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Prediction markets thrive in gambling’s legal gray areas

admin — Fri, 26 Dec 2025 04:54:12 +0000

Prediction markets are the latest in a long line of examples of how gambling innovation takes root in the gray areas.

Major prediction markets are embroiled in lawsuits across the country, with some states like Arizona banning some operators altogether. State governments argue that the services are sidestepping necessary gambling licensing laws, while prediction markets maintain they shouldn’t be subject to state-level regulation.

While there are some ways that prediction markets mimic traditional gambling, especially sportsbooks, there are also clearly ways that they are innovating. Traditional gambling operators wouldn’t offer so many entertainment or political bets – if any at all. Local betting shops don’t offer odds on what a tech CEO is going to say in the next all-hands meeting.

These types of off-the-wall bets are attracting a new crowd who wouldn’t typically be betting. Speaking to Sigma, CEO and founder of Yield Sec Ismail Vali noted that those under 30 are the most responsive to prediction markets and their current affairs-style event contracts.

“Under-30s don’t think they’re gambling,” he said. “They genuinely believe they’re predicting. Whatever that means, but it’s not gambling when it absolutely is.”

Gambling innovation has a long history of operating in the legal gray areas

Part of the reason why prediction markets have surged in popularity so quickly, and why they’re getting so much pushback now, is because they operate in the legal gray area.

There is virtually no specific regulation for what prediction markets can offer event contracts on, as they’re currently overseen by the Commodity Futures Trading Commission (CFTC), which treats them as derivatives exchanges. Some market leaders like Kalshi are working proactively with the CFTC to keep up this relationship, rather than move to state-by-state regulation like traditional gambling.

“Prediction markets are a perfect example. They borrow mechanics from futures and options markets, behavioral incentives from gambling, and speech-based framing that resembles polling or forecasting. That hybridity creates regulatory ambiguity, which is where innovation thrives.” – Braden Perry, Kennyhertz Perry, LLC, attorney

Prediction markets may be the current example of gambling innovation springing up just past the line of official regulation, but past examples have included sweepstakes, slot machines, daily fantasy sports games, and a wealth of other once-innovative, now-normalized (and regulated) gambling methods.

“Most gambling laws in the US were written to regulate clearly defined activities: casinos, sportsbooks, lotteries, or regulated derivatives markets,” Braden Perry, a litigation, regulatory, and government investigations attorney with Kennyhertz Perry, LLC, explained to ReadWrite. “Innovation happens when a new product doesn’t fit neatly into any of those boxes.

As Perry goes on to note, this is far from incidental. The developers of prediction markets seemingly skirt regulation to create something new, avoiding being weighed down by regulatory ties.

“Developers tend to design products right up to the edge of existing definitions: avoiding ‘chance’ by emphasizing skill or information, avoiding ‘wagering’ by using contracts or tokens, or avoiding ‘consideration’ through alternative purchase mechanisms,” he stated. “This is not accidental. It’s a direct response to highly prescriptive gambling statutes that leave little room for licensed experimentation.”

Where does regulation need to step in?

Prediction markets are in a lightning-in-a-bottle stage right now. With little specific regulation beyond what applies to derivatives exchanges, the playing field is fairly open for experimentation. That’s both a good thing for consumers in terms of offering a lot of variety, but also exposes both users and third parties to potential risk.

“Regulators are often reactive rather than proactive in this space,” Perry continued. “Agencies typically wait for scale, harm, or public visibility before stepping in, especially when jurisdiction is unclear, such as between gaming regulators, securities regulators, and commodities regulators. That delay effectively becomes a window for experimentation.”

A recent example centers around Coinbase CEO Brian Armstrong, who poked fun at prediction markets in the company’s quarterly earnings call on October 30.

lol this was fun – happened spontaneously when someone on our team dropped a link in the chat https://t.co/tQiV3B9jUj

— Brian Armstrong (@brian_armstrong) October 31, 2025

“I was a little distracted because I was tracking the prediction market about what Coinbase will say on their next earnings call,” Armstrong said in his parting remarks, as reported by Bloomberg. “I just want to add here the words Bitcoin, Ethereum, blockchain, staking, and Web3, to make sure we get those in before the end of the call.”

While naturally just being a lighthearted comment, his comment shows just how easily he could manipulate such event contracts. If Armstrong put money on him saying that string of words, he can then easily fulfil said event contract. Make the words something even more random, raise the odds, and he could make even more off the back of it.

