Samsung's HBM4 partnership with Nvidia could be the comeback story of this AI cycle. After SK Hynix dominated HBM3E by getting to market first, Samsung has a window with HBM4 to reset the competitive landscape if they can avoid the yield issues that plagued their earlier generations. The 2026 timing aligns perfectly with Nvidia's next gen Rubin platform launch. This partnership would give Samsung strategic leverage beyond just being a supplier, potentially shaping how memory architecture evolves for futue AI workloads.
AMD's multi-year OpenAI chip deal bringing tens of billions is transformativ for the company's positioning against NVIDIA. What's equally interesting is IBM running quantum error-correction on off-the-shelf AMD chips, showing AMD's architecture is versatile enough to handle both traditional AI workloads and emerging quantum applications. These two data points together suggest AMD is building a much broader technology moat than people realize. The insatiable compute demand you mention is real, and AMD is finally positioned to capture meaningful share beyond just being the alternative option.
Samsung entering HBM4 discussions with Nvidia is a critical move for them after losing ground to SK Hynix in the HBM3E race. The 2026 timeline for HBM4 gives them a chance to leapfrog competitors if they can nail the manufacturing yields early. High-bandwidth memory is becoming as strategicaly important as the GPUs themselves for AI workloads. If Samsung secures this partnership, it could fundamentally reshape the AI hardware supply chain dynamics.
Samsung's HBM4 partnership with Nvidia could be the comeback story of this AI cycle. After SK Hynix dominated HBM3E by getting to market first, Samsung has a window with HBM4 to reset the competitive landscape if they can avoid the yield issues that plagued their earlier generations. The 2026 timing aligns perfectly with Nvidia's next gen Rubin platform launch. This partnership would give Samsung strategic leverage beyond just being a supplier, potentially shaping how memory architecture evolves for futue AI workloads.
AMD's multi-year OpenAI chip deal bringing tens of billions is transformativ for the company's positioning against NVIDIA. What's equally interesting is IBM running quantum error-correction on off-the-shelf AMD chips, showing AMD's architecture is versatile enough to handle both traditional AI workloads and emerging quantum applications. These two data points together suggest AMD is building a much broader technology moat than people realize. The insatiable compute demand you mention is real, and AMD is finally positioned to capture meaningful share beyond just being the alternative option.
Samsung entering HBM4 discussions with Nvidia is a critical move for them after losing ground to SK Hynix in the HBM3E race. The 2026 timeline for HBM4 gives them a chance to leapfrog competitors if they can nail the manufacturing yields early. High-bandwidth memory is becoming as strategicaly important as the GPUs themselves for AI workloads. If Samsung secures this partnership, it could fundamentally reshape the AI hardware supply chain dynamics.