Last week, when Xiao Li sent the position screenshot, I almost thought he had sent it by mistake. This is the same young man who cried six months ago about being cheated out of 200,000 by an AI stock trading robot. Now, the total value of his FET and AGIX has quadrupled, and he has even paid off half of his mortgage early. His comeback wasn't based on luck; it was all about stepping through the pitfalls of AI and cryptocurrency to seize the tail of 'real technology.'
In the cryptocurrency world of 2025, 'AI' has become the hottest traffic password: social media is filled with 'AI quantitative passive income' and 'AI coin selection tools.' New coins can surge 50% just by having an 'AI' label at launch. But the truth is that 90% of 'AI + cryptocurrency' is just a guise for scams. Either they are fake robots like the one Xiao Li encountered, charging an annual fee of 2888 yuan while miscalculating basic K-lines, or they are air coins filled with AI terminology in the white paper but haven't updated their actual code in three months.
Xiao Li's painful lesson is particularly typical: at the end of 2024, he was deceived by an 'AI stock recommendation' live stream, spending 20,000 to buy a so-called 'smart trading robot', which claimed it could automatically capture the launch signals of AI concept coins. As soon as he connected the funds, the robot bought an unnamed new coin with all his funds, and a week later, the project team ran away with the money, and the robot displayed a 'system maintenance' message, becoming inaccessible. Later, the police reported that the 'intelligent strategy' of such robots was essentially just writing the logic of the scammer's manual coin selection into the program, having nothing to do with AI.
After suffering heavy losses, Xiao Li reorganized his layout according to my method, purchasing FET in March this year and increasing his position in AGIX in June, recovering his previous losses and doubling his investment in just six months. The core reason these two projects can grow is that they have truly landed in the AI + cryptocurrency field. FET's distributed AI network allows ordinary people to rent out idle computing power for tokens, and it has now connected to 300,000 home computers; AGIX has also launched an on-chain AI model trading market, where companies can directly purchase trained AI algorithms with tokens, and this year reached a cooperation with Microsoft's AI cloud services.
Here I share my 'three screening methods' for filtering 'AI + cryptocurrency' real projects, which I have personally tested to avoid all fake AI traps: First, screen for 'real-world applications'; don't believe empty talk about 'disrupting industries', look for projects with specific use cases. For example, FET is for computing power sharing, AGIX is for model trading; projects that can clearly explain 'who makes money' are reliable; those that only say 'using AI to optimize blockchain' but can't specify their service targets should be blacklisted. Second, screen for 'data value'—the core of AI is data, and the core of cryptocurrency projects is on-chain data; the key to combining the two is that 'data can be monetized'. Projects like OCEAN, which support AI model training data on-chain, allow users to upload data to earn tokens, and companies have to pay tokens to use the data; such closed-loop projects are ten times stronger than those that merely shout slogans. Third, screen for 'regulatory compliance'—AI is currently a regulatory focus; those AI cryptocurrency projects that claim 'decentralization without regulation' are likely crossing red lines. Prioritize those cooperating with compliant institutions, like FET which has integrated Amazon Cloud AI services, and AGIX which has passed EU AI ethics review; the safety factor will be much higher.
Simply screening is not enough; the timing for entry is even more important. The practical skills I taught Xiao Li are to 'watch two signals': one is on-chain computing power data; open the browser for AI cryptocurrency projects to see if the connected computing power nodes are continuously increasing. Before FET surged this year, the computing power nodes had increased by over 20% for three consecutive weeks; the second is institutional cooperation announcements. The trigger for AGIX's surge was Microsoft's announcement to use its tokens to purchase on-chain AI data; often before such announcements, there will be large amounts of funds laying out on-chain that can be discovered through address tracking.
Now many people ask me, is AI + cryptocurrency a bubble? I dare say that the bubble of fake AI projects is indeed large, but real projects are just getting started. In 2025, global AI computing power demand is expected to grow by 300% year-on-year; traditional centralized computing power is simply not enough, while the distributed nature of cryptocurrency can precisely solve the problem of dispersed AI computing power, which is a real necessity. The next focus can be on two directions: one is 'AI security', such as GRT, which uses blockchain technology for tracing AI models; now banks are procuring its services for AI risk control systems; the other is 'edge computing AI', such as lightweight AI blockchain applications that can run on mobile phones; these types of projects might become the next hot trend.
To put it frankly: AI + cryptocurrency is not an 'ATM', but rather 'requires the right partners'. Xiao Li was deceived before because he treated AI as a brainless magical tool; later, he made money because he understood the value of the project. If you have coins related to the AI concept, use the 'three screening methods' to check them tonight, and don't get trapped by fake AI.
