US Billionaire Backs Stablecoins To Take Over Payment Systems – Details

bitcoinistPublicado em 2026-03-14Última atualização em 2026-03-14

Resumo

American billionaire investor Stanley Druckenmiller predicts stablecoins will become central to the U.S. payment system within the next 10-15 years, citing their efficiency, speed, and cost-effectiveness. While he views blockchain and stablecoins as highly productive innovations, he remains skeptical of regular cryptocurrencies, calling them an unnecessary "solution looking for a problem." His comments follow the recent U.S. regulatory approval for stablecoins, prompting developments from firms like Tether and major financial institutions. Despite his crypto criticism, he acknowledged the potential for a cryptocurrency to challenge the U.S. dollar as the global reserve currency in the next 50 years. Stablecoins currently represent 13% of the $2.42 trillion crypto market.

American billionaire and investor Stanley Druckenmiller has postulated that stablecoins will play a central role in the US payments system in the next decade. However, the philanthropist and former hedge fund manager remains skeptical about regular cryptocurrency.

Stablecoins Drive Productivity, Druckenmiller Says

In a recently released interview with Wall Street Titan Morgan Stanley, Stanley Druckenmiller shared his expert thoughts on several financial and economic subjects.

When asked about the crypto industry, the veteran investor described blockchain and stablecoins as two inventions that are “incredibly useful in terms of productivity”. Druckenmiller boldly claimed that the US payment system would likely run on stablecoins within the next 10-15 years.

Druckenmiller is the former chairman and president of Duquesne Capital, a hedge fund he founded in 1981 and closed in 2010 with an asset under management (AUM) of $12 billion.

The experienced financial professional expects the potential full-scale adoption of stablecoins, stating they are “efficient, quicker, and cheaper.” Notably, these comments come months after US President Donald Trump signed the GENIUS Act into law, thereby establishing a recognized regulatory framework for the issuance and operation of stablecoins.

This regulation has resulted in multiple developments, including Tether, issuer of the USDT stablecoin, to launch a US-focused product, USAT, designed to cater to the needs and peculiarities of the American financial system.

Meanwhile, financial institutions, including JP Morgan, Citigroup, and the Bank of North Dakota, are actively developing a stablecoin product to tap into expected adoption growth. For context, stablecoins are cryptocurrencies whose value is pegged to an underlying asset, most commonly the US dollar.

Crypto Not Needed?

In his general comments on the cryptocurrency industry, Drunckenmiller describes these digital assets as an unnecessary invention. The veteran investor said:

It’s a solution looking for a problem, I am very sad it ever happened as a store or value because it wasn’t needed. But it’s a brand that people love, so it’s going to be a store of value.

Notably, when speaking about the US dollar’s role as the reserve currency of the world, the former hedge fund manager also stated the high potential of a replacement emerging in the next 50 years. While Druckenmiller has no specific picks on the new reserve currency, he has hinted at the potential of it being a cryptocurrency.

At press time, the total crypto market is valued at $2.42 trillion, 13% of which is attributable to stablecoins.

Total stablecoin market dominance at 13.14% | Source: STABLE.C.D chart on Tradingview.com

Perguntas relacionadas

QWhat does Stanley Druckenmiller predict about the role of stablecoins in the US payment system?

AStanley Druckenmiller predicts that the US payment system will likely run on stablecoins within the next 10-15 years, describing them as efficient, quicker, and cheaper.

QWhat is Stanley Druckenmiller's view on regular cryptocurrencies?

AHe is skeptical of regular cryptocurrencies, describing them as an unnecessary invention and 'a solution looking for a problem.'

QWhat recent US legislation has impacted the stablecoin market?

APresident Donald Trump signed the GENIUS Act into law, which established a recognized regulatory framework for the issuance and operation of stablecoins.

QWhich major financial institutions are developing stablecoin products?

AJP Morgan, Citigroup, and the Bank of North Dakota are actively developing stablecoin products to tap into expected adoption growth.

QWhat percentage of the total crypto market is currently attributed to stablecoins?

AStablecoins account for 13% of the total crypto market, which is valued at $2.42 trillion at press time.

