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ZERO Market Flash #003# China's Second AI Shockwave: Is the Market Misreading It Again? Why Cheaper AI May Mean More Infrastructure—Not Less In January 2025, DeepSeek triggered one of the biggest debates in AI investing. The market quickly concluded that if powerful models could be trained with fewer GPUs, future demand for AI infrastructure must decline. NVIDIA lost nearly 17% in a single day, and AI-related stocks sold off across the board. More than a year later, history appears to be repeating itself. Kimi K3 has once again demonstrated that Chinese companies can build highly competitive large language models at significantly lower cost. The market immediately returned to the same question: If AI keeps getting cheaper, will we need fewer GPUs? Ironically, Kimi itself may have provided the opposite answer. Shortly after launch, the company suspended new subscriptions—not because the model had reached its limits, but because user demand had pushed GPU capacity close to its deployment limit. That may be the most important signal from Kimi's release. The first bottleneck wasn't model capability. It was deployment capacity. For the past several years, AI competition has largely been defined by training. Whoever trained larger models with more GPUs was assumed to have the strongest competitive advantage. Under that framework, lower training costs naturally imply lower infrastructure demand. But that assumption depends on one premise: that AI's value is created primarily during training. The more important question is: What happens if cheaper AI leads to dramatically more adoption? A foundation model may be trained once. It may perform billions of inference requests afterward. Over the long run, infrastructure consumption is driven less by training than by continuous deployment. Lower cost reduces the price of each interaction. Growing adoption increases the number of interactions. If usage grows faster than cost declines, total infrastructure demand can continue to expand. That is why Kimi's GPU capacity announcement may matter more than the model itself. The market focused on lower training costs. Reality exposed growing deployment demand. This also gives new context to SK Group Chairman Chey Tae-won's observation that the memory industry may gradually shift from a Price-driven cycle to a Volume-driven one. If AI deployment continues to expand, future industry growth may depend less on rising prices and more on rising deployment volumes. Kimi's capacity constraints do not prove that transition has already happened. They do suggest that AI competition is beginning to extend beyond training and into deployment. One year ago, DeepSeek forced investors to rethink training costs. Today, Kimi may be forcing investors to rethink deployment demand. Training creates models. Deployment creates industries. — This article reflects personal research and opinions only and should not be considered investment advice. Please conduct your own research before making investment decisions. ZERO Good is not good enough for conviction.
Only the best deserves concentration. Scientist · Doctor · A9 Investor Search Tags #AI# #ArtificialIntelligence# #GenerativeAI# #LLM# #KimiK3# #MoonshotAI# #DeepSeek# #Inference# #Deployment# #Training# #AIAgents# #GPU# #NVIDIA# #Memory# #HBM# #Semiconductors# #AIInfrastructure# #SKHynix# #Micron# #SNDK# #TechInvesting# #ZERO#

zero chance this was lionel messi’s last world cup. he like tom brady (and he probably trains with tom). he’s a crazy person. 39 yo today? yes. but just 43 next WC? yes. doable this is a world pushing the limits, and i bet messi will be back to push those limits again in 4 years

ZERO Market Flash July 16, 2026 Why Korea’s Rate Hike Hit AI Memory First The Bank of Korea raised its benchmark rate by 25 basis points to 2.75% today, its first increase in three and a half years. The decision was not aimed specifically at AI. The central bank cited stronger-than-expected growth, persistent inflation, pressure on the won, and broader financial-stability concerns. South Korea’s semiconductor export and investment boom gave policymakers enough economic strength to tighten. Yet AI memory stocks absorbed the greatest damage. The reason is straightforward: SK hynix and Samsung had become two of the most crowded and leveraged trades in Korea. Single-stock leveraged products tied to those companies expanded rapidly in Korea and Hong Kong, and on some recent trading days accounted for as much as 35% of KOSPI turnover. When rates rose and risk appetite weakened, the most leveraged winners became the first source of liquidity. The KOSPI fell roughly 6.2%–6.4%, while SK hynix dropped about 12% and Samsung nearly 9%. This was not the central bank deliberately “popping the AI bubble.” It was monetary tightening triggering a deleveraging process in a market that had already become structurally fragile. The shock quickly crossed into the United States. SK hynix ADRs, Micron, SanDisk, and Western Digital all came under heavy pressure before the opening bell. The global memory and storage trade is tightly connected through supply chains, capital flows, and investor positioning; forced selling in Seoul was immediately interpreted as a broader warning for AI hardware. Volatility is likely to remain elevated. In the near term, the key question is whether deleveraging has run its course. Over the next several weeks, the more important test will be whether late-July and August earnings confirm that AI data-center demand, memory pricing, and profit growth remain intact. The rate hike was the trigger. Leverage was the amplifier. Fundamentals determine direction. Liquidity determines speed. ⸻ This is not investment advice. Do your own research. ZERO Truth before conclusions. Test Hundreds. Commit to One. Scientist · Doctor · A9 Investor #Korea# #BankOfKorea# #AI# #Semiconductors# #Memory# #SNDK# #MU# #WDC# #STX# #SKHY# #Samsung#