Recently, the AI-driven Web3 trading and research platform Vision Makers has secured $4 million in seed funding. This is not an isolated early chip, but rather buoyed by a larger capital narrative: according to a single source, OpenAI's revenue for the third quarter has approached $10 billion, increasing by about 50% quarter-over-quarter, while CoreWeave's revenue was $3.66 billion during the same period, soaring by 167% year-on-year. Despite ongoing losses, their yearly guidance has been raised, collectively reinforcing the global growth story that "computing power and models are the new oil." The explosive supply of computing power has led to concessions on the tool side; Claude's one-time free reset of its full quota for paid users directly reduced the marginal costs of using large models for intensive research and high-frequency trading, allowing more on-chain funds to view AI as infrastructure rather than a luxury. However, not all tokens labeled "AI" under the same storyline are being uplifted unconditionally: according to a single source, GPRO dropped 15.7% within 24 hours to about 0.752 USDT, revealing a divergence within the sector regarding who truly benefits from the computing power dividend and who is merely telling stories. On the other end of the screen, the Prime Minister of Qatar mentioned at the G7 foreign ministers' meeting that he has sought at least two additional weeks for US-Iran negotiations, but there remain significant differences on key issues such as the steps to lift maritime blockades and nuclear matters. This delayed uncertainty casts a shadow over energy supply, dollar liquidity, and interest rate expectations. One hand of capital is being drawn toward AI-driven businesses like Vision Makers by high AI growth, while the other is tightening between GPRO-type corrections and US-Iran negotiation risks, repricing mainstream on-chain assets like BTC and ETH, reshaping the current crypto market's risk appetite and capital flow between the "growth story chase" and "return to safe assets."

AI Giants' Earnings Reports: Risk Appetite Warms

While the new AI+Web3 infrastructure represented by Vision Makers is still telling a story, OpenAI and CoreWeave have already written "AI growth" into cash flow with quarterly numbers. A single source shows that OpenAI's revenue in the third quarter was about $10 billion, increasing by approximately 50%, mainly from model and advertisement sales; CoreWeave's revenue was $3.66 billion in the third quarter, a 167% year-on-year increase, and it raised its full-year revenue guidance to between $13 billion and $13.3 billion, even though it still reported a loss of $1.27 per share. For global capital, this set of "high-growth + high capital expenditure + not profitable yet" signifies that computing power, models, and ad space now constitute a visible pool of revenue, and the investment cycle for AI infrastructure is far from over. Historical experience suggests that when such capital expenditures expand, the risk appetite for the NASDAQ and growth stock indices tends to warm up simultaneously, with investors more willing to pay higher valuations for "future computing rents" and "model penetration rates."

This sentiment quickly transmits across assets to the on-chain world. When technology and high-growth sentiments improve, BTC is often included in the same "risk asset basket," while ETH and a batch of high Beta tokens serve as leveraged tech beta: funds first increase bets on US AI and cloud computing, then extend out along the risk curve to liquid assets like BTC and ETH, and finally to more aggressive narrative tokens related to computing power and infrastructure. In light of the giants' earnings confirming demand for computing power and models, the market's valuation tolerance for "computing power, infrastructure, and AI narrative tokens" increases, and it is more willing to give time to the stories of sectors like on-chain GPUs, AI research, and trading tools. However, the fact that CoreWeave is still in a loss reminds funds that high growth does not equate to risk-free. During the same phase, GPRO's 24-hour drop of 15.7% to about 0.752 USDT reflects this misalignment—although the US AI sector gained strength, raising overall risk appetite, it did not endorse all on-chain AI tokens. Incremental funds favored selecting targets between BTC, ETH, and a few higher-deterministic high Beta assets, while enjoying the AI growth premium and actively avoiding the excessively financialized parts of the narrative.

Vision Makers Secures Investment: Betting on AI On-Chain Trading

At the same time when narrative tokens like GPRO are being filtered by funds, Vision Makers completed a $4 million seed round of financing, which feels more like a bet by capital on the "AI-driven on-chain trading and research tools" infrastructure side. It is positioned as an AI-driven Web3 trading and research platform, but the use of funds, valuation, and leading investors have not been disclosed, which indirectly indicates that this track is still in the early exploration phase: what investors are buying now is not a definite business model, but a direction—most future on-chain financial decisions will be completed by models rather than by humans.

For quantitative funds and high-frequency traders, AI trading and research tools are already a natural extension of strategy discovery and execution optimization. Once such platforms secure ongoing financing, this implies more robust computing power, denser data access, and lower barriers to tool usage. Historical experience has proven to be harsh: when barriers lower and automation increases, the usage rates of derivatives and leveraged products often rise, leading to a more concentrated on-chain dollar liquidity around high liquidity varieties like BTC and ETH, further strengthening them as the primary collateral and main trading targets for the entire AI trading chain. Meanwhile, if tools like Vision Makers begin to penetrate into retail levels, the execution gap between "smart money" and "ordinary money" will be partially narrowed, but the overall market's leverage density and strategy homogenization may also rise in tandem. In the next wave of volatility cycles, the directional choices for BTC and ETH, along with the migration pace of funds between major exchanges, will be more easily shaped by this type of AI+Web3 tooling.