Leituras Relacionadas

Silicon Valley 'Startup Guru' Steve Hoffman: Web3 + AI Could Be a Trap

Silicon Valley investor and "Godfather of Startups" Steve Hoffman warns that combining Web3 with AI is likely a trap, not a promising venture. In an interview, Hoffman argues that while AI is a foundational technology touching all industries, Web3 adds complexity, friction, and regulatory risk without solving mainstream consumer or business needs. He advises founders to focus on deep, specialized applications where startups can out-iterate giants, rather than on generic features easily replicated by large tech companies. Hoffman observes that Silicon Valley will lead foundational AI research, while China excels at rapid, large-scale application and commercialization, particularly in robotics. He stresses that AI-driven autonomous agents capable of collaborative, multi-step tasks are 2-4 years away, which will cause significant job displacement. The solution is not to slow AI but to redesign business models around human-AI collaboration and reform social systems like education and retraining. For startups, Hoffman recommends focusing on vertical, expertise-heavy domains to build defensibility. He sees major opportunities in AI fraud detection and cybersecurity. Key founder mindsets include systemic thinking over feature-focus, relentless customer centricity, building adaptive teams, and deeply understanding AI's capabilities and limits. Hoffman is also leading a non-profit initiative to establish university centers aimed at training future leaders in responsible, human-value-aligned AI innovation.

marsbitHá 1h

Silicon Valley 'Startup Guru' Steve Hoffman: Web3 + AI Could Be a Trap

marsbitHá 1h

Token Inefficient, Economy Tokenless

The article "Tokens Aren't Economical, Economics Aren't Tokenized" analyzes a pivotal shift in the AI industry from a technology-driven narrative to one dominated by capital efficiency. It highlights two concurrent trends: a severe capital shortage due to the exorbitant and recurring costs of compute (e.g., OpenAI's high burn rate) and a wave of corporate spin-offs where major tech companies are separating their AI units (like Kuaishou's Kling and Baidu's Kunlunxin). The core argument is that AI's "anti-internet" business model, where user growth increases costs rather than profits, has created a disconnect between high valuations and actual cash flow. Spin-offs address this by allowing AI assets to be valued independently. Within a parent company, they are seen as cost centers, but as standalone entities, they are priced based on their growth potential and scarcity in the primary market, leading to massive valuation premiums (e.g., Kling's estimated value tripling post-spin-off). The industry is at an inflection point, moving from "model worship" to "value realization." The competition is evolving from a pure compute (GPU) race to a broader focus on systemic efficiency and full-stack engineering (involving CPUs and orchestration) to achieve viable commercialization. The year 2026 is framed as a critical moment where the industry must definitively answer how to economically translate AI capability into tangible business value, reshaping the sector's future power structure.

marsbitHá 1h

Token Inefficient, Economy Tokenless

marsbitHá 1h

Crossing the 'Memory Wall': The Wafer-Level Revolution and Computing Power Routes in the AI Inference Era

In 2026, a historic shift occurred in AI as major cloud providers' inference spending surpassed training spending for the first time, signaling a move from "building large models" to "using large models." This shifts the core challenge from computing power to the "memory wall"—the bottleneck of data movement (model weights, activations, KV Cache) between external DRAM and processors, where energy and latency from data transfer far exceed computation itself. Companies like Nvidia face GPU idle time due to bandwidth limits. In contrast, Cerebras Systems adopts a radical "wafer-scale" approach with its Wafer-Scale Engine (WSE). Instead of cutting a silicon wafer into many chips, Cerebras uses almost the entire wafer as one massive chip (WSE-3). This design provides 44GB of on-chip SRAM, delivering memory bandwidth thousands of times higher than traditional HBM (e.g., 21 PB/s vs. Nvidia B200). For LLM inference, weights are streamed layer-by-layer from external MemoryX storage to the chip, avoiding HBM bottlenecks. This results in token generation speeds 1.5–5 times faster than Nvidia's B200 in some models and significant advantages in first-token latency and long-context tasks. Additionally, Cerebras's architecture offers much lower interconnect power consumption (0.15 pJ/bit vs. GPU's ~10 pJ/bit). However, Cerebras faces challenges: SRAM scaling has slowed with advanced nodes, limiting future capacity gains; the chip requires specialized liquid cooling and custom software stacks; and its external I/O bandwidth (150 GB/s) is low compared to NVLink, hindering multi-system scaling for very large models. Competition is intensifying. Major players are pursuing three paths: 1) Developing proprietary inference ASICs (e.g., Google TPU, Microsoft Maia), 2) Leveraging advanced packaging (e.g., TSMC's SoW) to democratize wafer-scale-like integration, potentially eroding Cerebras's process advantage within a few years, and 3) Exploring optical interconnects for ultimate bandwidth. Commercially, Cerebras is transitioning from a hardware vendor to a service provider, facing the immense challenge of building high-power, specialized data centers to meet large contracts (e.g., 250MW/year from 2026–2028). In conclusion, the AI inference era presents a fundamental architectural trade-off. Cerebras opts for extreme physical optimization for low-latency, single-task performance, while Nvidia prioritizes versatility and massive cluster throughput. The path forward remains uncertain, with technology and business models still evolving in the race toward advanced AI.

marsbitHá 1h

Crossing the 'Memory Wall': The Wafer-Level Revolution and Computing Power Routes in the AI Inference Era

marsbitHá 1h

Has Bitcoin's 'Rebound Ended', Officially Entering the Late Bear Market Phase?

