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Grayscale, the world’s largest crypto asset manager, just dropped a powerful statement: “Tariffs are bullish for Bitcoin.” This isn’t your average crypto hype. Grayscale manages over $50 billion in digital assets, runs the top Bitcoin ETF, and influences institutional strategies worldwide. When they speak — it’s signal, not noise. Grayscale’s Influence on Global Crypto Narratives Grayscale has become the bridge between Wall Street and Bitcoin. They guide: 🔹 Hedge funds 🔹 Venture capital firms 🔹 Sovereign investors Their reports shape long-term crypto adoption — and now they’re calling for a major BTC breakout due to rising geopolitical tension. The Macro Shift: Why Tariffs Matter Grayscale warns that Trump-era tariffs could return — and that’s big news for Bitcoin. Here’s what tariffs trigger: 🔹 Slower global trade 🔹 Economic uncertainty 🔹 Sticky inflation 🔹 Stagflation risks And during stagflation? 🔹 Traditional assets suffer 🔹 Fiat weakens 🔹 Investors seek scarce, independent assets Scarcity Is King — And Bitcoin Is the Throne In Grayscale’s latest note: “Trade tensions and inflation could drive medium-term Bitcoin adoption.” Why? 🔹 The U.S. dollar is weakening 🔹 Trust in fiat systems is fading 🔹 Gold is solid — but Bitcoin is faster, leaner, borderless BTC is becoming the first digital reserve asset — and it’s already on its way to replacing gold in some portfolios. A Familiar Economic Playbook We’ve seen this setup before: 🔹 Weak dollar 🔹 High inflation 🔹 Distrust in central banks Gold used to be the go-to hedge. But now? 🔹 Bitcoin is faster 🔹 More accessible 🔹 With higher upside Infrastructure + Politics = Rocket Fuel Grayscale also points to new U.S. crypto momentum: 🔹 Institutional rails are built 🔹 Spot ETFs are live 🔹 Politicians are pivoting pro-BTC This isn’t 2018. Crypto is now backed by Wall Street-grade infrastructure. Bitcoin: No Longer a Fringe Asset Bitcoin is evolving into a macro hedge used by: 🔹 Nation-states 🔹 Asset managers 🔹 Everyday investors It checks every box: 🔹 Supply-capped 🔹 Censorship-resistant 🔹 Independent of central banks Grayscale’s Final Call: $BTC to $250,000 This isn’t hopium — it’s institutional conviction. Grayscale sees: 🔹 A crumbling fiat system 🔹 A rising alternative 🔹 And a global shift to Bitcoin The price target? $250,000 — and the smart money is already moving.

Amazon CEO Andy Jassy said artificial intelligence infrastructure remains too expensive for widespread enterprise use, but that’s exactly what Amazon Web Services aims to change by developing its own chips and slashing inference costs. Speaking on CNBC’s Squawk Box , Jassy pushed back against speculation that recent advances in artificial intelligence model efficiency, such as those introduced by DeepSeek, would reduce the need for infrastructure buildout. “We have very high demand,” he said. “I don’t see us attenuating our building centers right now.” Jassy emphasized that AWS is experiencing no drop-off in AI infrastructure demand, despite macroeconomic uncertainty and the looming threat of tariffs. He explained that while more efficient models are welcome, the challenges of AI infrastructure are deeper and more persistent. “If you’re building frontier models like we are, you’re working on a lot of the same problems,” Jassy said. “The lower that we can make the cost of AI, the more customers are going to use it.” Jassy drew parallels between today’s AI shift and the early days of AWS. Lower costs per unit of compute, he said, often lead to increased customer spending—not less—as companies find new ways to innovate. “It allows them to save money in what they’re building, but they don’t spend less,” he said. “It unleashes them to do more innovation.” According to Jassy, there are two primary levers for reducing AI costs: the chips themselves and the cost of inference, the process of making predictions using trained models. While training dominates spending today, inference will become the cost center at scale. AWS has responded by building its own custom AI chips, which Jassy says deliver 30% to 40% better price performance than current GPU-based instances. He also noted that reducing inference costs involves advances in hardware and software techniques. Jassy framed the mission clearly: “If you sat in the meetings with the AWS team right now, they feel like it is their responsibility and their mission to make the cost of AI meaningfully less than today.” That push to lower AI costs is a potential catalyst for certain segments in the crypto sector. Notably, developers have long explored AI use cases but often hit a wall due to infrastructure and cost constraints. With more affordable technology to come within years, blockchain -native AI applications, from on-chain analytics to decentralized autonomous agents, could become more feasible at scale.

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