In fact, before Chinese traders used USDT to buy US stocks, this path had already been taken for 30 years.
Over these 30 years, the way Chinese traders access US stocks has evolved through three generations. I've been thinking lately that breaking down these three historical phases is quite an interesting observation. Phase One (1997-2014): Shanghai-Hong Kong Stock Connect and US Brokers Phase Two (2014-2024): Chinese Brokers and Hong Kong Bank Cards Phase Three (Starting 2025): Stablecoins and Crypto Exchanges, which will surely create a lot of opportunity windows. Phase One (1997-2014): QDII and the Charles Schwab Era, US stocks were a rich person’s game. Initially, regular folks had two ways to buy US stocks: - QDII Funds. To put it simply, these are fund products issued by domestic fund companies that can invest in overseas markets.
Saw Sun Ge retweeting the 8th anniversary of the Tron chain.
Back in the day, TRON had the rep of being a shitcoin, and not many believed it could survive the bear market.
Even now, a lot of folks outside the space still don’t know that Tron was created by Sun Ge.
What really made Tron pop were two key turning points.
The first turning point was March-April 2019, when TRC20-USDT launched.
In March 2019, Tron struck a deal with Tether, and by April, they started issuing USDT on their own chain.
Before that, USDT mainly ran on Ethereum, where transfers took ages and fees weren't cheap. Over on Tron, a block gets churned out every 3 seconds, so sending a dollar takes just a few seconds and costs almost nothing.
Instead of going head-to-head with Ethereum for all those DeFi bells and whistles, they focused on one thing: making dollar transfers fast and cheap.
This demand gradually picked up in emerging markets, cross-border remittances, and OTC trading, snowballing into a core, loyal customer base.
The second turning point: April 2021.
By April 2021, Sun Yuchen tweeted that Tron’s version of USDT hit $23.9 billion, surpassing Ethereum's $23.4 billion for the first time, taking a total of 729 days.
This was Tron’s first time sitting on the throne of stablecoins.
That top spot changed hands a few times, but by May 2025, Tron had surged to $75.7 billion, claiming 50.2% market share again, overtaking Ethereum.
By May 2026, USDT on Tron had already exceeded $90 billion.
After 8 years, that once-labeled shitcoin, the Tron chain, now carries a hefty chunk of the world’s on-chain dollars.
The "Forbes" list of the world's most influential businesswomen has been around for 29 years, and this year, for the first time, a name from the crypto space made the cut: He Yi.
Alongside her is Citi CEO Jane Fraser, among others. One is the head of a century-old Wall Street bank, while the other is a co-founder of a crypto exchange established in 2017.
In the past decade, crypto has been seen as a wild ride. This year, it finally entered the mainstream financial core rankings with a "specific female figure."
I recall a deeply resonant saying from before, There's no limit to what we, as women, can accomplish.
A $160 billion IPO wave is coming, and I've been wondering, will it drain the market? Will the market drop?
June is just around the corner, with SpaceX leading the charge. In 2026, there are nearly 100 companies lined up for IPOs. In total, we’re looking at $160 billion being pulled from the US stock market. I went through a few reports and roughly outlined three answers that could impact the market. 1. Will a mega IPO like SpaceX drain the market's liquidity? Let’s take a look back at the data for heavyweights like META and GM from their IPO days. The S&P 500 typically drops by an average of 1% in the month leading up to a major IPO. But after the IPO, there was a rebound of 5% within a month. The overall trend closely resembles that of high-yield bonds. The so-called 'siphoning' is mainly a reaction to pre-IPO sentiment; it doesn't mean there's actually less money in the market.
Today's fun fact: Binance is one of the top ten shareholders of SpaceX.
Remember back in 2022, when Binance dropped 500 million bucks to get in on Elon Musk's Twitter acquisition?
Yeah, that investment was supposed to buy Twitter, but it ended up as a gift to SpaceX shareholders.
Let me break it down for you. In March 2025, xAI fully merges with Twitter.
So, the original shareholders of X (including Binance) had their stocks swapped for xAI shares based on their ownership ratios. That means Binance's stake in Twitter automatically converted to xAI shares.
Then in February 2026, SpaceX fully merges with xAI.
So the original xAI shareholders, including Binance who got their shares through the Twitter swap, are now passively converted to SpaceX stocks.
Assuming SpaceX goes public at a valuation of 2 trillion bucks, then Binance's initial investment of 500 million has skyrocketed to over 1.5 billion.
They didn’t lift a finger, but they hit the jackpot.
