From July 27 to 28, 2026, within two days, Nvidia announced a significant piece of news capable of rewriting industry narratives: the global chip giant, which tops the market value rankings, has reached a long-term strategic partnership with Safe Superintelligence (SSI), founded by OpenAI co-founder and former chief scientist Ilya Sutskever. Nvidia will invest "tens of billions of dollars" into this company focused on the safety research of "superintelligence," to provide ammunition for building large-scale computing infrastructure on Nvidia's latest Vera Rubin platform. However, on the same trading day when this long-term bet, which seemingly represents the ultimate direction of AI, was announced, the market's immediate response was particularly tepid: Nvidia's stock price fell against the tide by about 5% that day, closing at approximately $195.92 per share, while the Nasdaq Composite Index dipped below 25,000 points during the session, reporting around 24,861.26 points, a decline of about 0.46%, marking a new low since May. With one side betting on the future of superintelligence and the other witnessing evaporating market value, this dislocation between long-term benefits and short-term pressure is the core question this article seeks to examine: why did the secondary market choose to respond to Nvidia's seemingly sound long-term gamble with a downward candlestick when it attempted to tie itself to the "ultimate race track" of superintelligence?
Tens of Billions Invested in SSI Superintelligence
If Nvidia's bet has a symbolic target, it is Safe Superintelligence—an experimental lab established by Ilya Sutskever, the co-founder and former chief scientist of OpenAI. After leaving his "old employer," he chose not to replicate a new general large model company, but instead labeled SSI with a narrower yet more extreme tag: focusing on safety research related to "superintelligence," directly placing the bet on systems that may surpass human cognitive boundaries in the future. For Nvidia, this is not an ordinary client order; rather, it represents a partnership with a team committed to "only doing superintelligence," tying its brand to one of the most controversial yet imaginative technological paths.
According to reports citing informed sources, SSI is receiving a "tens of billions of dollars" investment from Nvidia to build large-scale computing infrastructure and plans to use Nvidia's latest Vera Rubin platform to establish its AI foundation during this process. The official statement defines this as a "long-term strategic collaboration," rather than a one-off purchase contract, which implies that Nvidia is no longer merely selling hardware to downstream developers but is instead co-building a technology and safety stack for superintelligence with real funds and cutting-edge platforms. In this design, Nvidia attempts to move from being a chip supplier at the end of the assembly line to a central position within the ecosystem—serving as a capital source, a provider of infrastructure, and a direct participant in the future rules and forms of superintelligence.
From Selling Shovels to Mining: Nvidia Changes Tracks
In recent years, Nvidia has occupied the "selling shovels" position: becoming the primary supplier of AI computing power globally through GPUs, fitting chips into data centers built by others, with cloud vendors and AI companies shouldering the risks of success or failure of upper-level products. This time, it is pouring tens of billions into Safe Superintelligence, no longer treating the Vera Rubin platform as a standard commodity on the shelf but instead bundling funding and platform together with an avant-garde research AI company, directly engaging in the "mining" of this new vein of superintelligence.
The change in roles directly rewrites Nvidia's risk curve. When selling chips, the cash flow rhythm is clear, and a single order from a large enterprise client rarely approaches the scale of "tens of billions of dollars"; betting on the infrastructure for superintelligence means amortizing inputs over a longer cycle, with returns highly dependent on whether projects like SSI can truly yield results. For other cloud vendors and chip manufacturers, this is both a signal and a pressure: whoever can establish an early foothold in the superintelligence infrastructure, like Nvidia, has the opportunity to gain more say in the future AI stack; conversely, AI startups must adapt to the new landscape—computing power is no longer just a standard commodity on the open market but is being redefined by the superintelligence camp, cloud camp, and chip camp. This is also one of the reasons why the market is still in the process of re-evaluating Nvidia's new identity.
Stock Price Downturn: Why Positive News Struggles to Save the Day
While Nvidia’s substantial bet on superintelligence was making headlines, its stock price took a downturn. On the announcement day, Nvidia closed at about $195.92 per share, a nearly 5% drop, which felt more like a splash of cold water rather than a shot of adrenaline. At the same time, the Nasdaq Composite Index dipped below 25,000 points, reporting around 24,861.26 points, a decline of about 0.46%, seen as a new low since May—this means that the pressures on Nvidia are not just from company-specific news, but the overall tech sector is experiencing downward pressure. In such a broad market environment, even a "tens of billions" long-term collaboration and investment struggles to immediately offset the valuation pullback caused by the contraction of risk appetite.