There’s no real regulatory framework to prevent anyone from doing this currently, highlighting how such rules are not just prohibitory but also protective for everyone involved. In time, organizations will need to catch up, whether that’s on a state or federal level.

“Historically, this is how many now-regulated products began: daily fantasy sports, online poker, esports wagering, and even early financial derivatives,” Perry said. “Grey areas aren’t a bug in gambling regulation; they’re a structural feature of how innovation tests outdated legal frameworks.”

Featured image: Midjourney

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Major housing markets in metro areas rebound after COVID-19

admin — Sun, 06 Jul 2025 04:33:17 +0000

Housing inventory in a significant number of major metropolitan areas hit levels higher than they were before the COVID-19 pandemic, according to a new report from Realtor.com.

The real estate marketplace said nearly half of America’s 50 largest metros had real estate markets whose number of active listings as of May had surpassed pre-pandemic levels.

The ten metro areas that had the largest jumps in active inventory from their averages in 2017-2019 all posted double-digit percentage increases, according to Realtor.com.

Eight states had representation among the ten areas that Realtor.com identified as having the “most dramatic improvement in active inventory,” with Texas claiming three spots within the top-five.

Denver, Colorado

According to Realtor.com, nearly half of America’s 50 largest metros had real estate markets with more active listings as of May than they did pre-pandemic. Tricia – stock.adobe.com

Denver was the metro with the largest increase in active housing inventory, with a 100% jump. Kevin Ruck – stock.adobe.com

Denver stood out as the metro with the largest increase in active housing inventory from pre-pandemic levels, seeing a 100% jump, the report said. Realtor.com linked the surge in inventory to factors like increased construction and the time homes remain on the market. The city serves as the capital of the Centennial State.

Austin, Texas

Inventory in Austin was up 69% in May from where it stood before the COVID-19 pandemic. Raymond – stock.adobe.com

Austin is located in Central Texas. Inventory in the metro was up 69% in May from where it stood before the COVID-19 pandemic, according to Realtor.com

Seattle, Washington

According to the U.S. Census Bureau, over 780,000 people live in Seattle. be free – stock.adobe.com

The real estate marketplace pegged Seattle’s change in active inventory at 60.9%. More than 780,000 people call the city home, according to the U.S. Census Bureau.

Dallas-Fort Worth, Texas

Homes in the Dallas-Fort Worth-Arlington area had a median price of $440,000 last month. trongnguyen – stock.adobe.com

Skyline of downtown Dallas, TX on a partly cloudy day.

In the Dallas-Fort Worth area, inventory rose 55.5% from pre-COVID, the report said. Homes in the Dallas-Fort Worth-Arlington area carried a median price of $440,000 in May.

San Antonio, Texas

San Antonio’s active inventory posted a 58.3% jump from pre-pandemic levels, per Realtor.com.

San Antonio’s active inventory experienced a 58.3% jump from pre-pandemic levels. trongnguyen – stock.adobe.com

The metro areas of San Francisco, Nashville, Orlando, Las Vegas and Tuscon rounded out Realtor.com’s top-10 when it came to having notched the “largest gains” in inventory. Their increases compared to before the pandemic ranged from 53.5% for San Francisco to 23% for Tuscon, according to the real estate marketplace.

“In general, we’re seeing strong inventory reboards in metros that have built more in the last 6 years,” Realtor.com Chief Economist Danielle Hale said in a statement. “This milestone underscores both the importance of enabling housing construction and the growing divide in housing conditions across regions, where some markets are rapidly normalizing and others remain stuck in low-supply dynamics.”

The national housing market appears to be moving towards being a “buyer-friendly” one, according to Realtor.com.

The U.S. had over one million homes on the market in May, a level that the U.S. hadn’t climbed above since the winter of 2019, a separate June 5 Realtor.com report found.

In March, the real estate marketplace said the U.S. was contending with a supply gap of about 3.8 million homes.

Supply and affordability have been two major issues that many homebuyers have been dealing with in recent years.

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Chinese AI models are popular globally and are beating U.S. rivals in some areas

admin — Tue, 17 Dec 2024 15:54:14 +0000

China’s attempts to dominate the world of artificial intelligence could be paying off, with industry insiders and technology analysts telling CNBC that Chinese AI models are already hugely popular and are keeping pace with — and even surpassing — those from the U.S. in terms of performance.

AI has become the latest battleground between the U.S. and China, with both sides considering it a strategic technology. Washington continues to restrict China’s access to leading-edge chips designed to help power artificial intelligence amid fears that the technology could threaten U.S. national security.

