The rise of gambling platforms like DraftKings and Polymarket has supercharged a timeless phenomenon: sports stars ruining their careers by placing bets on their own games.
The latest case rocking the world of college sports is instructive. According to reporting from Fox News, Texas Tech star quarterback Brendan Sorsby is seeking an injunction in a Texas district court after the National Collegiate Athletic Association suspended him over hundreds of bets he’s placed throughout his four-year college football career, in direct violation of Association rules.
If granted, the court order would functionally allow Sorsby to play football during his senior year — while his lawsuit against the NCAA works its way through the courts.
Sorsby previously admitted to placing hundreds of bets worth some $90,000 through family members and friends, including on games he himself was playing in while at Indiana University and Texas Tech. He allegedly helped himself to a buffet gambling apps — according to court filings, Sorsby frequented books hosted by FanDuel, Underdog, Prize Picks, and Hard Rock Bet. After the allegations came to light, the young QB went so far as to check himself into gambling rehab for several weeks, CBS Sports reported.
“I want to be clear that I never bet to make money,” Sorsby wrote in his court statement. “Given the money I had and earned from NIL [name, image, and likeness], the total amount of money I made from 2022 to 2025 was not a big deal to me. I never kept track of my betting over time, but I’m pretty sure I lost more than I won.”
His case comes as college-aged men are increasingly losing themselves to gambling on sports betting apps and prediction markets like Polymarket and Kalshi, which are really just betting parlors by another name.
Back in January, the Associated Press reported that federal investigators had closed in on a massive scheme to rig games for bettors by exploiting students playing in the NCAA as well as the Chinese Basketball Association. In Fall of 2025, two separate investigations uncovered at least nine student-athletes who had manipulated their on-court performance to make sure certain bets hit. At the time, the NCAA said it was looking into 30 separate violations allegedly committed by current or former players.
Though the NCAA prohibits student athletes from betting on any game — whether they play in it or not — the culture around college sports is a breeding ground for gambling companies. Sportsbook advertise heavily in NCAA-adjacent spaces, for example, by partnering with broadcast networks like ESPN or even universities themselves.
In a society where college students are inundated with gambling ads — and prediction markets, not lawmakers call the shots — who’s really to blame when fledgling sports stars decide to join in on the fun?
More on sports: Fans Aghast as New York Jets Say They’re Switching to AI
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The financial landscape is undergoing a profound transformation as traditional finance (TradFi) and decentralized finance (DeFi) increasingly intersect, forging a hybrid system that promises to redefine global banking and democratize access to financial services. This convergence is not a theoretical possibility but an unfolding reality that is fundamentally reshaping how individuals and institutions interact with money, investments, and credit.
At the heart of this convergence lies tokenisation, a sophisticated technological innovation that allows real-world assets—ranging from real estate and bonds to private equity—to be digitally represented on blockchain networks. Tokenisation functions as a crucial bridge, linking the rigorous, regulated structures of traditional finance with the agile, decentralized infrastructure of DeFi protocols. This hybridization creates a financial ecosystem operating at internet speeds, characterized by unprecedented inclusivity and efficiency.
The implications for global financial inclusion are particularly striking in regions traditionally marginalized or underserved by conventional banking systems. In many emerging economies, access to basic financial tools remains a significant barrier. Here, DeFi emerges as an essential infrastructure, enabling access where trust in centralized institutions is low and legacy financial systems are insufficient. The remarkable case of a Syrian farmer whose livelihood was revived through a cryptocurrency payment on a plastic card underscores this paradigm shift. Such examples illustrate DeFi’s capacity to circumvent friction and restore economic agency in conflict-ridden or isolated areas.
Beyond facilitating basic financial services, the integration of tokenisation democratizes investment opportunities that were previously the exclusive domain of the ultra-wealthy. Traditional private equity and real estate investments, typically requiring multimillion-dollar commitments, are now accessible to a broad spectrum of investors via tokenized securities. This accessibility is not just reshaping individual portfolios but is recalibrating market dynamics, as trillions of dollars’ worth of assets transition from traditional ledgers onto blockchain platforms, promising liquidity, transparency, and fractional ownership at scale.
The economic magnitude of this shift is staggering. Market forecasts project that tokenised real-world assets will grow exponentially, reaching valuations between $10 trillion and $16 trillion by the decade’s end. This growth trajectory is underpinned not by speculative fervor but by a deliberate and calculated migration of conventional assets into blockchain-based frameworks. The tokenisation of collateral, programmable settlements, and continuous liquidity provision are addressing inefficiencies and frictions that conventional financial infrastructures have long failed to resolve.