The much-anticipated OPENAI researcher Leopold Aschenbrenner has just revealed the latest AI holdings of the SAF fund.
Let me sum it up in one sentence, Long on power, racks, and storage; Short on logic chip complexes (GPU/ASIC/foundry/lithography).
Buying Put options worth up to 8.46 billion, Actually, I think he’s hedging against an overheated market in Q1 rather than going fully bearish.
His current top 5 holdings this quarter:
1. Fuel Cell Company BE — 879M (but he reduced his position) 2. SanDisk SNDK — 724M 3. CRWV — 556M (increased position) 4. My favorite stock IREN — 401M (he added to it) 5. CORZ — 389M (also reduced)
Newly established stocks. We’re cutting the small long positions. The core new directions are three: 1. TE (local solar, new piece in power generation) 2. SHAZ (AI computing underdog, betting on the second tier) 3. HIVE (mining company getting into AI)
Completely liquidated the three AI side plays, 1. Optical Communication (LITE, COHR) 2. Natural Gas Supply Chain (EQT, LBRT) 3. Secondary mining stocks + secondary OEM (CIFR, HUT, TSEM)
Very interesting, I see this dude even bought Wu Jihan’s Bitdeer.
Looks like he’s really bullish on data centers, and not betting on the execution of a single company.
Microsoft has been fully liquidated by Bill Gates.
The Gates Foundation just disclosed to the SEC that in Q1 this year, they shorted the last 7.7 million shares of Microsoft, totaling around $3.2 billion.
This is the company he founded himself, and now there's not a single trace of his holdings left.
Out of the 8.1 billion people worldwide, 84% have never used AI.
I came across some stats before, showing that only 16% have tried free AI tools, and the paying user ratio is just 0.3%.
So, the level of AI adoption is akin to the early days of smartphones back in 2007.
If you understand prompts, skills, or even just basic chatbot communication, any one of those makes you ahead of the game.
But with AI products popping up left and right, it’s tough to keep pace with all the updates and iterations.
- The newly launched xBubble from dappOS focuses on having AI use AI, AI learning from AI.
It operates on two layers. - The frontend is called Bubble Pilot, essentially AI using AI. For example, if you say "Create a comparison dashboard for BYD vs. Tesla," it recognizes what task that is, digs into its repository for a matching SOP, which is a "Standard Operating Procedure," selects the best model and tool combo, and spits out the result.
If there’s no matching SOP in the repository, it falls back to the general Agent to do it from scratch and logs this attempt.
- The backend is called Bubble Engine. Its core function is AI learning from AI.
It monitors which tasks on the frontend keep falling back, which ones aren’t stable enough, and for those tasks, it has the AI programming the Agent to generate several solutions, testing different model and tool combos to find the highest quality result.
The best solution is solidified into a new SOP added to the repository, and it gets tested again before going live.
The more the Pilot runs, the more the Engine learns, and the thicker the repository gets. It’s a snowball effect.
The biggest difference between xBubble and a general Agent is right here.
The general Agent figures things out on the fly every time, making ten attempts at the same type of task can lead to significant quality fluctuations.
xBubble is more like an "experience-gathering" Agent, using polished SOPs for common tasks, and figuring things out for the novel ones, which get integrated into the repository once they’re refined.
-xBubble has two operating environments.
The cloud-based Bubble Computer runs end-to-end projects, PPTs, research, and comparison web pages all in one go. The local Bubble Personal can access files, browsers, and schedules on your computer but only acts upon your authorization, keeping your system clean.
For instance, that 84% of people who can’t write prompts but can say, "Help me get something done." AI should inherently operate this way.
Here's the deal with the US stock market right now: Everyone's making gains, but no one's really happy.
I talked to a bunch of folks, whether it's missing out on Micron, or getting shaken out of SanDisk because of fear of heights, or just using leverage to snag a little tail end,
everyone's feeling regret, wishing they had done things differently back then.
I've been backtesting Binance's moves in financial infrastructure lately, and there's definitely a lot going on.
- You can top up your domestic phone bill with Binance; - You can cash out fiat directly to your Hong Kong card; - Vietnam's payment system is rolling out, with 90% of local merchants supporting Binance payments. - Cathie Wood herself clarified that 1011 isn’t an issue with Binance.
Individually, each of these points may seem minor, but together they tell an interesting story: Binance is actually switching lanes.
From a "exchange" to aiming for a super financial app.
I’ve been pondering what the big boss said a couple of days ago: Binance's next target is to serve 3 billion users.
3 billion, I did the math. There are about 240 million retail investors in A-shares and 167 million in U.S. stocks, which adds up to roughly 500 million people.
