Gemini Receives CFTC License for US Prediction Markets

TheNewsCryptoPublicado em 2025-12-11Última atualização em 2025-12-11

Resumo

Gemini, a cryptocurrency exchange, has received a license from the U.S. Commodity Futures Trading Commission (CFTC) for its affiliate, Gemini Titan, to operate a designated contract market. This approval, which concludes a regulatory process initiated in March 2020, allows Gemini to offer event-based prediction markets in the U.S., enabling users to speculate on outcomes in areas like sports and politics. Following the announcement, Gemini's share price surged nearly 14% in after-hours trading. The company views this as a key step in its strategy to build a comprehensive crypto super app and expand its derivatives offerings. Despite the sector's growth and investor confidence, evidenced by platforms like Kalshi securing significant funding, prediction markets face regulatory challenges from some states that view them as unauthorized gambling operations.

Gemini,​‍​‌‍​‍‌​‍​‌‍​‍‌ a cryptocurrency exchange, got the green light from the regulator to introduce prediction markets in the U.S. This is a notable development in the company’s business operations. The Gemini Titan, an affiliate of the company, was granted a license for a designated contract market by the Commodity Futures Trading Commission, which makes it possible for the company to provide the clients with the trading of event-based contracts. After the news was made public, the price of Gemini’s shares went up by almost 14% in the after-hours trading and reached $12.92 per share, while the market was not doing well ​‍​‌‍​‍‌​‍​‌‍​‍‌earlier.

Five-Year Journey Culminates in Market Entry

The​‍​‌‍​‍‌​‍​‌‍​‍‌ approval of the license marks the end of a detailed regulative procedure which, as per Gemini CEO Tyler Winklevoss, had started in March 2020. American users will be able to purchase event contracts via Gemini’s online platform, thus they will be able to speculate on various outcomes such as sports and political events. Besides that, the exchange is willing to expand its derivatives portfolio by adding crypto futures, options, and perpetual contracts for U.S. traders.

Gemini President Cameron Winklevoss was upbeat about the industry’s potential, indicating that prediction markets might become as large, or even larger, than traditional capital markets. The optimistic outlook of the sector comes as a result of platforms like Polymarket and Kalshi experiencing record-breaking trading volumes in November, thus indicating the increasing consumer interest in event-based wagering.

Kalshi recently secured a massive $1 billion funding round, thus reaching an $11 billion valuation and thereby demonstrating investor confidence in the prediction market sector. ​‍​‌‍​‍‌​‍​‌‍​‍‌

Regardless,​‍​‌‍​‍‌​‍​‌‍​‍‌ the sector encounters some problems related to regulations as several state authorities have escalated enforcement actions against CFTC-regulated platforms that are accused of running unauthorized sports betting operations. Those opposing the idea say that these platforms are just gambling services, and this raises questions regarding the protection of consumers and regulatory supervision of the new market segment.

The Gemini prediction markets proposal is to be seen as part the overall strategy of the company to build a comprehensive crypto super app with various financial products. The crypto company founded by billionaire twins Tyler and Cameron Winklevoss, the firm is a potential competitor to other crypto platforms which are gradually becoming more than just trading services. Recently, Trust Wallet unveiled its prediction markets feature, and Coinbase seems to be working on a similar platform in collaboration with ​‍​‌‍​‍‌​‍​‌‍​‍‌Kalshi.

Highlighted Crypto News Today:

Real Finance Secures $29M to Accelerate Global RWA Tokenization

TagsCFTCGemini

Criptomoedas em alta

ctr
CitreaCTR
wstusdt
wrapped stUSDTWSTUSDT
apr
CapricornAPR
ctx
Cryptex FinanceCTX
audio
AudiusAUDIO
comp
CompoundCOMP
mantra
MantraMANTRA
waxl
AxelarWAXL
bill
Billions NetworkBILL
pyth
PYTH (Pyth)PYTH
rune
THORChainRUNE
brev
BrevisBREV
cake
PancakeSwapCAKE
dos
DAPPOSDOS
jst
JUSTJST

