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The Convergence of AI and Blockchain: What You Need to Know

A joint blog by Kambria and Liquid Head of North America Nick Chong Modern artificial intelligence and blockchain are two of the most powerful technologies shaping our current realm of global digital information. Combining these technologies opens a whole world of possibilities.
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A joint blog by Kambria and Liquid Head of North America Nick Chong

Modern artificial intelligence and blockchain are two of the most powerful technologies shaping our current realm of global digital information. Combining these technologies opens a whole world of possibilities.

In fact, there are a growing number of concepts and disciplines, particularly among leading AI companies, regarding the impending importance of combining blockchain and AI.

In this article, we’ll explore some of the foundational thinking that exists on how blockchain and AI can thrive together.


The line between AI and blockchain

Artificial intelligence aims for human-like cerebral efficiency in action, decision and processing.

Blockchain aims for security, transparency and decentralization in action, decision and processing.

Already we can see how AI and blockchain appear to complement one another – a sort of yin and yang, balancing each other’s strengths and weaknesses.

This is the basic premise of proposals for combining the two technologies. After all, if you want to make a decentralized, data-encrypted, tamper-proof system that has the processing efficiency and level of structure of an AI, then we’ve probably officially entered the fourth industrial revolution.

The possibility of combination

So what exactly are the benefits of combining AI and blockchain?

For AI, having a blockchain as its base system would be beneficial for a number of reasons:

Development becomes more observable

Visualizing the development and evolution of neural networks is typically impossible for humans when a deep learning system reaches a certain number of iterations.

However, because each process in a blockchain is reported to all nodes within the network, we have a valuable opportunity to be able to see step by step how AI would operate when placed within its framework.

Training AI becomes inexpensive

Centralization is one of the biggest issues concerning big AI today. A lot of the most powerful, and therefore, useful AI systems are currently owned by big tech corporations that can finance the huge costs needed to process the sheer amount of AI data.

Developing the algorithms of an AI on a blockchain would not only make it decentralized via hardware distribution, but also make it cheaper, as it is accessible to more users due to the basic structure of a blockchain network.

Malicious alterations are limited, if not prevented

Even if it is technically possible to falsify data within a blockchain network, the mere attempt at doing so would be easily noticed by all nodes, and thus can be prevented to an efficient degree. Deep learning is especially vulnerable to targeted alterations in the initial data, so the early detection provided by a blockchain and AI system is a very welcome security addition. Besides, the blockchain’s data encryption is not practically penetrable anyway.

For blockchain systems adapting AI, there are also benefits:

Direct performance enhancement

Blockchain’s basic architecture has a distributed nature that leads to inherent speed limitations. This is because processing tasks require every node to run the blockchain in order to gain the approval of all nodes for a certain action or decision.

With a deep learning system, optimization of data becomes possible as the AI adapts to the way information is diffused throughout the blockchain. For cryptocurrency, this could mean faster verification of transactions, and for database-related tasks, this means reduced access latency. All without compromising security.

Making smart contracts smarter

A smart contract is basically a verification protocol that is distributed across a blockchain network. One criticism about smart contracts is that they were previously proven to be vulnerable to value-based errors.

While the bug was presumably eventually fixed, it is conceivable that similar errors might happen in the near future. With AI and blockchain, such loopholes and vulnerabilities can be detected early as it “learns its way”.

Optimizing energy consumption

Anyone with any kind of Bitcoin mining setup knows just how energy intensive blockchain systems can be. Machine learning AI, while also having this same inherent problem, can be developed and programmed to learn and develop energy management to keep a blockchain system running efficiently. If it knows where to focus hardware resources along the network as it needs to per operation, huge energy savings, and thus cost, can be achieved.

The path forward

According to the latest statistics from Statista, there are currently almost 35 million blockchain wallet users around the world as of the first quarter of 2019. While this growth is fairly significant compared to last year, in the United States this still averages to about 8% of Americans using cryptocurrency of any type. Compare that to the number of people regularly doing billions of digital transactions every day using traditional fiat currencies.

Perhaps AI will open floodgates to blockchain to make cryptocurrency and other immutable, decentralized database systems even more prevalent in our current world. There’s huge potential for combining blockchain and AI and what it means for this looming data revolution.

Want to learn more? Developers interested in getting more involved with AI and blockchain can check out Kambria, an open innovation blockchain platform focused on AI and robotics. Kambria is hosting a series of hackathons around the world starting with the Vietnam AI Grand Challenge. The deadline to register for that event is June 25, 2019. See Vietnam AI Grand Challenge for more information and join Kambria on Telegram or Facebook to stay up-to-date on future hackathons.

Image via www.vpnsrus.com

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