Claude Quota Reset: Lowering Trading and Research Costs

Beyond platforms like Vision Makers, model providers themselves are quietly rewriting cost curves. Recently, Claude offered a one-time free full quota reset for paying users to address previous limitations that exceeded expectations. This is viewed by those heavily using AI for research and trading not just as "experience optimization," but as a substantive reduction in marginal costs: long reports, strategy iterations, and multi-chain data fetching, which originally required careful budgeting within a monthly allowance, can now run more test rounds and open several hypothetical scenarios within the same payment range, directly raising their frequency of model calls and their "willingness to use."

For professional traders, the cost of using analytical tools and research models is an important constraint on their ability to iteratively refine strategies at a high frequency. With a more abundant and predictable quota, the rhythm of on-chain research, strategy backtesting, and intelligence gathering will naturally accelerate; cross-exchange price differences, mispricing of cross-chain assets, and altcoin narrative rotations will be more easily "smoothed" by capital the moment they are discovered. Historical on-chain records show that the popularity of research and intelligence tools often leads to increased activity in arbitrage and spread trading, reducing price differences between different exchanges and assets. Today, this process is further expedited by AI models, meaning that the "information efficiency" of BTC, ETH, and even more fringe altcoins is improving, with the speed of price discovery and responsiveness to news also likely to elevate overall.

GPRO Plummets 15%: AI Token Filtering and Risk Aversion Backflow

During the same phase when the AI narrative is being constantly reinforced, the on-chain market presented a counter sample: GPRO dropped 15.7% within 24 hours, with prices plunging to about 0.752 USDT (according to a single source), and the specific project's background, reasons for the drop, and market response have not been publicly disclosed. This type of "no apparent bearish news but suddenly abandoned" trend is often not an isolated incident, but rather the first round of "survival of the fittest" following a warming of sector stories—once the funds have acknowledged the general direction of AI+Web3, the next step is to distinguish among specific tokens what is truly fundamental and what is merely a trend label. For tokens that already have limited liquidity and lack clear income or use-case support, any fluctuation will be amplified into a re-pricing opportunity, with funds quickly choosing to exit and concentrate chips on a few leaders and more capable assets.

Historical experience repeatedly shows that when certain tokens in a hot sector begin to frequently exhibit double-digit declines, funds often flow back along the same path: first reducing exposure to thematic investments, then reallocating positions into BTC, ETH, or on-chain dollar-denominated assets, turning sector risk into "index risk." BTC and ETH are viewed as safe haven points within the sector, absorbing some of the funds exiting during dramatic corrections of thematic tokens, and this backflow will directly lower the valuation center of the entire AI+Web3 narrative. New stories are still emerging in the primary market, but in the secondary market, significant declines like GPRO’s will be benchmarked to similar projects, leading to larger pricing discounts that investors are willing to offer and higher liquidity compensation requirements, consequently raising financing costs. In other words, every severe correction of smaller AI tokens serves as a depreciation provision for the entire sector, reminding participants that only a few assets can transit through narrative cycles, while the remainder will be ruthlessly liquidated in the accelerating price discovery process.

Qatar Mediates US-Iran: Geopolitical Risks Cast Shadows on Crypto

While the secondary market is still pricing stories like Vision Makers' "AI + on-chain trading," the Prime Minister of Qatar has subtly shifted the macro backdrop with another narrative clue revealed at the G7 foreign ministers' meeting—he stated that he has secured at least two more weeks for US-Iran negotiations, but there remain significant discrepancies on key issues such as the steps to lift maritime blockades and nuclear matters (according to a single source). This implies that tensions in the Middle East have not genuinely cooled but have simply been briefly "paused." In terms of pricing, this is an invisible hand directly pointing towards oil prices and inflation expectations: if the US-Iran deadlock continues, the market will first discount energy supply risks, driving up oil prices and inflation expectations, which will in turn raise interest rate expectations and the US dollar index, applying uniform valuation pressure on all high Beta risk assets. The transmission chain in the crypto market is often faster: once traders begin to reassess interest rate pathways, the roles of BTC and ETH will oscillate between "growth sidekicks" and "geopolitical hedge instruments"—some funds exit high-leverage AI concept tokens to increase holdings in decentralized assets like BTC, hedging sovereign risks; while others choose to flow back into dollars and short-duration bonds, reducing overall on-chain position weight. Ultimately, in a scenario where the fervor for AI capital and geopolitical shadows coexist, the real challenge is not which narrative line to believe, but how to dynamically switch positions between “growth narratives” and “geopolitical hedges”: adequately granting upward premiums to the AI sector while reserving foundational positions in assets with more macro-hedging properties like BTC and ETH, to avoid a sudden volatility of oil prices and interest rate expectations that could drop the entire AI+Web3 trading chain from a high-growth narrative into a passive deleveraging liquidation scenario.

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