This means the ceiling for being an "exchange" isn’t that high.
But if we look at Alipay, it has 1.4 billion monthly active users.
So the ceiling for a "super financial app" needs a different approach.
Since Binance is targeting 3 billion, what's coming next is likely a "global crypto version of Alipay."
The national team of China is personally stepping in to fund DeepSeek.
Just as Kimi hits a valuation of 20 billion, DeepSeek is rumored to be valued at 45 billion.
And I checked last night, DeepSeek's lead investor isn't any VC, but the national team of China. A state-level fund worth 344 billion RMB, specifically backing Chinese chips.
So from this moment on, DeepSeek is more than just an AI company.
I previously thought Liang Wenfeng would never go for funding.
Because he holds 84% of the shares, The parent company, Huanfang Quantitative, is projected to net 5 billion in 2025, Numerous investors like Wuyuan Capital have tried to pitch him but were turned away, The reason being: different paths don’t make for a partnership.
Now the reason for opening up is probably quite simple. DeepSeek has reached a level where, funding, and the choice of chips, are no longer just Liang Wenfeng's call.
Plus, V4 has been consistently delayed, The reason being a migration from Nvidia to Huawei Ascend, Almost all the underlying code needs to be rewritten; Core researchers have also been poached by Xiaomi and ByteDance; After R1 broke out, the daily active users reached 30 million, and the inference costs are unsustainable. Three issues colliding at once.
OpenAI's backing comes from Microsoft + Nvidia + SoftBank. DeepSeek's ally is the state itself.
After all, the color of money is different, and the paths diverge.
About Predict.fun project and some interesting tidbits
1. A few days ago, I happened to chat with a big NFT whale, Dingaling. Folks new to the crypto scene might not recognize that name.
But back in the NFT era, he was a superstar, among the big shots who ruled the scene, he was a true legend.
2. I attended a small gathering for Predict.fun in Hong Kong. We talked about a couple of interesting details.
Boss Dingaling, I heard ten years ago, was referred to by CZ as 'Binance's number one handsome guy.'
3. I chatted with others about how back in the day, Boss Ding wanted to recruit Teacher Yue Xiaoyu, but fate didn't align. Teacher Yue was already picked up by Probable through a connection.
So by chance, they brought in TC and Ah Huang, one good-looking and one charming, and that's how the team came together.
Later, CZ made the call, and Probable merged with Predict.fun.
Boss Ding kind of hit the jackpot, happily welcoming Teacher Yue.
4. Boss Ding is a very nostalgic guy. The current tech team is said to be made up of his old friends from his earlier ventures. They’ve fought together and are back at it again.
5. Predict.fun is still aiming to be a long-term project. Boss Ding himself isn’t short on cash and has also raised quite a bit. There might be a TGE in the second half of the year.
Of course, the first real test for Predict.fun will be next month's World Cup.
Doubao is starting to charge; the basic plan is 68 bucks a month, and the pro plan is 500 bucks a month.
Honestly, I think it's only a matter of time before Doubao starts charging.
No company is willing to subsidize users indefinitely.
Plus, overseas AI has already started to commercialize, while domestic AI is still offering free membership fees—this can't last.
Of course, there's a ceiling on the consumer-side, so they won't rake in much cash.
The real monetization direction for AI is on the enterprise side. The B2B market, the professional-grade sector, is where the real battle for AI is happening.
I've been chatting with several leading crypto institutions lately,
and their views are surprisingly consistent:
There’s expected to be another bottoming out around September this Q3, with BTC dropping to around 50k. Then it’s all in for the bottom pick, kicking off a wild bull run.
I’ve been discussing with different folks in various settings, originally hoping to hear diverse opinions, but the institutional consensus is strikingly aligned.
However, I feel that the more oddly consistent the expectations are, the more likely we are to see inconsistent outcomes.
What do you all think?
Is it a reverse signal or destined for greatness? Let’s revisit in five months.
It's an honor to sit across from the top trader and have a small chat.
To be honest, the questions from everyone are pretty sharp, and she responds quite candidly.
For instance, regarding the recent pump of RaveDao, Binance hopes to minimize losses for regular users;
And about the Alpha airdrop, the recent "egg drops" are getting fewer and harder to grab; she honestly mentioned that in a bear market, it's tough for project teams to respond, but the Alpha airdrop team is doing their best to keep it going;
Also, on AI and crypto trading, the goal for Binance AI is to promote quantitative equity.
Plus, her signature is a heart, placed in the introduction she wrote.