The futures for computing power have not yet been officially listed, but the battleground around it has already heated up. According to a single source, Jump Trading has formed a dedicated team internally, intending to use its own balance sheet to provide market-making services for the computing power futures proposed by CME and Silicon Data, as well as the competitive contracts being prepared by ICE and Ornn; another established quantitative institution, DRW, has also been reported to be planning various strategies to participate in this emerging AI computing power derivatives market, similarly willing to invest its own funds. At the same time, the trading activity in cryptocurrencies has begun to show differentiation: Analyst CW mentioned that prior to mid-August, Binance's daily spot trading volume was around $6 billion to $13 billion, then it surged to a high of about $19.4 billion, and recently has remained around $10 billion; meanwhile, Coinbase in the same materials was described as having "cooled in activity," without providing specific figures. In the story of funds seeking new avenues, the asset paths of celebrities have also subtly shifted toward U.S. stocks—Justin Sun stated that he had not changed his BTC holdings over the past year but has reduced about 80%-90% of his ETH, reallocating a large percentage of funds to the U.S. stock market, while Trump has boasted on social media about the S&P 500 index rising from about 5881 points in December 2024 to about 7651 points in September 2026, a cumulative increase of about 30%, using a macro narrative to endorse this preference. Even more tension derives from technical changes: Anthropic disclosed that its model Claude solved the NIST standard elliptic curve seed generation puzzle that has troubled the cryptography community for about 25 years in less than half an hour, and Justin Sun has also publicly expressed worries about quantum computing and AI algorithms impacting the security of existing cryptographic assets, although the materials simultaneously point out that Bitcoin does not utilize the relevant NIST elliptic curve standards. However, the discussion surrounding "whether Bitcoin needs to prepare for the AI and quantum era in its design" is being pushed to the forefront once again at this junction of narratives.

Quantitative Giants Compete for AI Computing Power Futures

At the same time that Claude is cracking cryptographic puzzles and computing power security is being repeatedly discussed, traditional quantitative giants have quietly moved "computing power itself" onto the trading floor. According to a single source, Jump Trading has established a dedicated team internally, preparing to utilize its own balance sheet to provide market-making services for the computing power futures proposed by CME and Silicon Data, as well as the competitive computing power futures being prepared by ICE and Ornn, rather than merely acting as a “technology provider” outside of the matching platform. This means that, before the specific launch time, specifications, and regulatory approvals of the contracts are made public, the market-making framework, risk control models, and funding usage paths have already been pre-emptively rehearsed on the asset side of top quantitative institutions.

In parallel with Jump, another traditional market-making and quantitative trading giant, DRW, has also been reported to participate in the same batch of computing power derivatives markets with its own funds, configuring between the on-exchange contracts of CME and ICE through various strategies, rather than just providing passive quotes. According to a single source, both institutions have almost simultaneously bet on the computing power futures that are still in the preparatory stage, allowing "AI computing power" to be systematically viewed as an asset target that can be derived, marking a new avenue for quantitative funds to compete in the competitive landscape between CME/Silicon Data and ICE/Ornn.

Binance Increases Volume, Coinbase Cools Down

While computing power futures remain at the "proposed" stage, the focus of trading at the spot level has already begun to subtly shift. According to a single source analyst CW, before mid-August, Binance's daily spot trading volume mostly fell within the range of about $6 billion to $13 billion, then it experienced a phase of increased volume, peaking at about $19.4 billion; although it has since retreated from that high, recent daily trading volumes still maintain around $10 billion, and there has been no typical "peak heat immediately sharply shrinking" scenario, but rather quantitative funds and high-frequency trading have treated Binance as the main liquidity hub, reserving test sites for new narratives.

Correspondingly, the materials mention that Coinbase's trading activity has "cooled down," but did not provide more detailed time distributions or specific quantitative data, nor did they disclose the differences in statistical methods, user structures, and regulatory environments between the two platforms, making it necessary to acknowledge the incompleteness of information in cross-comparison. Even so, the shifts in trading volume still reflect a redistribution of participant preferences: on one end, traders more sensitive to product lines and leverage tools are gravitating toward over-the-counter and on-exchange interfaces more willing to take on new derivatives; on the other end, funds that value compliance frameworks and asset safety are choosing to wait and see amidst the cooling, and this differentiation itself is an important signal of risk appetite and product preferences under the current computing power narrative.

