To The Moon

【 LIVESTREAM RECAP｜Inside the AI Memory Boom: Opportunities and Challenges for SK hynix】

Hi Tigers! In this session we zoomed in on one of the hottest — and most debated — trades right now: AI memory. From the recent pullback in Korean and US memory stocks, to the core question of "is this a top, or just halftime in a longer bull market," all the way to the HBM supply gap, KOSPI valuations, Korea's macro fundamentals, and how open-source AI models are reshaping memory demand — the flow was layered and packed with substance. Ross doesn't dodge the sharp question of "is the AI thesis broken"; instead he unpacks it piece by piece with data, fund flows and industry cycles.

Full replay 👉 Inside the AI Memory Boom: Opportunities and Challenges for SK hynix

【About the Guest】

Our speaker, Ross Dong @Ross_Macro_Trading,, is a founding partner at Morning Cloud Asset Management, specializing in macro trading and US equities. He spent over 15 years as an equity trader at firms like JP Morgan and KCG, and holds a degree in applied mathematics from Columbia University. Ross is known for spotting secular growth trends early; today he manages over $30M in AUM and leads a community of 15,000+ members. What makes his perspective unique: he blends top-down macro logic with bottom-up stock selection, thinking about both industrial/technological cycles and monetary/financial cycles.

【Highlights】

1. Top or halftime: why Ross sees this as a "short-term top and healthy correction," not the end of the AI bull market.

2. Four signals behind the pullback: from hyperscalers leasing compute, to OpenAI's delayed IPO, to capital flowing out of US tech.

3. The HBM supply gap: why capacity expansion for advanced memory still lags structural AI demand.

Live Recap:

• Live Recap 1: Why the Memory Selloff Is a Buying Opportunity, Not the End of the Cycle

• Live Recap 2: Korea's Macro Backdrop — GDP, Valuations, and Capital Flows Behind the KOSPI Story

• Live Recap 3: Inside the Memory Supercycle — NAND, DRAM, and the AI Compute Shift

• Live Recap 4: SK Hynix in Focus — Q&A Highlights on Timing, Risk, and Embracing AI

【THIS CLIP】

The impact of open-source models may be the most underrated variable in memory demand. 🤖 Ross uses the just-released Kimi K3 as an example — billed as the world's largest open-source model, 2.8 trillion parameters, a 1-million-token context window, and always-on reasoning. He draws a parallel to the DeepSeek R1-driven correction, but goes further with the key point: open-source models tend to be *more* memory-intensive than frontier labs because of longer contexts and always-on reasoning. In other words, the very "efficiency" markets fear could actually lift memory demand — a counterintuitive angle worth a dedicated listen.

We genuinely recommend watching the full replay — many overlooked details (like the rebalancing pace of Korea's NPS, KOSPI's 12-month forward PE dropping to its lowest range in 20 years, and the exact timing of passive ETF inflows) live in the full version. And stay tuned for our upcoming community livestreams — let's keep filling in the gaps and learning together.

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(For education only, not investment advice.)

Full replay 👉 Inside the AI Memory Boom: Opportunities and Challenges for SK hynix