AI and Crypto, A Perfect Match or a Mismatch?
17 April 2023
As a tech enthusiast and a passionate developer in both industries, I have always been captivated by the potential of cutting-edge technologies to transform industries. In recent years, one technology that has been making waves in the world of cryptocurrency is Artificial Intelligence (AI). The fusion of AI and cryptocurrency has unlocked a plethora of opportunities, but it also has its own set of limitations. It depends on how you interpret AI in crypto: either as crypto powered by AI or AI powered by crypto. In this blog, we will explore the role of AI in crypto, its capabilities and limitations, potential use cases, and investment opportunities.
What is AI?
AI, a field of computer science that focuses on creating intelligent machines capable of performing tasks without human intervention, has been rapidly advancing. With breakthroughs in machine learning, natural language processing, and data analytics, AI has found applications in various industries, including finance. Most recently, LLMs (large language models) such as ChatGPT (formally known as GPT3.5) have taken the world by storm. The cryptocurrency market, with its intricate algorithms, data-driven decision-making, and volatile nature, seems to be a perfect playground for AI.
How is AI Applied in Crypto?
One of the primary roles of AI in the crypto space is data analysis. Cryptocurrency markets generate massive amounts of data, including historical price data, trading volumes, social media sentiment, and on-chain data. Analyzing this data manually would be impractical, if not impossible by a single individual. This is where AI comes into the force. AI algorithms can analyze vast amounts of data in real time, identify patterns, and make predictions based on historical data, technical indicators, and market sentiment. This can assist traders and investors in making informed decisions, managing risks, and optimizing their trading strategies. One example enabling this use-case is The Graph (GRT) by indexation of blockchain data through subgraphs.
Another potential use-case of AI in crypto is fraud detection and security. The anonymous and decentralized nature of cryptocurrencies can attract fraudsters and scammers. AI can be employed to detect suspicious activities, track transactions, and identify potential fraudulent behaviours. For instance, AI algorithms can analyze transaction patterns, identify unusual activities that may indicate money laundering or other illicit activities, and raise alerts. This can help enhance the security and integrity of the cryptocurrency ecosystem and protect investors and users from fraud. This is especially interesting for decentralized applications such as Web3 and DeFi. For example, SingularityNET (AGIX), is a blockchain platform that allows anyone to build, share and monetize AI services for any application, including Web3 apps.
AI's Limitations
The biggest limitation is the major differences in the required infrastructure. AI requires mostly centralized infrastructure as every operation needs to be as fast as possible. AI requires billions if not trillions of calculations per second. This is why a crypto-native AI cannot exist, at least not in crypto’s current state. Cryptocurrency, as we know, is decentralized and primarily optimized for security and public access. This generally means much slower operations than what would be possible on centralized infrastructure. Besides limitations, AI in crypto also comes with risks that are often overlooked. AI is far from perfect, this means that AI could misinterpret data, make wrong decisions based on that data and missing cases of fraud or abuse. We see that complex large models like chatGPT are often confidently wrong, “hallucinate” and come up with sources that don’t exist. This presents a massive risk to users, especially when used in a financial setting like crypto.
The significance of the AI narrative in crypto is in my opinion heavily overestimated. In the past months, a handful of projects doing something with AI have skyrocketed due to the explosion of growth ignited by ChatGPT. Opportunities for AI that I am currently looking at are, for example, distributed ownership of AI models, multi-party computations to decentralize the execution of AI models and token incentive models to utilize users’ processing power to enable AI.
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