Justin Sun Reduces ETH Holdings in Favor of U.S. Stocks

Against the backdrop of differentiated participant preferences, Justin Sun's asset path over the past year is particularly striking. According to a single source, he has almost treated Bitcoin as his "base": over the past year, he has not changed his BTC position, emphasizing long-term holding using a cold wallet, refraining from swing trading and not chasing new stories. In stark contrast, there is an active reduction of exposure in Ethereum—Justin Sun stated in the same interview that he has reduced about 80%-90% of his ETH position, equivalent to transforming historical major positions into marginal allocations, with this magnitude indicating that he is no longer willing to bear the technological and narrative risks associated with Ethereum.

Post-reduction, the funds have not remained on-chain but are described by him as flowing in "large proportions" to U.S. stocks, although specific targets, timings, and amounts have not been disclosed. From a narrative perspective, he ties this cross-market rebalancing to concerns about future technological risks: quantum computing and AI algorithms may weaken the security of existing cryptographic assets, while the market has not yet fully priced this in, which is more a personal judgment than a conclusion backed by empirical verification. The result is that a long-term crypto investor, while maintaining a cold storage position in BTC, reduces ETH and reallocates to U.S. stocks, placing himself in a more distant, observational position concerning the uncertainties of AI and cryptography; this cross-market shift itself serves as a reminder that the next stage evolution of computing power and algorithms has begun to impact the risk coordinates of longstanding crypto heavyweights.

Claude Breaks the Elliptic Curve Mystery

While computing power futures are still at the "proposed" product level, AI has already reached directly into the core problems of cryptography. Anthropic disclosed that its model Claude solved the NIST standard elliptic curve seed generation puzzle that has troubled the cryptography community for about 25 years in less than half an hour (according to a single source). This seed generation problem, considered an open problem, originally belonged to an area accessible only to a very few top experts, but now under the reasoning capabilities of general large models, it has been rapidly dismantled, drawing concentrated attention from the cryptography community on "to what extent can AI achieve in specialized security fields."

The material further connects this event to the application background of the elliptic curve digital signature algorithm (ECDSA), reminding readers that NIST curves have been adopted by some cryptographic assets to build on-chain signature systems, while Bitcoin intentionally chose a different elliptic curve design and did not adopt the relevant NIST standards (according to a single source). In this comparison, Claude has broken through a standard detail that seems "far from the market," yet suddenly brings general large models and the underlying cryptography of cryptographic assets into the same picture: the technical details and complete reviews have not yet been made public, and much of this currently comes from disclosures by project parties and media interpretations, which are temporarily insufficient to rewrite any public chain's security conclusions, but are enough to serve as a clear signal, reminding the crypto world that future risk assessments cannot only revolve around price volatility but must also include AI's capability to penetrate cryptographic infrastructure.

The Triple Pull of AI, Cryptocurrency, and U.S. Stocks

The emergence of AI computing power futures has led traditional quantitative capital to first choose the path of "switching tracks": Jump Trading and DRW have formed teams and are using their own funds to target the CME/Silicon Data and ICE/Ornn computing power contracts, which are still in the proposed phase, attempting to seize market-making positions in the absence of established rules and regulatory gaps. On one side, computing power derivatives attract top quantitative funds, while on the other side, according to AiCoin data, Binance's daily spot trading volume surged from about $6 billion to $13 billion in mid-August to about $19.4 billion, and has recently remained around $10 billion, while concurrently, Coinbase has been described as having "cooled in transaction activity"; adding to this, Justin Sun has maintained his BTC cold storage position without changes over the past year, yet reduced about 80%-90% of ETH and redirected more chips to U.S. stocks, these differentiated paths among exchanges and personal assets pull the game of "AI computing power—cryptocurrency—traditional markets" onto the same risk map. On the other hand, Anthropic disclosed that Claude solved the NIST elliptic curve seed generation puzzle in less than half an hour, while Bitcoin did not adopt the relevant NIST elliptic curves, which provides a new narrative space for "conservative curve selection" and makes Justin Sun's personal concerns about the security impact of quantum computing and AI algorithms no longer just a distant hypothesis; however, discussions on the impact of AI and quantum on chain security remain at a theoretical level and lack systematic attack cases and quantifiable research support. Meanwhile, Trump has repeatedly emphasized on social media that the U.S. stock market is the "strongest in history" and uses the S&P 500’s rise from about 5881 points in December 2024 to about 7651 points in September 2026, a 30% cumulative increase, to support his macro narrative, making U.S. stocks, within this politicized optimistic context, viewed by some crypto circle funds as a third main axis for reallocation. Moving forward, the variables worth continuous observation will be when computing power futures will officially start trading, whether mainstream crypto exchanges will continue to differentiate, and whether breakthroughs in AI in cryptography will leave quantifiable empirical traces in on-chain security.

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