**Title: Has Bitcoin's Rebound Ended, Entering the Late Bear Market Phase?** **Summary:** Bitcoin's price has declined by 13% this week, signaling a potential return to late-stage bear market conditions. The price fell to around $67k, positioned between the Realized Price and Realized Cap Weighted Average. For the first time since early 2022, the Short-Term Holder cost basis has dropped below this key average, confirming a hallmark of late-cycle bear markets. Profitability metrics have collapsed sharply. The 7-day average of the Realized Profit/Loss ratio plummeted from a local high of 3.16 to 0.29, mirroring the February panic sell-off. Critically, the 90-day average never breached the threshold of 2, indicating the recent rally to $82k was a bear market bounce, not a structural shift. Realized losses surged to $1.35 billion daily, with $770 million coming from Long-Term Holders selling at a loss. This accelerating redistribution of supply from weak to strong hands is a necessary but ongoing process for a market bottom. The rally stalled almost precisely at the aggregate cost basis (~$83k) of US spot Bitcoin ETF investors, turning that level into strong resistance and leaving the average ETF holder underwater again. Spot market flows have turned decisively negative, showing sellers are dominating order books despite the price drop. While a significant futures long liquidation event cleared over $400 million in leverage, providing a potential reset, sustained spot demand is yet to materialize. Options markets continue to price in higher future volatility (Implied Volatility) than recent price action (Realized Volatility) has shown, with a persistent skew towards put options, indicating ongoing demand for downside protection. In conclusion, multiple metrics point to a fragile market structure. Resistance at the ETF cost basis, accelerating realized losses, dominant spot selling, and cautious options pricing all suggest the bear market trend persists. A sustainable recovery likely requires a resurgence of spot demand, ETF holders returning to profit, and a clear reduction in selling pressure.

marsbitHá 1h

Has Bitcoin's 'Rebound Ended', Officially Entering the Late Bear Market Phase?

marsbitHá 1h

TechFlow Intelligence Agency: Anthropic Calls for Global Pause in AI Development While Preparing for Trillion-Dollar IPO; SpaceX IPO Roadshow Heats Up, But S&P 500 Rejects Fast-Track Inclusion

In today's TechFlow Intelligence Briefing, several major tech stories highlight a growing theme of trust and credibility gaps across AI, crypto, and finance. AI company Anthropic has publicly called for a global pause in AI development, citing risks from Claude's "recursive self-improvement." Ironically, this coincides with reports the company is preparing for a massive IPO targeting a near $1 trillion valuation. This perceived hypocrisy, coupled with widespread user complaints about Claude's declining performance, is sparking debate over whether the safety warning is genuine or a competitive tactic. Meanwhile, in a substantive security move, Anthropic open-sourced a framework for AI-powered vulnerability discovery. In the crypto market, Bitcoin's price drop below $61,000 triggered over $1.16 billion in liquidations, flipping the market into a state where more BTC is held at a loss than at a profit, a historical bearish signal. On the corporate front, SpaceX's highly anticipated IPO is generating immense Wall Street excitement, with Goldman Sachs projecting 100x revenue growth by 2030. However, the S&P 500 has refused to fast-track the company's inclusion post-IPO, potentially limiting immediate institutional demand. Separately, ByteDance's AI app Doubao lost over 6 million monthly active users after introducing a subscription model, highlighting the challenges of AI monetization. Other notable developments include Nvidia certifying HBM4 memory from Samsung, SK Hynix, and Micron; Cloudflare's acquisition of front-end tooling company VoidZero; and its CEO warning that bot traffic now exceeds human traffic online. The underlying narrative connects these events: a trust crisis. From AI firms' contradictory actions and crypto volatility to the clash between SpaceX's hyped narrative and institutional rules, a pattern is emerging where stated intentions and actual practices are increasingly misaligned.

marsbitHá 1h

TechFlow Intelligence Agency: Anthropic Calls for Global Pause in AI Development While Preparing for Trillion-Dollar IPO; SpaceX IPO Roadshow Heats Up, But S&P 500 Rejects Fast-Track Inclusion

marsbitHá 1h

Trading

Spot
Futuros
活动图片

Categorias popularesright-arrow

Etiquetas Popularesright-arrow