More subtly, Nvidia's stock price at this time incorporates multiple rounds of expectation premiums regarding the "AI first stock" and "superintelligence entry." Any new investment will be scrutinized by the market under a magnifying glass regarding its return cycle and uncertainty. When the Nasdaq index as a whole declines and risk asset sentiment fluctuates, the sensitivity of highly valued growth stocks to macro variables such as interest rates and economic growth expectations is amplified, testing investors' patience regarding distant future cash flows repeatedly. Nvidia's bet on superintelligence, while reinforcing the narrative of a "long-term moat," is also interpreted by some market participants as a source of pressure on short-term profit statements; under conditions where the reasons remain unclear, a more reasonable interpretation is that the market is undergoing a period of patience instability regarding large AI investments amid rising macro uncertainty and heightened emotional volatility.
The Computing Power Race Across the Oceans Intensifies
In contrast to Wall Street’s hesitant weighing of Nvidia's "superintelligence gamble," the story of computing power is unfolding in a different narrative at the other end. ChangXin Technology's listing on the Star Market is seen by many investors as a "debut ceremony" for the Chinese semiconductor industry. Some media estimates that the equity market value corresponding to the shares held by Hefei State-owned Assets will be about 1.21 trillion yuan, indicating more than 1 trillion yuan in paper gains, representing not only a capital victory for local state-owned assets but also a manifestation of the local semiconductor "wealth creation effect" in the capital market, bringing the slogan of "mastering computing power" into the reflection of real wealth figures for the first time.
At the same time, offline, Shanghai state-owned enterprises have achieved mass production of self-developed DUV lithography machines, with plans to produce about 5 units in 2026 and expand production to about 20 units in 2027. This progress is viewed as a symbol of accelerating domestic replacement—despite the output being still at an early stage in the global landscape, it is sufficient to rewrite the supply chain narrative. As Nvidia pays the price of stock price volatility for its "tens of billions" bet on superintelligence in the US capital market, Chinese semiconductors are showcasing a different investment logic for computing power through IPO paper gains and equipment production timelines in the domestic market: one side is an enormous investment concentrated on a single giant's balance sheet, while the other side is an industrialization path dispersed and undertaken by local state-owned assets and equipment companies. The concurrent advancement of the two makes the global competition in computing power and supply chains shift from a capital story to a more three-dimensional and direct competitive landscape.
When Declines Meet the Long-Term Gamble of Superintelligence
From a timeline perspective, Nvidia has invested "tens of billions" into Safe Superintelligence, betting on a superintelligence narrative that can only be validated over years, while its stock price dropped about 5% on the announcement day, closing around $195.92, facing an emotional valuation based on minute-by-minute and daily volatility. This temporal mismatch, coupled with the Nasdaq falling below 25,000 points and technology stocks being under pressure, has led the market to prefer using "cash flow discount tables" over "science fiction scripts" to evaluate this investment in the short term. For investors wanting to place bets on AI infrastructure, this means assessing not just the height of Nvidia's own valuation but also incorporating the US regulatory environment, domestic and foreign industrial support policies, as well as the supply chain reconstruction brought about by ChangXin Technology's IPO paper gains and domestic DUV mass production into their models. If global computing capacity and capital returns unfold in different regions, merely focusing on one company's story can easily overlook changes in cost structure and bargaining power amid geopolitical competition. In the same time window, Audiera (BEAT) rose about 26.45%, and Venice Token fell about 9.46%, with differentiation in gains and losses among risk assets indicating that funds were not simply "taking risks" or "hedging," but rapidly rotating among different tracks. This multi-layered split in sentiment makes the long-term gamble on superintelligence feel more like a journey needing continuous calibration of its coordinate system: prices may swing between bad news and good news, but what truly determines long-term returns will be whether investors can see through the height of their valuation, the policy cycle, and the supply chain dynamics they are situated in.
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