Crypto ATM operator to expand to Texas, citing friendly regulation

cointelegraphPubblicato 2025-12-15Pubblicato ultima volta 2025-12-15

Introduzione

Bitcoin Bancorp, formerly Bullet Blockchain, plans to deploy up to 200 cryptocurrency ATMs in Texas by Q1 2026 as part of its national expansion. The company cited Texas’s crypto-friendly regulations, modernized money-transmitter laws, and pro-innovation policies as key reasons for the move. Texas, the second-most populous U.S. state, has become a major crypto hub, hosting mining firms like Riot Platforms and Cipher Mining, and recently passed a bill allowing the state to hold Bitcoin as part of its long-term assets. In November, Texas invested $5 million in BlackRock’s spot Bitcoin ETF and plans to invest another $5 million directly in Bitcoin. Other states like Arizona and New Hampshire have passed similar laws but have not yet made significant crypto purchases.

Cryptocurrency ATM operator Bitcoin Bancorp, formerly known as Bullet Blockchain, said it would deploy up to 200 machines in Texas as part of its national expansion strategy.

In a Monday notice, Bitcoin Bancorp said the move into Texas, expected for the first quarter of 2026, is part of a strategy to deploy ATMs nationwide. The company said Texas was “one of the most crypto-forward jurisdictions,” citing the state’s “business-friendly regulation,” “modernized money-transmitter laws” and “pro-innovation policy environment.”

With a population of about 32 million people and the second most populous US state, Texas has grown to become a significant cryptocurrency hub in the country. In addition to ATM operators like Bitcoin Depot and CoinFlip, which have deployed machines, the state is home to several Bitcoin (BTC) miners, including Riot Platforms, Cipher Mining and Bitdeer.

In the last year, Texas lawmakers became the first to pass a strategic Bitcoin reserve bill, allowing the state to hold the cryptocurrency as part of its long-term financial assets. The text of the bill would allow other digital assets to qualify for purchases, signaling that Ether (ETH) could be next in the state’s investment strategy.

Related: Texas cops cut open crypto ATM to recover $25K lost to scam

Texas invests in Bitcoin ETFs amid reserve strategy

Texas Governor Gregg Abbot signed the bill establishing a state-managed fund to hold Bitcoin in June. In November, state officials said that they had purchased $5 million worth of shares in BlackRock’s spot BTC exchange-traded fund, with plans to invest an additional $5 million directly in the cryptocurrency.

Other US states, including Arizona and New Hampshire, have passed similar bills allowing their treasuries to hold digital assets. However, neither appeared to have publicly announced any significant purchases since the laws were passed in 2025.

Magazine: When privacy and AML laws conflict: Crypto projects’ impossible choice

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Huang Renxun Dramatically 'Saves' South Korean Stock Market

In early June, South Korea's stock market experienced a sharp decline, with the KOSPI index dropping over 5% and triggering a trading halt. Amid this volatility, NVIDIA CEO Jensen Huang's visit to Seoul provided a dramatic boost to market sentiment. During his trip, Huang held a dinner meeting with SK Group Chairman Chey Tae-won and SK Hynix CEO Kwak Noh-Jung. He announced that NVIDIA's new Vera CPU would utilize SK Hynix DRAM and confirmed a multi-year technical collaboration between the two companies. This partnership aims to co-develop next-generation memory for NVIDIA's AI infrastructure roadmap, covering products from data center supercomputers to personal AI devices. Huang also publicly commented that AI company stocks were attractively priced. A key announcement was that NVIDIA's upcoming Vera Rubin AI supercomputer systems will use HBM4 memory, with supply qualifications granted to all three major suppliers: SK Hynix, Samsung Electronics, and Micron Technology. Despite this multi-sourcing strategy, Huang warned that the industry-wide chip shortage, affecting everything from wafers to packaging, is expected to persist for several years due to relentless demand from global AI factory construction. The collaboration extends beyond memory supply. SK Hynix will employ NVIDIA's AI platforms and Omniverse digital twin technology to enhance its own semiconductor design, simulation, and manufacturing processes, aiming for more autonomous factory operations. This visit builds upon a prior October 2025 agreement for SK Group to build a large-scale AI data center using over 50,000 NVIDIA GPUs. Huang's itinerary also included meetings with other Korean giants like Hyundai, LG, and Samsung, indicating NVIDIA's broader strategy to deepen ties with South Korea's tech industry.

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Huang Renxun Dramatically 'Saves' South Korean Stock Market

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When Inference Becomes a Scarce Resource, Who Captures the Value?

When Inference Becomes the Scarce Resource, Who Captures the Value? The core AI bottleneck has shifted from model training to inference (runtime execution). While concerns persisted about an "AI compute gap"—initially a $200B, now a $600B problem—the market is now recognizing that the solution and value lie in the inference layer. Nvidia's financial restructuring around "serving tokens" and Cerebras's successful IPO highlight this shift. Inference is a recurring, usage-based cost, estimated to be 10-50x larger than the one-time training market, especially with the rise of agentic AI. The inference stack spans six layers: silicon (e.g., Nvidia), bare metal (e.g., CoreWeave), GPU rental/aggregation, deployment/optimization, model APIs, and end applications. Most companies operate in one layer. However, Hyperbolic uniquely spans three layers (GPU rental, deployment, and model APIs) without owning any hardware. It aggregates fragmented GPU supply from multiple cloud providers into a standardized pool, offering developers the cheapest available compute through intelligent routing. Its multi-cloud aggregation creates a data moat and a flywheel: more supply leads to better pricing data and liquidity, attracting more developers and providers. In contrast, applications like Venice operate at the top of the stack, reselling privacy-wrapped inference but remaining dependent on and constrained by the underlying compute costs they purchase. As inference demand explodes, value accrues not just to consumer applications but increasingly to the aggregation and routing layer that captures their cost of revenue. The coming potential GPU oversupply reinforces this dynamic. While hardware owners may suffer from depreciation, asset-light aggregators like Hyperbolic benefit from price arbitrage, routing workloads to the cheapest available capacity. The ultimate winner in the inference economy may not be the entity with the most GPUs, but the one that can most efficiently discover, aggregate, and route the world's fragmented compute.

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When Inference Becomes a Scarce Resource, Who Captures the Value?

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