The not yet launched $Aif, has already forced us to think about a very interesting question:
"When a coin's narrative, content, and exposure, a large part of it is completed by AI, are we really trusting the project, or are we trusting the algorithm?"
Maybe looking back a few years from now, AIF is just one of many experiments; it might also be the starting point that binds "AI operation" and "token mechanism" together.
The rational approach is: neither to overly deify it, nor to easily mock any attempts. Let time pass for a while, and then use data to answer all the assumptions of this round. #Aif
The truly worth recording "progress" is often not the numbers on the account.
This week, I deliberately recorded some less "exciting" things:
There were several times I could have impulsively placed an order but ultimately held back;
There were several times I followed my plan to cut losses and didn’t go for another "bet";
There were several times I wanted to chase the highs but chose to close the software instead.
These moments may seem mundane at the time, they won’t show up in profit screenshots, but in the long run, they might be more important than any short-term profit.
If you’re also practicing to be a bit more rational, it might be worth trying to note these small moments down. #深度思考理性分析
Many people do not lose because of their skills, but because of "role misalignment".
Think about it: If you have to work during the day, take care of children, and handle many trivial matters, yet you keep fantasizing about being a "high-frequency short-term trader", this itself is already a wrong role setting.
Trading does not have only one way to play:
Some people are suited for day trading.
Some people are suited for swing trading.
Some people are suited only for regular investments and asset allocation.
When you choose the wrong role, even the best strategy cannot be used effectively. So sometimes, you need to honestly answer yourself a question: What type of trader am I really suited to be? #深度思考理性分析
"Missing" this course, sooner or later you will have to learn
Most of the experienced traders I know have gone through one thing: Watching a big market move right in front of their eyes, whether they didn't get on board or got off halfway.
In the past, I considered this as "bad luck", now I prefer to see it as a compulsory course:
Accept that you can't have every bite;
Accept that you can only act on the parts you understand;
Accept that some opportunities are just there to tell you "next time be prepared a bit earlier."
Those who can coexist peacefully with "missing", are the ones who will not panic when the next suitable opportunity arises. #深度思考理性分析
Google partners with Reliance Group to seize the Indian AI market
Google's collaboration with India's richest man, Mukesh Ambani's Reliance Industries, packages the $396 AI Pro plan into Jio 5G, offered for free for 18 months. The first batch targets young people aged 18 to 25, with the plan including Gemini 2.5 Pro, the image generation tool Veo 3.1, and 2TB of cloud storage.
India's 450 million active internet users are a battleground for tech giants. Google's move directly confronts Microsoft's OpenAI alliance, which has already rooted itself in India through Azure cloud services. The Indian AI market is expected to reach $170 billion by 2030, growing at 38% annually, second only to the US and China, ranking third globally.
Jio covers 430 million users, paving a highway for Google. The free 18 months is to cultivate user habits, and the conversion rate at the end of the period directly determines success or failure. Meta's WhatsApp AI and Amazon Alexa are also competing for territory in India. Reliance itself is also developing large models, and cooperating with Google is essentially learning while doing; who knows when they might turn against each other. Additionally, India's data localization and privacy regulations are not yet finalized, which could become an invisible barrier. For the crypto circle, Google's cloud infrastructure also supports many blockchain nodes and DApps, and AI tools may be integrated into on-chain data analysis in the future.