It’s led China to pursue its own approach to boosting the appeal and performance of its AI models, including relying on open-sourcing technology and developing its own super-fast software and chips.

China is creating popular LLMs

Like some of the leading U.S. firms in the space, Chinese AI firms are developing so-called large language models, or LLMs, which are trained on huge amounts of data and underpin applications such as chatbots.

Unlike OpenAI’s models which power the hugely popular ChatGPT, however, many of these Chinese companies are developing open-source, or open-weight, LLMs which developers can download and build on top of for free and without stringent licensing requirements from the inventor.

On Hugging Face, a repository of LLMs, Chinese LLMs are the most downloaded, according to Tiezhen Wang, a machine learning engineer at the company. Qwen, a family of AI models created by Chinese e-commerce giant Alibaba, is the most popular on Hugging Face, he said.

“Qwen is rapidly gaining popularity due to its outstanding performance on competitive benchmarks,” Wang told CNBC by email.

He added that Qwen has a “highly favorable licensing model” which means it can be used by companies without the need for “extensive legal reviews.”

Qwen comes in various sizes, or parameters, as they’re known in the world of LLMs. Large parameter models are more powerful but have higher computational costs, while smaller ones are cheaper to run.

“Regardless of the size you choose, Qwen is likely to be one of the best-performing models available right now,” Wang added.

DeepSeek, a start-up, also made waves recently with a model called DeepSeek-R1. DeepSeek said last month that its R1 model competes with OpenAI’s o1 — a model designed for reasoning or solving more complex tasks.

These companies claim that their models can compete with other open-source offerings like Meta‘s Llama, as well as closed LLMs such as those from OpenAI, across various functions.

“In the last year, we’ve seen the rise of open source Chinese contributions to AI with really strong performance, low cost to serve and high throughput,” Grace Isford, a partner at Lux Capital, told CNBC by email.

China pushes open source to go global

Open sourcing a technology serves a number of purposes, including driving innovation as more developers have access to it, as well as building a community around a product.

It is not only Chinese firms that have launched open-source LLMs. Facebook parent Meta, as well as European start-up Mistral, also have open-source versions of AI models.

But with the technology industry caught in the crosshairs of the geopolitical battle between Washington and Beijing, open-source LLMs give Chinese firms another advantage: enabling their models to be used globally.

“Chinese companies would like to see their models used outside of China, so this is definitively a way for companies to become global players in the AI space,” Paul Triolo, a partner at global advisory firm DGA Group, told CNBC by email.

While the focus is on AI models right now, there is also debate over what applications will be built on top of them — and who will dominate this global internet landscape going forward.

“If you assume these frontier base AI models are table stakes, it’s about what these models are used for, like accelerating frontier science and engineering technology,” Lux Capital’s Isford said.

Today’s AI models have been compared to operating systems, such as Microsoft’s Windows, Google‘s Android and Apple‘s iOS, with the potential to dominate a market, like these companies do on mobile and PCs.

If true, this makes the stakes for building a dominant LLM higher.

China is focusing on large language models (LLMs) in the artificial intelligence space.

Blackdovfx | Istock | Getty Images

“They [Chinese companies] perceive LLMs as the center of future tech ecosystems,” Xin Sun, senior lecturer in Chinese and East Asian business at King’s College London, told CNBC by email.

“Their future business models will rely on developers joining their ecosystems, developing new applications based on the LLMs, and attracting users and data from which profits can be generated subsequently through various means, including but far beyond directing users to use their cloud services,” Sun added.

Chip restrictions cast doubt over China’s AI future

AI models are trained on vast amounts of data, requiring huge amounts of computing power. Currently, Nvidia is the leading designer of the chips required for this, known as graphics processing units (GPUs).

Most of the leading AI companies are training their systems on Nvidia’s most high-performance chips — but not in China.

Over the past year or so, the U.S. has ramped up export restrictions on advanced semiconductor and chipmaking equipment to China. It means Nvidia‘s leading-edge chips cannot be exported to the country and the company has had to create sanction-compliant semiconductors to export.

Despite, these curbs, however, Chinese firms have still managed to launch advanced AI models.

“Major Chinese technology platforms currently have sufficient access to computing power to continue to improve models. This is because they have stockpiled large numbers of Nvidia GPUs and are also leveraging domestic GPUs from Huawei and other firms,” DGA Group’s Triolo said.