Leituras Relacionadas

Two Funding Rounds in Three Months: The Chinese Version of Palantir is on Fire

Investment Community AI has learned that Beijing Zhongshu Ruizhi Technology Co., Ltd., a domestic industrial-grade causal intelligence and high-reliability decision-making AI company, has recently completed a strategic financing round worth hundreds of millions of RMB. This round saw participation from China Internet Investment Fund, Suzhou Chuangtou National Social Security Fund, Financial Street Capital, ICBC Capital, Kunlun Capital, among others, with existing shareholders also increasing their investment. This follows a Series B funding round in the hundreds of millions completed just three months prior. The rapid succession of two major funding rounds signifies strong market recognition of the company's underlying original technology and scaled commercial implementation. Often referred to as the "Chinese version of Palantir," Zhongshu Ruizhi is entering a new phase of accelerated technological iteration, widespread scenario replication, and scaled performance release, mirroring the explosive growth of China's AI market. Founded in April 2020 by Dr. Han Han, a Tsinghua University Ph.D. and former core drafter of national AI policies, the company is mission-driven to "move AI from the digital world to the physical world." It focuses on the high-reliability, strong-decision industrial AI track and enterprise-grade AI Agent full-stack infrastructure. The team tackles the challenge of applying AI to China's vast and complex industrial and energy systems by developing a new intelligent operating system from scratch. Its core technological breakthrough lies in three proprietary底层 technologies: meta-causal cognitive theory, causal models, and a dynamic ontology engine. These address critical pain points of generative large models in industrial settings—such as AI hallucinations, insufficient reasoning, lack of temporal logic, unverifiable decisions, and multi-source rule conflicts—thereby providing trustworthy, explainable, and executable智能决策 capabilities. Commercially, Zhongshu Ruizhi has achieved scaled deployment, serving over 50 central state-owned enterprises and industrial groups in sectors like power, petroleum, and aerospace, with implementations in more than 800 highly complex production scenarios. The company reported doubled revenue in 2025, demonstrating strong self-sufficiency and a viable business model—a rarity among new-generation AI firms. The latest funds will be allocated towards advancing foundational theoretical research, replicating successful application models to expand market presence (including overseas), and attracting top-tier talent. Lead investor China Internet Investment Fund highlighted that in the current shift from general AI capability contests to deep industrial empowerment, industrial-grade causal intelligence is crucial for building China's modern digital foundation and fostering new quality productive forces. They expressed support for the company's efforts to define decision-making paradigms and trustworthy standards for industrial intelligence, aiming to secure a rule-making voice in the global physical AI arena.

marsbitHá 9m

Two Funding Rounds in Three Months: The Chinese Version of Palantir is on Fire

marsbitHá 9m

The Biggest Political Economy Question in the AI Era: As Robots Become More Capable, How Do Humans Share the Value?

In the AI era, the most pressing political economy question is: as machines become increasingly capable, how can humanity share in the value they create? An article originally critiquing China's tech focus has sparked a deeper debate on this global challenge. Historically, industrial progress improved efficiency but still relied on human labor for wealth creation and distribution. AI is fundamentally different—it is now replacing cognitive and knowledge work. As AI and robots take over more tasks, economic growth may continue while direct human participation in value creation shrinks, creating a core tension between productivity gains and widespread income generation. The issue is not unique to China. While leading tech companies amass enormous wealth, labor's share of income is declining globally. The core problem is a broken link: technological innovation and corporate profits are not translating into sufficient consumer income and demand. Three potential paths forward are outlined: a traditional capitalist model where profits primarily go to capital owners; a state-capitalist approach with public investment in AI; and more innovative models like digital sovereign wealth funds, universal shareholding, or AI-era basic income schemes to directly distribute AI-generated value. The future competitive advantage may lie not just in technological supremacy, but in which society can build a new, inclusive distribution system for the intelligent economy. The ultimate challenge is ensuring that as AI creates value, humans have a means to obtain income and share in the resulting widespread social benefits.

marsbitHá 19m

The Biggest Political Economy Question in the AI Era: As Robots Become More Capable, How Do Humans Share the Value?

marsbitHá 19m

Generating Profits for Seven Consecutive Quarters, Emerging Markets Carry Trade Outperforms Everything

For the seventh consecutive quarter, dollar-funded emerging market carry trades have delivered positive returns, marking the longest winning streak since 2008. According to Bloomberg's index, this strategy has gained approximately 22% since late 2024, outperforming U.S. Treasuries, emerging market sovereign, and corporate dollar debt. The core of the trade involves borrowing low-interest currencies like the U.S. dollar, euro, or yen to invest in high-yielding emerging market assets, such as Turkish lira bonds offering over 40% returns. Returns were amplified by favorable currency moves, with the dollar weakening against most emerging market currencies and other traditional funding currencies. For instance, the trade gained 48% on the Colombian peso in the past year. A key test came in August 2024 with a historic joint U.S.-Japan currency intervention, which caused only a modest 1% dip in the carry trade risk premium as investors shifted funding from the yen to the euro and Swiss franc. Looking ahead, the primary risk is the timing of Federal Reserve policy changes. While persistent inflation allows the Fed to hold rates, a rapid rise in long-term U.S. yields could threaten the trade. Another concern is crowding, as massive inflows increase vulnerability to a sudden reversal. High interest rates in regions like Latin America and Eastern Europe, supported by external factors like Middle East tensions and energy prices, continue to sustain the opportunity. Major investors remain engaged, favoring currencies like the Mexican peso, South African rand, and Turkish lira.

