U.S. stocks and the crypto market have plummeted, and the hardest hit besides memes are AI-related coins. You may hate it, but you can't ignore it. After the crash, AI is still a trend, but you need to understand some things. Which projects will succeed and which will fail depend on analytical skills. The expert Blum gives you three steps to distinguish fake from real AI coins, which are very simple and useful~
Definitely check out this great article!! It can't guarantee you will make money, but it can definitely help you lose less or not lose at all!! You can also share it with your friends who are losing money; they need to see it too~
The first step starts with the simplest question: Does this project really need AI? Is it important in what they are doing?
It sounds straightforward, but this question can help you calm down and look at the big picture. Is AI a core key or just a fashionable decoration? We need to see if AI can truly make things better, faster, and safer, and this improvement must be supported by data. If AI is the indispensable soul of the project, then it needs to drive the main functions and products to make everything smoother!
For example, an AI model trading market on the blockchain where everyone can train and share models while making money; or a decentralized platform that uses AI to monitor on-chain transactions in real-time to catch suspicious activities and prevent hackers and scammers. This sounds credible; AI and blockchain are both essential.
But conversely, some projects claim to be AI-driven but only create a chatbot on a website, which has nothing to do with blockchain and is not useful for the project's success. After clarifying the importance of AI, the next step is to look into the data situation.
The second step is that AI relies entirely on data; data is its lifeblood. We need to figure out where the project's data comes from. Is it reliable? Is the method of obtaining data legitimate? These questions are crucial!!
The project must clearly explain how the data is used and protected because data can be messy. There must be a mechanism to ensure quality, and most importantly, do they mention data in their documentation?
A project that genuinely takes data seriously and works on AI will definitely discuss data, and that's a good sign; you can distinguish quality by looking at the data!
For example, some projects sell pre-installed AI trading bots that sound impressive, but the algorithms are hidden, and they don't disclose what data is used or how; the trading data is also untraceable. Such opaque projects raise questions even if the AI is genuine.
Conversely, a decentralized training platform where AI agents train on-chain, with trading strategies being transparent and auditable to prevent tampering and censorship, is the right way for AI and blockchain to combine. Such projects deserve your attention!
Step three, the project needs to understand whether it requires AI, and the data situation is clear. The next step is to look at the community. If data is the lifeblood of AI, then the community is the lifeblood of the crypto project!
Take a look at how their community is, how the team manages the community, whether their progress is transparent, and do they talk about the pitfalls and failures they encounter? Or is the team keeping everything to themselves, ignoring everyone?
You need to think carefully about these things. Don't get overly excited just because you see the words AI and throw all your money in. Be cautious when selecting projects!
If everyone uses this three-step framework, most people can avoid bad projects, and the crypto market will become more reliable, not just a cash machine for those goods!
We support projects that do practical work and expose those who are just riding the hype! So get moving, stay skeptical, ask hard questions, and dig for real value together.
Everyone can leave a message sharing your tips for distinguishing good from bad projects. Feel free to share~