Articles Tagged: softbank

2 articles found

JPMorgan’s $10B ‘National‑Security’ Push: How Big Banks Are Rewiring Capital to Chips, AI and Defense — Market, Deal‑flow and Policy Fallout

JPMorgan Chase has drawn a clear line between national security and capital allocation. In a new decade‑long Security and Resiliency Initiative, the bank plans up to $10 billion in direct investments and to finance or facilitate $1.5 trillion in capital for defense, frontier technologies, energy systems, and advanced manufacturing. The move, 50% larger than its prior plan, formalizes what has become an urgent theme in corporate finance: hardwiring capital to strategic industries amid geopolitical tension, supply chain fragility, and surging AI‑driven infrastructure needs. The timing is not accidental. Washington and Beijing have escalated policy risks around critical inputs, with China tightening rare‑earth export controls and the U.S. threatening new 100% tariffs and fresh export restrictions. Europe, too, has moved from theory to action, with the Dutch government taking control of Chinese‑owned Nexperia to safeguard chip supply and strategic capabilities. In markets, these shocks are colliding with record‑scale AI capex and increasingly interlinked deal structures across chips, software, cloud and data centers. This article examines the scale and scope of JPMorgan’s initiative, why the policy backdrop is accelerating such shifts, where the money is likely to flow, the financing “plumbing” risks in AI and semis, the regulatory spillovers to watch, and the investor playbook under base, upside and downside paths. Real‑time market, rate, and macro data frame the opportunity set and risk contours.

JPMorgannational securityAI infrastructure+17 more

Inside the $100B OpenAI–NVIDIA Pact: Chips, Compute, and the New Economics of Model Building

NVIDIA’s pledge to invest up to $100 billion in OpenAI, tied to a 10-gigawatt buildout of AI supercomputing, is not just another mega-deal—it is the capital markets’ clearest signal yet that compute is the strategic high ground of artificial intelligence. The architecture is unusually explicit: money arrives in $10 billion tranches, capacity arrives in gigawatts, and the first phase targets the second half of 2026 on NVIDIA’s next-generation Vera Rubin systems. OpenAI positions NVIDIA as a preferred, not exclusive, supplier across chips and networking, preserving leverage with other partners while concentrating on the stack that currently defines frontier AI performance. The stakes extend well beyond a bilateral relationship. A 10 GW program equates to roughly 4–5 million GPUs—about NVIDIA’s total expected shipments this year—and it forces hard choices about energy, siting, and financing. The pact reverberated immediately in markets, with NVIDIA shares rallying on the announcement and broader indices hitting fresh highs. Behind the pop is a recalibration of AI’s cost structure: concentrated access to compute becomes a moat, training throughput becomes the new velocity metric, and the economics of inference compress toward power, density, and interconnect performance. This article dissects the capital stack, engineering constraints, chip and cloud implications, and policy risks that will determine whether this bet on scale earns the returns its size implies.

NVIDIAOpenAIVera Rubin+17 more