Around July 5, 2026, multiple unrelated yet thematically aligned materials were simultaneously brought to light: on one side was Leto Bao, who became famous for "earning 30 million from trading stocks in ByteDance," publicly reflecting on his investment path at Binance Square, discussing lessons learned from NVIDIA's pullback, how to integrate CPI, non-farm payrolls, and Federal Reserve policies into a framework, and concluding that "ordinary people should allocate AI-related assets early to hedge against the job risks posed by AI"; on the other side, the decentralized prediction market Polymarket launched a new event regarding whether the U.S. government would revoke public access to another major AI model before the end of 2026, with on-chain contracts pricing the probability of this scenario at around 33%, turning regulatory uncertainty into a chip for betting; almost simultaneously, a report leaked from a scam park in Myanmar starkly showcased another reality—local electronic fraud networks have built their infrastructure through Starlink, completed cross-border settlements using cryptocurrency, and invoked OpenAI and Google’s large models to mass-produce scripts and identity disguises, honing AI and cryptography into highly industrialized tools of deception. Individuals discuss how to protect themselves by betting on AI assets, on-chain markets bet on when regulatory measures on AI will tighten, while the black market exploits AI and crypto to tear open global security's soft underbelly, illustrating the contradiction of "being both an asset and a weapon," transforming the narrative surrounding AI from mere technical optimism into a core force reshaping personal risk landscapes and the entire ecological order of cryptocurrency.
From Ignoring Interest Rate Hikes to a 30 Million Comeback: An Individual's AI Bet
For Leto Bao, AI is not just a new term constantly emerging in the news but a watershed moment in reshaping his investment framework. In his reflections, he admitted that during his early bets on NVIDIA, he focused only on the company's performance and industry prospects, having little understanding of the interest rate hike cycle; despite the Federal Reserve signaling tightening continuously, he still increased his holdings based on the intuition that "good companies will always rise," and consequently, NVIDIA's pullback during that interest rate environment left him with a painful financial realization. He did not disclose the exact amount of his losses, but that lesson directly pulled him from a world focused solely on fundamentals into the real battlefield where macroeconomics and market sentiments intertwine.
Looking back on his experience of "earning 30 million from trading stocks in ByteDance," Leto Bao now views that pullback as a necessary cost. Nowadays, when reflecting publicly at Binance Square, he places CPI, non-farm data, and Federal Reserve policies at the forefront of his investment framework, treating earnings seasons as a concentrated reflection of these macro variables on specific companies and industries. On this basis, he added personal strategies suited to the AI era: since ordinary people worry about being replaced by AI, it’s prudent to allocate some funds to AI-related companies or assets early on, as a hedge against future job risks. In his narrative, he emphasizes that this isn't a guaranteed shortcut for anyone to earn 30 million but a proactive choice to transform fears into positions and convert passive risks into manageable variables in uncertain times.
33% Probability of Suppression: On-Chain Betting on AI Regulation Trends
When Leto transforms his anxiety about being replaced by AI into holdings, the market at the other end is doing something similar, though the tools are more directly exposed on-chain. The decentralized prediction market Polymarket enables users to bet with cryptocurrency on various real-world events, turning the debate over "will the U.S. tighten AI regulations"—which could only take place in media and policy reports—into real-time trading price signals.
Recently, Polymarket launched a new betting event: whether the U.S. government will cancel public access to "another major AI model" before the end of 2026. According to a single public page, the current market pricing for this event reflects an occurrence probability of about 33%, though the specific model has not been disclosed. This figure is not based on insider information from any officials or conclusions from think tanks but represents a consensus range formed by participants continually buying and selling contracts on-chain: they believe the risk of a second major AI model being suppressed within the next three years is significant and not negligible. However, the predictive prices should only be seen as an aggregation signal of emotions and expectations, reminding us that the market is concerned about the further tightening of U.S. AI regulation, but it should not be perceived as a definitive timeline or judgment regarding when regulations will be enforced.
Starlink and Cryptocurrency Support: The AI Factory in Scam Parks
If the on-chain prediction market merely writes concerns about regulation into a string of contract prices, then the report leaked from the Myanmar scam park has torn open another side of reality: there, Starlink, cryptocurrency, and large models have been pieced together into a complete black assembly line. Starlink lays the groundwork, connecting previously unstable border parks to a relatively reliable network, creating an invisible "AI factory" atop this coverage.