marsbitHá 34m

Generating Profits for Seven Consecutive Quarters, Emerging Markets Carry Trade Outperforms Everything

marsbitHá 34m

Tsinghua and Whiton Mentor-Disciple Team Cracks 40-Year-Old Mystery, Core Math All Written by GPT, Anyone Could Do It

Tsinghua and Wharton researchers have used GPT-5.6 Sol Pro to solve a 40-year-old open problem in optimization theory, proving a fundamental limit for gradient descent. They demonstrated that by adjusting only the step size sequence—without adding momentum or changing the algorithm's structure—the convergence rate of gradient descent cannot exceed Ω(T^{-1.9319}). This establishes a mathematical ceiling, showing that structural modifications are necessary to achieve the fastest possible convergence rates like O(1/T²). The core proof, involving a geometric construction based on "resisting oracles," was entirely generated through iterative interaction with the AI. The proof was then formally verified using the Lean 4 theorem prover, achieving zero "sorry" or "admit" statements, confirming its logical correctness without human intervention in the non-trivial mathematical steps. This result bridges the gap between the known O(T^{-1.2716}) rate achieved by the "silver stepsize" sequence and the newly proven impossibility bound. The work suggests a new paradigm where researchers can leverage general-purpose AI to explore and formally verify complex theoretical proofs.

marsbitHá 44m

Tsinghua and Whiton Mentor-Disciple Team Cracks 40-Year-Old Mystery, Core Math All Written by GPT, Anyone Could Do It

marsbitHá 44m

Anthropic Admits Fault, Evidence of Secretly Downgrading Claude's Intelligence

Anthropic publicly apologized after users discovered a hidden A/B test in Claude Code (versions 2.1.237+) that seemingly "dumbed down" the model. Developer argofowl found that selecting the "high" reasoning effort was being mapped internally to a value of "10," which previously corresponded to the "low" setting. While Anthropic engineers clarified this was only a change to the numerical mapping scale and assured it did not affect performance based on internal evaluations, the lack of communication about the test sparked widespread user backlash and self-tests on social media. Separately, significant complaints emerged about the flagship Opus 5 model, with users reporting it became "unstable," prone to lazy outputs, factual errors, and repetitive corrections. An Anthropic engineer acknowledged Opus 5's performance instability, calling its resolution a top priority. The incident highlights a growing industry-wide rift between improving benchmark scores and declining user-perceived quality and reliability. It underscores the lack of transparency in continuous model updates, where server-side changes, A/B tests, and configuration adjustments occur without clear user notification, eroding trust as AI models become critical infrastructure.

marsbitHá 44m

Anthropic Admits Fault, Evidence of Secretly Downgrading Claude's Intelligence

marsbitHá 44m

Trading

Spot

Artigos em Destaque

Como comprar US

Bem-vindo à HTX.com!Tornámos a compra de Talus Network (US) simples e conveniente.Segue o nosso guia passo a passo para iniciar a tua jornada no mundo das criptos.Passo 1: cria a tua conta HTXUtiliza o teu e-mail ou número de telefone para te inscreveres numa conta gratuita na HTX.Desfruta de um processo de inscrição sem complicações e desbloqueia todas as funcionalidades.Obter a minha contaPasso 2: vai para Comprar Cripto e escolhe o teu método de pagamentoCartão de crédito/débito: usa o teu visa ou mastercard para comprar Talus Network (US) instantaneamente.Saldo: usa os fundos da tua conta HTX para transacionar sem problemas.Terceiros: adicionamos métodos de pagamento populares, como Google Pay e Apple Pay, para aumentar a conveniência.P2P: transaciona diretamente com outros utilizadores na HTX.Mercado de balcão (OTC): oferecemos serviços personalizados e taxas de câmbio competitivas para os traders.Passo 3: armazena teu Talus Network (US)Depois de comprar o teu Talus Network (US), armazena-o na tua conta HTX.Alternativamente, podes enviá-lo para outro lugar através de transferência blockchain ou usá-lo para transacionar outras criptomoedas.Passo 4: transaciona Talus Network (US)Transaciona facilmente Talus Network (US) no mercado à vista da HTX.Acede simplesmente à tua conta, seleciona o teu par de trading, executa as tuas transações e monitoriza em tempo real.Oferecemos uma experiência de fácil utilização tanto para principiantes como para traders experientes.

580 Visualizações TotaisPublicado em {updateTime}Atualizado em 2026.06.02

Como comprar US

Discussões

Bem-vindo à Comunidade HTX. Aqui, pode manter-se informado sobre os mais recentes desenvolvimentos da plataforma e obter acesso a análises profissionais de mercado. As opiniões dos utilizadores sobre o preço de US (US) são apresentadas abaixo.

活动图片

Categorias popularesright-arrow

Etiquetas Popularesright-arrow