyze health trends across individuals and groups. Blockchain would provide a robust data system to prevent unauthorized access, and then AI and machine learning could analyze the data and observe trends.

Current Open Source Blockchain and AI Technologies

Fortunately, many open-source AI and blockchain technologies are emerging, and their popularity only continues to grow. Next, we’ll take a look at some of the most popular open-source projects.

One of the most popular open-source AI technologies today is TensorFlow. TensorFlow was developed by engineers and researchers working at Google’s Brain Team. TensorFlow helps researchers worldwide by giving them valuable insights into data.

Hyperledger is the leading open-source blockchain technology. Spearheaded by industry executives picked by the Linux Foundation, Hyperledger aims to allow developers to create enterprise-level solutions using blockchain technology.

What makes these tools useful is that they are targeted at industry professionals but still maintain the principles of open-source software, thereby enhancing their security. However, a comprehensive system for joining these types of technologies together has yet to emerge. Big names like IBM recognize the importance of uniting these two technologies together.

Where will the future take us?

How blockchain and AI technologies will be combined in the future is anyone’s guess, but as data privacy and data abuse become regular conversations, it’s certain that blockchain and AI will continue to disrupt industries. The widespread adoption of open-source software demonstrates that use applications for both AI and blockchain technologies depend on leveraging the security and reliability of open-source software.