The so-called "industrialization of AI," as described in the report, is not an abstract concept but specifically pertains to technological replacements at every step of the electronic fraud process: where previously relied on oral traditions passed down by mentors for scripts, it is now entrusted to OpenAI and Google’s large models to generate en masse, adjusting the wording and emotional rhythm in real-time based on the victim's age, occupation, and region; earlier, identities needed to be carefully woven by operators, now are directly generated by models into highly realistic personas, resumes, and chat logs, even maintaining a consistent narrative style for different roles. The forward end uses Starlink to steadily deliver this content globally, while the back end completes cross-border settlements and value retention using cryptocurrency; once funds are induced out of victims' accounts, they quickly get split, mixed, and recombined on-chain, becoming another chip that can be taken at any time. In this gray amalgamation, communication technology, large models, and crypto assets are firmly welded together, no longer mere buzzwords in innovation narratives but rather a set of already operational criminal infrastructure.
The Same AI Double-Edged Sword: Investment, Defense, and Crime
Piecing these threads together paints a clear picture: on one side is Leto Bao reflecting on his path at Binance Square, transitioning from the consequences of ignoring the interest rate cycle leading to significant pullbacks in NVIDIA stock to integrating CPI, non-farm, and Federal Reserve policies into his framework, further using "early investments in AI-related companies or assets" to hedge against job risks posed by AI; in his narrative, AI is a growing engine to buy into ahead of time and a tool for ordinary people trying to save themselves. Almost concurrently, the on-chain Polymarket provided another dimension: wagering cryptocurrency on "whether the U.S. will cancel public access to another major AI model by the end of 2026," with current pricing around 33%, reflecting some participants' expectations and anxieties regarding regulatory tightening, with AI turning into a bargaining chip in a policy game.
In parallel, we find the extreme scenarios described in the report from the Myanmar scam park: the front end uses Starlink to connect to the global network, the back end uses cryptocurrency for cross-border fund settlements, and large models are responsible for generating scripts and disguising identities in bulk—a complete "AI electronic fraud factory" is already operational in reality. When placing these three stories on the same map, the combination of AI and cryptographic technology points in different directions: investment opportunities, defensive strategies, and crime escalation, intertwining originally clear role divisions into a mess: are you buying an asset, participating in a prediction contract, or a tool in some black market chain? As investors, regulators, and scam parks simultaneously mobilize the same technical stack, the boundaries between "what are chips, what are tools, and what are risks" in the crypto world are rapidly blurring; in this context, AI is no longer just a technological trend but is rewriting the asset logic, tool roles, and risk boundaries in the crypto world.
Between Risk and Opportunity, How Should Ordinary People Choose Sides
At this point in time, AI and cryptocurrency are no longer simply questions of "what assets to buy," but on a constantly fluctuating map of situations, the question of which side you stand on. Leto Bao's experience illustrates that early bets on AI sectors or assets can indeed yield considerable returns within a few years, provided that macro variables like CPI, non-farm, and the Federal Reserve's stance are included in the framework; otherwise, amidst interest hikes and reversals in expectations, one may similarly face severe pullbacks. On the chain side, the event on the decentralized prediction market Polymarket regarding whether the U.S. government will tighten access to another major model by the end of 2026 has a pricing probability of about 33% according to a single public source; these contracts essentially bet on policy paths rather than simply being "bullish on AI," and ordinary people must realize that participating essentially means gambling against regulatory psychology. On the darker end, the "industrialization of AI" report from the Myanmar scam park reminds us of the reality that Starlink, large models, and cryptocurrency settlements are integrated into the same fraud assembly line, indicating that regulation and law enforcement have yet to form stable boundaries over this gray area. Choosing sides between risk and opportunity means distinguishing three layers of risk: are you betting on the AI narrative, predicting policy expectations, or unknowingly approaching AI-driven scams? The truly worthwhile variables to continuously monitor moving forward are macro data and the Federal Reserve's rhythms, various AI regulatory signals, and the evolutionary paths of scam organizations exploiting AI and cryptographic technologies.
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