For consumers, this convergence transcends abstract technological advancement; it reshapes the everyday experience of money. Younger generations, especially Gen Z, display a palpable preference for digital-first financial services, with a strong reliance on mobile apps and a desire for instantaneous, seamless monetary transactions. This demographic shift exerts profound pressure on financial institutions to evolve beyond legacy systems characterized by delayed processing times, opacity, and high costs. The demand now centers on time compression: enabling money to flow as fluidly and swiftly as data over the internet.
Industry analysts anticipate that the ongoing melding of TradFi and DeFi will proceed in a deliberate, stepwise fashion. The driving force behind this evolution is not mere technological novelty but the profound capacity of programmable finance to dismantle historic barriers. Programmable settlement engines automate complex processes, tokenised collateral increases market efficiency by enabling fractionalized, on-chain asset usage, and always-on liquidity models ensure capital availability that was previously unattainable.
Looking ahead to 2030, the vision is clear: financial transactions that are as instantaneous, continuous, and ubiquitously available as streaming digital content. This offers a paradigmatic shift where money moves with zero latency, effectively operating 24/7/365 without interruption. The trajectory toward this seamless monetary ecosystem reflects a natural adaptation process within the global financial system—one that embraces, standardizes, and integrates new technological infrastructure while preserving the trust and resilience foundational to economic stability.
Far from being a competitive arena, the convergence of TradFi and DeFi is better understood as a cooperative recalibration. Financial institutions, blockchain developers, regulators, and protocol creators are all actively engaged in shaping this new landscape through collaboration and dialogue. As regulations crystallize globally, the old debate over the legitimacy and place of DeFi within the formal financial system has largely been resolved. The contemporary challenge lies in the speed and efficacy with which institutions can incorporate these emergent technologies without compromising security, compliance, or systemic stability.
This transformative journey is extensively documented in The New Intersection of Money: Where DeFi & TradFi Converge, authored by Scarlett Sieber and colleagues at Money20/20, a premier fintech event organizer. Drawing from a wealth of insights across their global platform, the authors illuminate how financial innovation is solving entrenched problems such as settlement inefficiencies, limited liquidity, and accessibility hurdles by integrating cutting-edge digital frameworks with established financial conventions.
In this new era, finance is no longer merely caught between tradition and innovation; it is evolving into an adaptable, programmable ecosystem. The future of money, according to the latest expert analyses, is not looming on the horizon—it is already taking shape. An interconnected system where trust meets technology at scale is clearing the way for global finance’s next chapter, one that promises to be more inclusive, efficient, and aligned with the fast-paced digital age.
The synthesis of traditional and decentralized finance is thus not just a trend—it is a structural reengineering of the monetary landscape, a quiet revolution that is steadily redefining the rules, infrastructure, and accessibility of global finance for generations to come.
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Web References: http://dx.doi.org/10.4324/9781003789543
References: The New Intersection of Money: Where DeFi & TradFi Converge, Scarlett Sieber et al.
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Keywords: Traditional Finance, Decentralized Finance, DeFi, Tokenisation, Blockchain, Financial Inclusion, Programmable Settlement, Digital Assets, Financial Innovation, Tokenised Securities, Market Liquidity, Global Finance
After more than three decades in public and project finance, I have learned that real inflection points in infrastructure development rarely announce themselves loudly. They usually arrive embedded in financing […]
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It turns out not even the people building Tesla’s self-driving tech trust Elon Musk’s extravagant claims about the company’s autonomous vehicles.
New reporting by Reuters interviewed nine former data labelers and a former self-driving engineer about their take on Tesla’s Full Self-Driving mode. The results were overwhelmingly negative, with seven of the data specialists admitting they wouldn’t ride in a Tesla in FSD.
“We have all seen it fail,” one Tesla insider told Reuters. “Definitely don’t trust Elon on this,” the self-driving engineer concurred, referencing Musks’ declaration that the the vehicles are ready for “safe unsupervised” rides.
One erstwhile worker told the publication they wouldn’t ride in a Tesla robotaxi “if you f**king paid me.”
At least five data labelers, whose job was to comb through hours of FSD footage to train the vehicle’s software to avoid past mistakes, told Reuters they routinely saw clips of Teslas driving above the speed limit, an issue which engineers and managers treated like a low-priority compared to edge-case issues.