Indeed, Chinese companies have been boosting efforts to create viable alternatives to Nvidia. Huawei has been one of the leading players in pursuit of this goal in China, while firms like Baidu and Alibaba have also been investing in semiconductor design.

“However, the gap in terms of advanced hardware compute will become greater over time, particularly next year as Nvidia rolls out its Blackwell-based systems that are restricted for export to China,” Triolo said.

Lux Capital’s Isford flagged that China has been “systematically investing and growing their whole domestic AI infrastructure stack outside of Nvidia with high-performance AI chips from companies like Baidu.”

“Whether or not Nvidia chips are banned in China will not prevent China from investing and building their own infrastructure to build and train AI models,” she added.

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Amazon sued by DC AG over excluding areas from Prime delivery

admin — Wed, 04 Dec 2024 13:52:16 +0000

Amazon workers deliver packages on Cyber Monday in New York, US, on Monday, Nov. 27, 2023.

Stephanie Keith | Bloomberg | Getty Images

Washington, D.C.’s attorney general sued Amazon on Wednesday, accusing the company of covertly depriving residents in certain ZIP codes in the nation’s capital from access to Prime’s high-speed delivery.

The lawsuit from AG Brian Schwalb alleges that, since 2022, Amazon has “secretly excluded” two “historically underserved” D.C. ZIP codes from its expedited delivery service while charging Prime members living there the full subscription price. Amazon’s Prime membership program costs $139 a year and includes perks like two-day shipping and access to streaming content.

“Amazon is charging tens of thousands of hard-working Ward 7 and 8 residents for an expedited delivery service it promises but does not provide,” Schwalb said in a statement. “While Amazon has every right to make operational changes, it cannot covertly decide that a dollar in one zip code is worth less than a dollar in another.”

In June 2022, Amazon allegedly stopped using its own delivery trucks to shuttle packages in the ZIP codes 20019 and 20020 based on concerns over driver safety, the suit states. In place of its in-house delivery network, the company relied on outside carriers like UPS and the U.S. Postal Service to make deliveries, according to the complaint, which was filed in D.C. Superior Court.

The decision caused residents in those ZIP codes to experience “significantly longer delivery times than their neighbors in other District ZIP codes, despite paying the exact same membership price for Prime,” the lawsuit says.

Data from the AG shows that before Amazon instituted the change, more than 72% of Prime packages in the two ZIP codes were delivered within two days of checkout. That number dropped to as low as 24% following the move, while two-day delivery rates across the district increased to 74%.

Amazon has faced prior complaints of disparities in its Prime program. In 2016, the company said it would expand access to same-day delivery in cities including Atlanta, Chicago, Dallas and Washington, after a Bloomberg investigation found Black residents were “about half as likely” to be eligible for same-day delivery as white residents.

The ZIP codes in Schwalb’s complaint are in areas with large Black populations, according to 2022 Census data based on its American Community Survey.

The Federal Trade Commission also sued Amazon in June 2023, accusing the company of tricking consumers into signing up for Prime and “sabotaging” their attempts to cancel by employing so-called dark patterns, or deceptive design tactics meant to steer users toward a specific choice. Amazon said the complaint was “false on the facts and the law.” The case is set to go to trial in June 2025.

According to Scwalb’s complaint, Amazon never communicated the delivery exclusion to Prime members in the area. When consumers in the affected ZIP codes complained to Amazon about slower delivery speeds, the company said it was due to circumstances outside its control, the suit says.

The lawsuit accuses Amazon of violating the district’s consumer protection laws. It also asks the court to “put an end to Amazon’s deceptive conduct,” as well as for damages and penalties.

To get packages to customers’ doorsteps, Amazon uses a combination of its own contracted delivery companies, usually distinguishable by Amazon-branded cargo vans, as well as carriers like USPS, UPS and FedEx, and a network of gig workers who make deliveries from their own vehicles as part of its Flex program.

Amazon has rapidly expanded its in-house logistics army in recent years as it looks to speed up deliveries from two days to one day or even a few hours. In July, the company said it recorded its “fastest Prime delivery speeds ever” in the first half of the year, delivering more than 5 billion items within a day.

In relying on its own workforce, Amazon has assumed greater control over its delivery operations.

In his complaint, Schwalb cites an internal company policy that says Amazon may choose to exclude certain areas from being served by its in-house delivery network if a driver experiences “violence, intimidation or harassment.” The company relies on UPS or USPS to deliver packages in excluded areas.

WATCH: Amazon bets on consumers shopping while tuning into Black Friday game

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