Connecticut can’t take action against Kalshi for now, judge rules

cointelegraphPublicado a 2025-12-10Actualizado a 2025-12-10

Resumen

A US judge has temporarily blocked Connecticut from taking enforcement action against prediction markets platform Kalshi, which received a cease and desist order from the state’s Department of Consumer Protection (DCP) for allegedly conducting unlicensed sports gambling. Kalshi sued the DCP, arguing its event contracts are legal under federal law and fall under the exclusive jurisdiction of the Commodity Futures Trading Commission. The court has paused enforcement while it reviews Kalshi’s motion for a preliminary injunction, with further legal proceedings scheduled through February. Kalshi, a CFTC-regulated platform that saw record trading volume in November, is also engaged in similar legal battles with multiple states, including New York, Massachusetts, New Jersey, Nevada, Maryland, and Ohio, over regulatory jurisdiction and gambling licensing.

A US judge has granted prediction markets platform Kalshi a temporary reprieve from enforcement after the state of Connecticut sent it a cease and desist order last week for allegedly conducting unlicensed gambling.

The Connecticut Department of Consumer Protection (DCP) sent Kalshi, along with Robinhood and Crypto.com, cease and desist orders on Dec. 2, accusing them of “conducting unlicensed online gambling, more specifically sports wagering, in Connecticut through its online sports event contracts.”

Kalshi sued the DCP a day later, arguing its event contracts “are lawful under federal law” and its platform was subject to the Commodity Futures Trading Commission’s “exclusive jurisdiction,” and filed a motion on Friday to temporarily stop the DCP’s action.

An excerpt from Kalshi’s preliminary injunction motion arguing that the DCP’s action violates federal commodities laws. Source: CourtListener

Connecticut federal court judge Vernon Oliver said in an order on Monday that the DCP must “refrain from taking enforcement action against Kalshi” as the court considers the company’s bid to temporarily stop the regulator.

The order adds that the DCP should file a response to the company by Jan. 9 and Kalshi should file further support for its motion by Jan. 30, with oral arguments for the case to be held in mid-February.

Kalshi is in a battle with multiple US states

Kalshi is a federally regulated designated contract maker under the CFTC and, in January, began offering contracts nationally that allow bets on the outcome of events such as sports and politics.

Related: How prediction markets raise insider trading and credit risks

Its platform has become hugely popular this year and saw a record $4.54 billion monthly trading volume in November, attracting billions in investments, with Kalshi closing a $1 billion funding round earlier this month at a valuation of $11 billion.

However, multiple US state regulators have taken issue with Kalshi’s offerings, which have led to the company being embroiled in lawsuits over whether it is subject to state-level gambling laws.

Kalshi sued the New York State Gaming Commission in October after the regulator sent a cease and desist order claiming it offered a platform for sports wagering without a license.

In September, Massachusetts’ state attorney general sued Kalshi in state court, which the company asked to be tossed. So far this year, Kalshi has sued state regulators in New Jersey, Nevada, Maryland and Ohio, accusing each of regulatory overreach.

Magazine: Can Robinhood or Kraken’s tokenized stocks ever be truly decentralized?

Criptos en tendencia

Lecturas Relacionadas

From South Korea to the United States: Blue-Collar Jobs Are Becoming Increasingly Popular, Thanks to AI

AI is reshaping the labor market's value proposition. The traditional four-year college degree is losing its appeal as a guaranteed career path, while skilled blue-collar trades like electricians, welders, and plumbers are experiencing historic demand and wage premiums. This shift is driven by dual pressures: AI's displacement of certain white-collar roles and a booming need for physical infrastructure and data center construction. Data confirms the trend. In the U.S., vocational school revenue surged, and a significant portion of recent layoffs are AI-related. Surveys show a majority of Gen Z adults plan to pursue blue-collar work, citing better job security against AI automation. Vocational education interest has exploded recently. Experts cite a psychological shift as younger generations seek tangible, AI-resistant careers and avoid high student debt. In many cases, salaries for skilled trades now match or exceed those requiring a bachelor's degree. In South Korea, semiconductor vocational high schools boast near-total employment, with graduates securing high-paying roles at companies like Samsung. The shortage is structural, exacerbated by a retiring baby boomer workforce and massive infrastructure projects. Companies like JPMorgan Chase, Meta, and Lowe's are investing heavily in training programs. However, overcoming historical stigma and a "perception gap" around trade careers remains a key challenge to closing the talent gap.

marsbitHace 51 min(s)

From South Korea to the United States: Blue-Collar Jobs Are Becoming Increasingly Popular, Thanks to AI

marsbitHace 51 min(s)

Qualcomm: AI Hype Subsides, When Will Smartphones Emerge from the Gloom?