Those glowing recommendations come amidst concerns that Tesla’s FSD mode may never be truly safe enough for public roads.
In recent months, Tesla operating on FSD move have driven riders into lakes, off bridges, and even into the path of oncoming trains — and those are just the incidents that get media exposure. Given these insiders’ direct access to terabytes’ worth of proprietary FSD footage, we’re inclined to take their word on it.
More on Tesla: Man Drives Cybertruck Into Lake to Test Elon Musk’s “Boat” Claims, and It Went About as Well as You’d Guess
The post Tesla Insiders Admit Self-Driving Is a Complete Disaster appeared first on Futurism.
With inflation out of control amidst a low-fire, low-hire economy, the amount of private debt in the United States is at an all time high. That’s a grim milestone for any country, let alone one as technically rich as the US — and it’s leading to a massive rise in late payments and credit delinquency.
But as more and more lenders come looking for their payments, it’s increasingly AI — rather than humans — doing the collecting.
New reporting by Wired details the rise of AI agents for hounding debtors. As one Seattle man identified as Ben told the publication, autonomous bots are even making erroneous calls on old debts that have already been settled.
During a call regarding a $266 dispute with a past landlord, Ben said he was hounded by Eve, an obviously artificial voice agent sent by the company ProCollect.
“Would you like to resolve it today by card or bank transfer?” the AI agent asked.
Knowing that he had already settled the dispute, Ben poked and prodded, trying to test its limits after it refused to connect him to a human. “I figured it was just going to kick me over to a person when I asked about repayment structure or anything more technical,” he told Wired.
In the end, he got the bot to engage in some quasi-sexual roleplay, where he was “just a little guy” and his debt was a sultry giantess. After a few minutes of this, Ben says he was unceremoniously whisked away to a human, who confirmed the debt had been settled.
As cofounder of AI call center startup Altur Pedro Fernández told Wired, debt collectors are some of his sector’s “best early adopters.” Altur, for example, places over 2.5 million debt calls a month with AI agents.
It’s not surprising they get things wrong, either. Debt collection is based on massive webs of data, spreadsheets which are essentially sold down the line from the original creditors to second-hand buyers, a sloppy and frustrating system at best.
For all their faults, humans are infinitely more reasonable when it comes to resolving discrepancies that turn up in the shuffle. While nobody likes a debt collector, human or otherwise, at least you can argue back to a fleshbag.
More on AI agents: Oops: Bosses Realize Their Companies Have Been Swarmed by Legions of Redundant AI Agents
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Do nothing. Win?
That’s more less Nintendo’s approach to AI, and the market is rewarding the Japanese video game maker for it, in Bloomberg’s analysis.
For the record, Nintendo is not a stellar stock. Investor uncertainty over its cheap Switch 2 pricing, which didn’t budge even as memory costs soared, helped cap off five straight months of decline, the longest loss streak sustained by the company in a decade.
But earlier this week, it showed some signs of life. On Tuesday, shares climbed as much as 6.8 percent in Tokyo for three days in a row, joining a broader rally of Japanese video game stocks, per the reporting.
It’s less a reflection on Nintendo, however, and more on shifting investor attitudes towards AI.
“This is all part of the rotation out of AI tech and into beaten-up names,” Amir Anvarzadeh, Japan equity strategist at Asymmetric Advisors Pte, told Bloomberg. Tuesday’s climb “underline the growing caution about the market — massive gains in AI tech which cannot be sustainable.”
Tomo Kinoshita, global market strategist at Invesco Asset Management Japan, speculated that it was a sign of investors hedging their bets ahead of Nvidia’s quarterly earnings, which were released Wednesday.
“Nvidia often fails to live up to the market’s sky-high expectations, and AI stocks can suffer as a result,” he said. “I expect many investors are temporarily selling AI stocks in preparation, which is driving the rotation.”
That prediction seems to have been vindicated. Despite clinching another record quarter, Nvidia’s numbers were less impressive than investors hoped, sending shares tumbling by a few percent. Its profits literally doubling from the same period a year ago was apparently not enough.
More on finance: SpaceX Stock May Actually Be a Horrendous Investment
The post Nintendo Is Completely Ignoring AI and Doing Fine appeared first on Futurism.
Imagine this scenario: your algorithm has pulled up a background YouTube video, or maybe a podcast. Unbeknownst to you, hackers have embedded inaudible sounds in it, designed to hijack your smart speaker or phone’s AI assistant — meaning the cybercriminals can now access your private photos, bank accounts, or any other personal information you’ve hooked up to your AI system.
