This week, S&P Global Ratings released a report on the crossover between AI and cryptocurrencies entitled “The question is not if, but when.” With the launch of ChatGPT about two years ago, the topic of AI has become much more prominent than blockchain and crypto. But the intersection of the two is not new.
Before delving into the report, it’s worth considering some examples of how the two technologies work together. Artificial intelligence requires machine learning, which also requires data. Therefore, some applications use cryptography to compensate the people and devices that generate the data.
Since 2019, German manufacturer Bosch has been working with Fetch.ai to use IoT devices and Fetch’s autonomous economic entity (AEA) ideas. These are sensor-driven (IoT) devices that are self-learning and capable of automatically transacting using cryptography. One can easily imagine a distributed network of weather stations compensated for data. These types of applications are called distributed physical infrastructure networks (DePIN).
Fetch recently signed a deal with GameSwift Launcher. This frees up your computer’s unused graphics card space for AI applications like text-to-speech and music creation. In other words, create a distributed network that runs large-scale language models (LLMs) locally and addresses capacity shortages. Of course, you will be compensated using crypto.
S&P report on the intersection of AI and cryptocurrencies
Let’s go back to the S&P Global Ratings report. This report highlights not only the potential of AI, but also the risks it poses. This includes data traceability, cyber threats, and data center energy consumption.
The report envisions three future scenarios. At the extreme, we see modest progress in both AI and cryptocurrencies. The other end includes a decentralized internet powered by cryptocurrencies and AI. In this scenario, blockchain’s immutability and traceability help with transparency and auditing. It will be possible to understand why AI came up with such crazy ideas. Blockchain can also help distinguish between humans and bots.
Another scenario is the rapid expansion of AI with the risk of centralization, as is currently happening. In other words, the governance of these large vendors is relatively opaque. There are concerns about bias, privacy, and censorship.
This report takes these three scenarios and applies them to a variety of use cases, including cybersecurity, financial markets, and supply chain.
Andrew O’Neill, managing director of digital assets at S&P Global Ratings, said: “Synergies between technologies will support technology growth and reduce the risk of centralization, from supply chain management to smart cities. This should lead to applications that will have a huge impact.” “The speed at which these applications emerge and the pace of their adoption remains uncertain. However, we believe the question is not if adoptions will occur, but when.”