Qualcomm reported its Q3 FY2026 results (ending June 2026), with revenue of $9.95B, down 4% YoY but above expectations. Gross margin declined to 53.1%, pressured by rising costs across manufacturing and memory. Key business segments showed mixed performance: Handset revenue fell 19.6% YoY to $5.09B, dragged by an 11% decline in non-Apple Android shipments and weaker high-end mix. Conversely, Automotive revenue surged 61% to $1.59B, and IoT grew 9% to $1.83B. Core operating profit dropped 41% YoY due to margin compression and higher expenses. Management's Q4 FY2026 guidance projects revenue of $9.7B-$10.5B, in line with consensus, but Non-GAAP EPS guidance of $2.05-$2.25 fell short of expectations. Amidst persistent weakness in its core handset market, Qualcomm is pursuing growth in AI, focusing on Edge AI (smartphones, PCs, automotive) and Data Center AI. Its data center strategy includes four pillars: AI accelerators (e.g., AI200), commercial CPUs (Dragonfly C1000), custom silicon, and connectivity solutions. While these initiatives initially boosted its stock, concerns over AI capital expenditure sustainability have since erased those gains. The company targets $5B in data center revenue for FY2027 and $15B for FY2029. The report concludes that with the traditional handset business still under pressure, the data center opportunity is currently viewed as a longer-term option, and a more conservative valuation based on core operations may be warranted until AI contributions materialize.

marsbitHace 55 min(s)

Qualcomm: AI Hype Subsides, When Will Smartphones Emerge from the Gloom?

marsbitHace 55 min(s)

From TPU to Self-Evolving Agents: How Jeff Dean Predicts the Next Step in AI

At the 2026 YC Startup School, Jeff Dean outlined his vision for AI's next phase, shifting focus from simply scaling models to building intelligent, autonomous systems. He believes AI's progress is no longer just about creating smarter models, but about integrating them into systems capable of long-term, iterative work, automated experimentation, and continuous learning. This evolution moves the competition from "who has the bigger model" to "who can best organize intelligence." Dean suggests AI capabilities are now comparable to a junior engineer, enabling the automation of complex workflows. However, the true challenge and opportunity lie in managing these AI "workers" at scale. He emphasizes the importance of **context engineering**—structuring tools, memory, and feedback loops—over raw model power. For startups, this means building deep expertise in niche domains where general models currently fail (near 0-1% success rates), leveraging proprietary data, specialized tools, and domain-specific evaluators. A recurring theme is re-examining fundamental constraints. Dean's past work, like moving Google's search index to memory or creating the TPU, stemmed from questioning outdated assumptions about hardware and cost. He sees similar inflection points today, particularly in **specialized inference hardware** to drastically reduce latency and energy consumption for real-time Agent operation. Notably, he points out that in modern AI systems, the dominant cost is often not computation but **data movement**. Reliable, long-running Agents require robust system design, borrowing concepts from distributed computing like checkpointing, state management, and parallel exploration to handle failures and maintain progress over days or weeks. As AI automates execution, the scarcest human skills will shift to **defining clear specifications**, **judging what problems are worth solving** (taste), and designing effective feedback loops. Ultimately, Dean's framework prioritizes understanding the problem deeply, identifying the true bottlenecks, and systematically building closed-loop systems where AI can not only perform tasks but also improve AI itself.

marsbitHace 55 min(s)

From TPU to Self-Evolving Agents: How Jeff Dean Predicts the Next Step in AI

marsbitHace 55 min(s)

Trading

Spot

Artículos destacados

Cómo comprar T

¡Bienvenido a HTX.com! Hemos hecho que comprar Threshold Network Token (T) sea simple y conveniente. Sigue nuestra guía paso a paso para iniciar tu viaje de criptos.Paso 1: crea tu cuenta HTXUtiliza tu correo electrónico o número de teléfono para registrarte y obtener una cuenta gratuita en HTX. Experimenta un proceso de registro sin complicaciones y desbloquea todas las funciones.Obtener mi cuentaPaso 2: ve a Comprar cripto y elige tu método de pagoTarjeta de crédito/débito: usa tu Visa o Mastercard para comprar Threshold Network Token (T) al instante.Saldo: utiliza fondos del saldo de tu cuenta HTX para tradear sin problemas.Terceros: hemos agregado métodos de pago populares como Google Pay y Apple Pay para mejorar la comodidad.P2P: tradear directamente con otros usuarios en HTX.Over-the-Counter (OTC): ofrecemos servicios personalizados y tipos de cambio competitivos para los traders.Paso 3: guarda tu Threshold Network Token (T)Después de comprar tu Threshold Network Token (T), guárdalo en tu cuenta HTX. Alternativamente, puedes enviarlo a otro lugar mediante transferencia blockchain o utilizarlo para tradear otras criptomonedas.Paso 4: tradear Threshold Network Token (T)Tradear fácilmente con Threshold Network Token (T) en HTX's mercado spot. Simplemente accede a tu cuenta, selecciona tu par de trading, ejecuta tus trades y monitorea en tiempo real. Ofrecemos una experiencia fácil de usar tanto para principiantes como para traders experimentados.

743 Vistas totalesPublicado en 2024.12.10Actualizado en 2026.06.02

Cómo comprar T

Discusiones

Bienvenido a la comunidad de HTX. Aquí puedes mantenerte informado sobre los últimos desarrollos de la plataforma y acceder a análisis profesionales del mercado. A continuación se presentan las opiniones de los usuarios sobre el precio de T (T).

活动图片