It sounds like an also-ran episode of “Black Mirror,” but it’s exactly what researchers have shown is possible in new research being presented this week at the IEEE Symposium on Security and Privacy.
Basically, a team of researchers in China and Singapore found that they can construct “adversarial audio,” completely undetectable to the human ear, that tricks voice AI models into doing things they shouldn’t. Then it’s a breeze to hide it in innocent-sounding audio — a song, a movie, or anything else that unsuspecting targets might play in the background — and lay in wait for users to accidentally compromise their digital lives.
“It takes just half an hour to train this signal, and then, because this signal is context-agnostic, you can use it to attack the target model whenever you want, no matter what the user says,” lead author Meng Chen, a PhD candidate at China’s Zhejiang University, told IEEE Spectrum of the work. “These single-point defenses struggle to resist our attack because we found it’s very hard for these models to distinguish the normal user intent and our adversary attack.”
One catch, at least for now: the technique required the hackers to have access to the full weights of the AI model they’re targeting, meaning they were only able to attack open source models. But because many commercial AI systems are built on open source models, that meant that their exploit was effective against mainstream products by Microsoft and Mistral.
Mistral didn’t respond to IEEE‘s request for comment, but Microsoft issued a statement that should probably give anyone pause before connecting any important information whatsoever to one of the company’s voice AI models.
“We appreciate the researchers’ work to advance understanding of this type of technique,” it read. “This study evaluates model resilience through controlled, direct interactions with the model itself, which helps inform our approach to building model resiliency. In practice, AI models are often integrated into user applications, and we offer developers tools and guidance they can use to implement additional layers of protection that help safeguard users.”
More on AI: Researchers Alarmed by AI That Can Self-Replicate Into Another Machine
The post Hackers Find That Inaudible Sounds Hidden in Podcasts or Random Videos Can Hijack Your AI Voice Chatbot appeared first on Futurism.
The rise of AI is many things: technological, sociological, political, even teleological.
But perhaps above all, it’s financial. When OpenAI released ChatGPT back in late 2022, it quick picked up enormous user traction — and moneymen across the tech industry immediately started scheming about how to cash in from the rush of interest.
The model they coalesced around hinges on gigantic investments in computing infrastructure to power the tech. It’s high risk and high reward: in their telling, the investments will pay off massively as the tech matures to automate huge swathes of the labor market, but some critics fear it’ll never generate enough revenue to justify the incredible spending.
Nobody is more exposed than the Japanese investment company SoftBank, which has poured an eye-watering $60 billion into OpenAI over the past few years.
According to explosive new reporting by Bloomberg, even certain insiders at the company are rattled. Viziers of founder Masayoshi Son have privately questioned what will happen if the Sam Altman-led company can’t pull off its grand promises — and Son’s reaction has apparently been so “brusque,” in the publication’s wording, that they eventually gave up.
What’s clear from the reporting is that Altman has done what he does best: turned Son into a true believer in his vision of computer superintelligence that causes profound shifts for the entire course of civilization.
Habib Imam, a former SoftBank insider who’s now at Menlo Park Capital, told Bloomberg that it’s fundamentally a “bet on a worldview about AGI,” adding that “you can’t hedge a worldview.”
The reality is that Son’s track record is dodgy. He made a series of canny bets during the company’s early history, then bet big on the Chinese retailer Alibaba, netting immense returns. But in recent years, the company is probably best known for Son’s dogged financial support of WeWork, the would-be coworking space startup with an Altman-like charismatic founder named Adam Neuman — and which imploded in spectacular fashion in 2019.
The question essentially comes down to a Rorschach test: is Altman a visionary ushering in a new world order, or is he a con man taking Son — and many other financial luminaries around the world — for a wild ride that’ll soon come crashing back to reality?
No matter how remote the chances, the consequences of the latter scenario could be catastrophic. SoftBank has already sold top assets, including shares in fellow AI company Nvidia, to pay for its OpenAI commitment. And insiders are reportedly jittery about signs that OpenAI is losing ground, with its defectors who jumped ship and started Anthropic now attracting the most buzz in the industry.
For their part, both companies downplayed Bloomberg‘s reporting.
“SoftBank and OpenAI have built a strong strategic partnership grounded in a shared view of where AI is headed and what it will require at global scale,” Softbank told the outlet. OpenAI said the two companies have a “great relationship” and are “among each other’s closest collaborators.”
