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Zero tolerance for malpractice. Zero compromise on merit. The Public Examinations (Prevention of Unfair Means) Amendment Act, 2026 delivers swift, decisive, and uncompromising action against those who threaten exam integrity. Towards building a secure, foolproof ecosystem where hard work always wins. #NTA# #ZeroTolerance# #ExamIntegrity# #FairExaminations# #MeritFirst#

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#

ZEROBASE WEEKLY 7.13-7.19 ZBT came under pressure this week, trading overall in the $0.08–$0.11 range. Despite the notable pullback, trading volumes remained decent and liquidity conditions stayed relatively stable, with bid-ask spreads holding at reasonable levels. Crypto market showed resilience this week despite volatility triggered by geopolitical tensions and shifting macro signals. Total cryptocurrency market capitalization remained in the $2.21T–$2.23T range, with only modest fluctuations across the period. Bitcoin opened the week near $63,700 on July 13, pulled back to a mid-week low around $62,000 amid renewed inflation and oil price concerns, then rebounded to trade in the $64,500–$65,000 zone by Sunday, closing near $64,700. This represented a net gain of roughly 2–3% from the weekly low. Ethereum moved in parallel, starting around $1,800, dipping toward $1,750 before settling near $1,860–$1,870 by week’s end — a gain of approximately 5% from the low. Derivatives metrics reflected cautious but stabilizing sentiment. Open interest held relatively steady, 24-hour liquidations remained moderate during volatility spikes, and funding rates on major pairs stayed near neutral to mildly positive. Macro and geopolitical developments featured notable headwinds early in the week. Escalating U.S.-Iran tensions, including fresh military exchanges and concerns over shipping disruptions through the Strait of Hormuz, triggered a sharp spike in oil prices on July 13. WTI crude jumped 9.4% to $78.14 per barrel, while Brent rose 9.6% to $83.30 — marking some of the largest daily gains in years. This initially fueled risk-off sentiment, weighing on equities and crypto while pushing Treasury yields higher. However, the release of June CPI data on July 14 provided meaningful relief. Headline CPI fell 0.4% month-over-month (the largest decline since April 2020), beating expectations of a 0.2% drop, while the year-over-year rate eased to 3.5% from 4.2% in May — also better than the 3.8% forecast. Core CPI came in softer than expected. The positive surprise on inflation helped reverse earlier losses and supported a broad recovery in risk assets through the latter half of the week. U.S. equity markets posted modest weekly declines overall. The S&P 500 fell approximately 1.6%, while the Nasdaq Composite declined 2.9%, pressured by weakness in technology and semiconductor stocks amid doubts over AI spending, compounded by the early-week oil spike. Institutional participation remained a key anchor. U.S. spot Bitcoin ETFs recorded a sharp $425 million outflow on July 13 but saw a reversal with $132 million in net inflows on July 17, led by BlackRock’s IBIT. Ethereum ETFs also posted positive flows that day. Crypto Fear & Greed Index stayed firmly in fear territory, fluctuating in the 25–30 range throughout the week. On-chain data offered constructive signals amid the price action. Long-term holders continued accumulating, while notable whale activity highlighted building support at current levels. In summary, the July 13–19 period delivered a measured recovery in spot prices, driven by favorable inflation data and institutional flows, even as geopolitical risks and equity market weakness kept sentiment cautious. Higher energy prices from Middle East tensions are widely viewed as likely to exert only temporary upward pressure on inflation. With stabilizing ETF dynamics and positive on-chain trends, the market continues to consolidate within a broader risk environment.

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#