AI vs. Crypto: Will It Make a Real Difference?

Giovanni explores whether AI is actually transforming crypto, looking at trading bots, blockchain analytics, and AI assistants. The core tension: crypto was built on decentralization, but today's AI lives in the hands of big tech companies.
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Artificial intelligence and blockchain are two of the most disruptive technology of our generation.
AI tools. Just as of right now, they're not good enough. It's basically like having a bunch of dumb partners who can adhere to very basic commands.
We use AI to organize your portfolio. Those things are fun, but they're not technologically impressive.
Artificial intelligence is really reshaping every sector of the world economy, including the crypto industry. But is it really? In this video, I will cut through the noise and uncover the truth about AI in crypto. I'll be addressing the main areas where AI is supposedly changing the crypto industry. Crypto trading, blockchain analytics, crypto user experience, and finally, some thoughts on the essence of these two technologies. I'm Giovanni, your host, and this is a Cointelegraph report. One of the crypto areas where AI seems to have the most potential is trading. You must have heard of AI trading bots. These are computer programs that leverage AI and machine learning to execute trades in an automated way. These bots can recognize patterns in crypto price movement and help traders in their decision making. Wait a second, you may say trading bots have been around for many years already. So what novelty is AI bringing to the table? Well, trading bots that have existed so far are based on preset rules and algorithms. Basically, they execute trades when certain technical criteria are met. With the advent of large language models such as ChatGPT, AI trading bots are now able to process large amount of historical data which can then be used by traders to make decisions. To understand more about the potential of AI trading bots, we talked to Marcello Mari, CEO of SingularityDAO, a project that is pioneering artificial intelligence in decentralized finance.
So we could, for example, use artificial intelligence machine learning to understand price fluctuation. For example, we can try to predict where major cryptos are going in the next day. We can use natural language processing to understand social sentiments around certain cryptos. We can understand which influences are actually influencing the market and in what way.
Some crypto trading platforms are already using AI powered bots. The world's second largest crypto exchange by trading volume has implemented an AI algorithm that allows users to capture volatility in the crypto markets. Still, while they can be useful tools to enhance traders capabilities, AI trading bots are still not sophisticated enough to replicate human trading. We talked to Eric Crown, a veteran crypto trader who told us about his own personal experience with AI trading bots.
I mean, a bot is not like a superpower. It's not anything that's it's not anything that you can't do yourself. It's basically, it's basically like having a, a bunch of dumb partners who can, who can adhere to very basic commands, but they can't do any like very complicated thinking themselves. I think people want or, or are looking at AI and machine learning to actually actively create a strategy which right now it's, it's, at least in my experience, it's not good enough. You know, there's still going to be a pretty big component of human input into these things.
So that means be wary of any bots that promise to make you rich while you are sleeping. We are not there yet by the way. If you want to know more about AI in crypto trading, check out our latest video where I compete with ChatGPT in an investment challenge. But the potential of artificial intelligence is not just limited to trading. One of AI's core functions is gathering and analyzing a large amount of data in a short period of time. Some say this would be particularly useful in crypto, where a large amount of public data is scattered across thousands of different blockchains. In theory, investors can use the data to predict market trends and make more informed decisions wherever there are data.
We can use artificial intelligence to better understand correlations and patterns. We can see how certain entities are moving cryptos between exchanges, between wallets, between between ecosystems. For example, we can see if a wallet or a liquidity pool has been interacting with a flagged with a flag wallet or a bad apple to understand it and analyze the counterparty risk associated with interacting with that label.
Still, there are serious limitations in terms of the data AI can use. A large amount of market data is generated on chain but kept off chain by centralized crypto exchanges. These entities decide how much of it is publicly available.
Price prediction tools are still very are still fairly inaccurate for a number of reasons. They should be using off chain data, but obviously off chain data produced by exchanges are not easily accessible. And if you train them using on chain data, then the quality and the consistency becomes a real problem to actually make accurate prediction.
So when it comes to blockchain analytics, AI is offering real value by processing data quickly and efficiently. Still, the problem is the quality of the data the AI is using, which is not always up to the task. Another way AI can provide value to the crypto industry is by improving the user experience. In the last few months, crypto exchanges have been integrating AI tools into their platforms as part of their customer support. For example, in May, crypto.com has launched its own AI assistant called Amy, which provides users with market updates and other real time information. By leveraging ChatGPT, this function of AI can be applied to crypto education as well. Binance has integrated ChatGPT into its Web3 Academy earlier this year. This tool uses machine learning to elaborate answers using the information available on Binance Academy. So all these tools are definitely improving user experience on crypto platforms. However, they can be hardly called revolutionary. Tristan Greene, a writer at Cointelegraph focused on AI, told us why I'm not.
Seeing anything out there other than just ChatGPT and some of the ChatGPT style plugins that I think is revolutionary today. I mean, obviously if you're going to run any type of interface on the Internet, I don't care what you're selling. If you're selling cars or you're selling NFTs, you got to have AI running the site because otherwise you got to have 20 employees answering phone. We use AI to organize your portfolio and ChatGPT told us the top 10 crypto those things are fun, but they're not technologically impressive. They're not going to make any VCs their return back.
So no real breakthroughs when it comes to user experience. But I would say also not much hype either. Finally, a few thoughts on a major obstacle that I think could slow down the integration of AI into crypto. This has to do with the essence of these two technologies. Crypto is about decentralization and democratization of financial services. It's about building Web3, a new Internet where users are fully in control of their own identities and finances. AI, on the other hand, is very much centralized at the moment. Tech giants like Google and Microsoft are developing the most advanced AI models behind closed doors. And we all know what happens when too much power is concentrated in the hands of these big companies.
Do we trust these entities to create such a powerful technology? I think AGI should be open, should be a collaborative effort, should be transparent, potentially even regulated.
In order to be truly compatible with the ethics of crypto, AI needs to be trained on data that is verifiable and transparent, on the blockchain data that is not controlled by single entities. That is why the development of Web3, a decentralized version of the Internet, could have a very positive impact on AI. Let's face it, most of the current integrations of AI into crypto are experimental and there is no killer app yet. Still, there is a lot of potential at the intersections of these two technologies and innovation is happening very fast. So when the dust settles in a few months. I'm excited to see what will be left behind. The hype. That's all for today's video. I'm Giovanni, your host. See you next time.