More on Sam Altman: Sam Altman Faces Nightmare Questions in Cross-Examination
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Longtime Cybertruck watchers might remember a peculiar day back before the brutalist pickup was even released, when Tesla CEO Elon Musk randomly tweeted that the vehicle would function as a rudimentary flotation device.
“It will even float for a while,” he wrote at the time.
It wasn’t a one-off claim. Musk later boasted that the vehicle would be able to “traverse at least 100m [330 feet] of water as a boat.”
“Mostly just need to upgrade cabin door seals,” he claimed, writing at another point that the “Cybertruck will be waterproof enough to serve briefly as a boat, so it can cross rivers, lakes and even seas that aren’t too choppy.”
The Cybertruck finally did make it to market, where it’s suffered a seemingly endless parade of recalls, embarrassing incidents, and dismal sales figures.
Unsurprisingly, all Musk’s bluster about the truck serving as a makeshift schooner turned out to be flimflam. In fact, it quickly emerged that just getting wet in a car wash could brick the thing.
To muddy the waters further, the company ended up adding what it calls “Wade Mode” to the vehicles, which sets the truck’s ride height to the highest level, ostensibly so it can ford creeks and streams.
All that mixed messaging clearly got jumbled for a Texas man, though, who activated Wade Mode and drove his Cybertruck into a lake. Unsurprisingly, things didn’t go well for him.
“Yesterday, [Grapevine Police Department] and [Grapevine Fire Department] were dispatched to Grapevine Lake, where a Tesla Cybertruck was stranded in the water,” police in Grapevine, Texas, wrote on X-formerly-Twitter. “The driver drove into the lake to use the ‘Wade Mode’ feature when the vehicle became disabled.”
Not only is the man’s vehicle swamped — as the cops showed in an amazing attached photo — but he’s in legal trouble as well.
“The passengers abandoned the vehicle and the driver was arrested,” they wrote.
More on the Cybertruck: Cybertruck Recalled to Keep Its Wheels From Flying Off While Driving
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Elon Musk has just pulled back the curtain on the biggest public stock offering in history, and the numbers are ghastly.
SpaceX, which is expected to go public on Nasdaq in June, just released the first round of financial summaries all companies are required to share when they’re about to sell stock to the public for the first time. The documents reveal Musk is targeting a raise of at least $80 billion — for a proposed valuation of $1.75 trillion — which would immediately make the rocket company one of the top 10 most valuable conglomerates in the US, Axios calculated.
With that kind of valuation in mind, one might expect SpaceX to be massively profitable going into its debut — but that’d be dead wrong.
According to the financial statement, the company lost $4.9 billion in 2025, even though it brought in around $18.7 billion in revenue. It’s not like that situation is about to turn around in time for the IPO, either: over the first three months of 2026, SpaceX posted further net losses of $4.3 billion.
As analyst Scott Melker pointed out, SpaceX wants investors to believe the company will someday make 93 times what it currently makes in a year. To understand why that’s absolutely nuts, just peep the numbers from the previous IPO record holder, Saudi Aramco, the state oil company of Saudi Arabia.
Commonly understood to be the most profitable corporation on Earth, Aramco went public in 2019. When it did, investors accepted a valuation about 6 times more than what Aramco made in yearly sales, raising $26 billion for a valuation of $1.7 trillion, as one analyst noted. SpaceX is asking for about 15 times more than that.
“Bro, have you seen inflation lately? Ketamine is expensive!” one stock analyst razzed on X-formerly-Twitter (that platform, by the way, has all but imploded under Musk’s leadership, with revenue down around 59 percent compared to 2021, the year before he took over).
To justify its wild revenue ambitions, SpaceX estimates its total addressable market — the maximum money it could make if everything goes perfectly — at $28.5 trillion. Of that, nearly 80 percent is attributed to the imaginary landscape of “enterprise applications,” which the document describes as a buffet of various Earth-shattering AI tools that have yet to be built, including one agentic AI platform called “Macrohard.”
Put it all together, and the numbers only work if you put your faith in unprecedented earnings from technology that doesn’t even exist, in a market as infinite and uncharted as outer space itself.
More on investments: It Seems a Lot Like Trump Accidentally Invested $1 Million in a Conveyor Belt Sushi Restaurant Thinking It Was an AI Hardware Company
The post SpaceX Stock May Actually Be a Horrendous Investment appeared first on Futurism.
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