Artificial Superintelligence Alliance

État actuel : Artificial Superintelligence Alliance is trading at $0.215100 with a $0.6 billion market capitalization (rank #107). The price moved +7.50% over the past 24 hours and is -20.04% over 7 days; the 30-day move stands at -8.04% and the 90-day at +49.69%.

Position dans le cycle : The asset trades deep in the post-peak drawdown regime, more than 70% below its prior cycle high — typical of late-stage bear conditions or assets that have permanently re-rated lower.

Volatilité et structure : 30-day realized volatility of 118.8% annualized is extreme for an asset this size. Our composite multi-horizon Price Strength reads Bearish (39/100), against a weakening multi-horizon backdrop with cumulative pressure across 30/90-day windows.

Beyond Bitcoin, FET's 90-day return correlations to the other two largest layer-1 references help characterize whether the asset moves as part of a crypto-market beta complex or as something more idiosyncratic. The Pearson correlations across daily log returns:

• Bitcoin reference: +0.57 — a moderate positive relationship.
• Ethereum reference: +0.67 — a strong positive relationship.
• Solana reference: +0.70 — a strong positive relationship.

Strong correlation to multiple references typically indicates that the asset trades primarily as crypto-market beta — moves in BTC/ETH/SOL drive most of the price action, and stand-alone alpha is harder to capture. Weak or negative correlations indicate idiosyncratic drivers (project-specific news, sector rotation within crypto, or narrative shifts) that can produce returns uncorrelated with the broader market.

Artificial Superintelligence Alliance (FET) is une cryptomonnaie, négociée sur les marchés mondiaux d'actifs numériques. It trades at $0.2151 as of the latest update, with a 24-hour move up 10.42%, placing it at rank #107 by market capitalisation among all listed digital assets. Artificial Superintelligence Alliance's current market cap stands at $584.96M, a figure used by traders, analysts and institutional desks to gauge relative liquidity and risk exposure across the crypto market.

Sur cette page, vous trouverez un tableau de bord en direct, actualisé quotidiennement, qui suit Artificial Superintelligence Alliance à travers plusieurs sources de données — historique des cours sur plusieurs années, activité on-chain quand disponible, fondamentaux comme l'offre en circulation et la dilution, principales plateformes par volume, analyse technique avec moyennes mobiles et RSI, et une prévision algorithmique à court, moyen et long terme. Tous les chiffres proviennent d'APIs publiques et sont mis en cache localement ; rien ici n'est un conseil en investissement.

Artificial Superintelligence Alliance is part of the AI×crypto sector — networks attempting to capture value from the explosion in AI demand by providing the substrate on which AI services run (compute, data, identity). This is a narrative-heavy category and prices have historically tracked AI-sector sentiment as much as any underlying network metric.

Artificial Superintelligence Alliance se situe à l'intersection de l'intelligence artificielle et de l'économie crypto. L'architecture spécifique varie : certains réseaux paient des récompenses en tokens à des fournisseurs de GPU contribuant en compute (Render, Akash), certains exploitent un marché d'inférence décentralisé (Bittensor, Fetch.ai), et certains construisent des systèmes de proof-of-personhood / identité pour l'ère IA (Worldcoin). Le fil conducteur est d'utiliser l'économie crypto pour coordonner compute, données ou identité à grande échelle en dehors du contrôle d'une seule entreprise d'IA.

Typical use cases include: paying for compute access, rewarding GPU providers, paying for inference, staking on data accuracy, and identity attestation. Real on-chain activity for most AI-crypto projects remains modest relative to market capitalization — meaning these are primarily narrative-driven assets at present.

Artificial Superintelligence Alliance's tokenomics combine its supply schedule, current circulating supply, and the relationship between circulating market cap and fully-diluted valuation. At over 99% of maximum supply issued, future issuance pressure is effectively zero — the supply curve is now flat, and value accrual must come from network adoption rather than from supply schedule mechanics.

For thesis-building, the relevant question is whether the structural value accrual mechanism (fee burns, staking yield reinvestment, deflationary supply mechanics, ecosystem TVL growth) outpaces the structural emission pressure. When it does, the price tends to grind higher over multi-quarter windows even without speculative momentum; when it does not, the asset typically requires consistent narrative-driven demand to absorb the issuance.

The macro backdrop for crypto assets in 2026 is dominated by the Federal Reserve's rate path, the trajectory of dollar liquidity, and the unwind (or non-unwind) of the post-2020 expansion in M2 money supply. Crypto assets — and Bitcoin in particular — have historically responded most strongly to changes in the global liquidity regime, with risk-on phases coinciding with falling real yields and a softening dollar, and risk-off phases the inverse. Given the 90-day BTC correlation of +0.57, FET's near-term macro sensitivity will be similar to Bitcoin's — driven primarily by the same liquidity conditions and risk-asset flows.

The cross-asset relationships worth monitoring: the dollar index (DXY) — historically inversely correlated with crypto over longer windows; the 10-year Treasury yield — a proxy for the cost of risk capital; gold — which often shares "monetary hedge" framing with Bitcoin during certain regime changes; and the S&P 500 — which during liquidity-driven moves often rhymes with crypto despite the popular framing of crypto as uncorrelated.

For Artificial Superintelligence Alliance specifically, the macro variable that has empirically led price most often is global crypto-market liquidity — proxied by stablecoin total supply, futures open interest, and exchange volumes. When these expand, FET tends to follow; when they contract, the relationship typically reverses.

Specific risks: narrative dependence (price tracks AI-sector sentiment more than network usage), regulatory exposure (especially for identity-related projects), competition from centralized AI providers with vastly better unit economics, and the open question of how much real AI compute actually needs to be decentralized to function. Volatility on AI-crypto tokens tends to be higher than the broad alt-coin average.