What is Deep Learning and how can blockchain enhance its reach?

One of the most current issues in the digital world is the deep learning and artificial intelligence (AI). These two concepts have a profound impact on the digital world and promise to forever transform our lives, including our interaction with blockchain technology.

But What exactly is Deep Learning? How does this concept relate to blockchain technology? Well, let's answer these questions.

What is Deep Learning?

When we talk about Deep Learning or Deep Learning, we are talking about a series of methods and computational algorithms built on artificial neural networks (or RNA) with the ability to perform representational learning.

Deep Learning algorithms have wide utility in fields such as computer vision, speech recognition, natural language processing, machine translation, bioinformatics, drug design, medical image analysis, climatology, materials inspection and board game programs, where they have produced comparable results and, in some cases, superior to the performance of human experts. The best thing is that these algorithms are capable of carrying out these learning actions in a supervised, semi-supervised or unsupervised way.

RNA, the construction base for Deep Learning

The artificial neural networks (RNA) were inspired by the information processing and distributed communication nodes of biological systems. However, RNAs present several differences with respect to biological brains.

Having said this, it can be seen that the main idea behind ANNs is replicate the most basic functions that make the human brain work. With this approach, ANNs would not only be able to replicate the basic data-processing capabilities that human brains do naturally, but also scale up those structures to create more advanced functions.

The result of this rapprochement and development has been explosive, since the ANNs have become a key component for the construction of the Artificial Intelligence (AI), machine learning (Machine Learning) and deep learning (Deep Learning).

Deep Learning and blockchain: enhancing the reach of both technologies

Knowing the potential of Deep Learning technology, we are left with a question: How can we take advantage of it to improve and integrate it into blockchain technology? Well, the reality is that this is a question that many projects have devoted themselves to answering and making a reality.

A smarter and more secure blockchain

After all, making use of Deep Learning on the blockchain would allow adding a series of unique capabilities to this technology that could make it not only smarter, but also more flexible, secure and private.

In addition, the blockchain can become a space to develop decentralized and secure infrastructures that serve to feed the datasets necessary to make these Deep Learning models a reality and everything related to the world of artificial intelligence.

Improving AI model building

Another use where blockchain and Deep Learning can enhance their capabilities is the building better learning models using the decentralized data architecture of blockchain technology. That is, using the same blockchain to chain jobs that can be studied and thus generate new, much more powerful AI models. Furthermore, Deep Learning models can use the data stored in the blockchain network to make predictions or for data analysis.

Let's take an example of any smart application where the data is collected by different sources like sensors, smart devices or IoT. In the blockchain, the necessary logics can be developed not only to gather all this data and process it in the network (a job for which the nodes will be rewarded), but also said network would serve as a gateway for users to use the AI ​​for different tasks as required.

Contrary to what currently happens, where there are access lists and different controls that make this relationship impossible, this would represent a democratization of access to AI.

Furthermore, if we store the data processed for an AI on a blockchain network, it can be reduce errors and biases within said information, making it more heterogeneous and thus generating more realistic models.

Generating new markets and job opportunities

One of the great possibilities of blockchain in Deep Learning is the construction of new markets and generation of employment or individual economic opportunities within those markets.

For example, a blockchain dedicated to Deep Learning (or any other branch of AI) could not only use its network to store information, but also to use their computing power to process the data (reducing costs and creating much more powerful networks than many current supercomputers) and thereby generating economic dynamics that would benefit many people around the world.

We have already seen this with cryptocurrencies and their PoW networks. Miners are capable of generating value and living from it, but in this case, the aim would not be to generate a simple number that corresponds to the difficulty of the network, but also to respond and generate the necessary data analysis to feed the AI ​​(or several AIs) that are developed on said blockchain.

As a result of all this dynamic, there are data marts, models and artificial intelligence, which would be available on the blockchain, through Dapps that can process micropayments securely and globally.

Improving the intrinsic security of the same blockchain and AI

The use of AI can enhance the security of the blockchain, especially if it has the ability to smart contracts Turing Complete. Currently, malicious hackers have a huge number of tools to break the security of our applications, including Dapps and their smart contracts. The year 2022 and its more than 400 hacks in the ecosystem are just an introduction to the enormous challenge that is coming in cybersecurity issues within the blockchain ecosystem.

In this sense, AI can help not only to improve the development of our protocols and smart contracts, but also to make them safer and more resistant against attacks and other types of threats that loom over them in the near future.