As AI becomes the fastest-growing tech wave, computing power is seen as a new “currency,” with GPUs turning into strategic assets. Yet financing and liquidity remain limited, while crypto finance needs real cash flow–backed assets. RWA tokenization is emerging as the bridge. AI  infrastructure, combining high-value hardware + predictable cash flows, are viewed as the best entry point for non-standard RWAs — GPUs offer near-term practicality, while robotics represent the longer frontier. GAIB’s RWAiFi (RWA + AI + DeFi) introduces a new path to on-chain financialization, powering the flywheel of AI Infra (GPU & Robotics) × RWA × DeFi.

In discussions around RWA (Real-World Asset) tokenization, the market generally believes that standard assets such as U.S. Treasuries, U.S. equities, and gold will remain at the core in the long term. These assets are highly liquid, have transparent valuations, and follow well-defined compliance pathways — making them the natural carriers of the on-chain “risk-free rate.”

By contrast, the RWAization of non-standard assets faces greater uncertainty. Segments such as carbon credits, private credit, supply chain finance, real estate, and infrastructure all represent massive markets. However, they often suffer from opaque valuation, high execution complexity, long cycles, and strong policy dependence. The real challenge lies not in tokenization itself, but in enforcing off-chain asset execution — especially post-default recovery and liquidation, which still depend on due diligence, post-loan management, and traditional legal processes.

Despite these challenges, RWAization remains significant for several reasons:

1. On-chain transparency — contracts and asset pool data are publicly visible, avoiding the “black box” problem of traditional funds.

2. Diversified yield structures — beyond interest income, investors can earn additional returns through mechanisms like Pendle PT/YT, token incentives, and secondary market liquidity.

3. Bankruptcy protection — investors usually hold securitized shares via SPC structures rather than direct claims, providing a degree of insolvency isolation.

Within AI assets, GPU hardware is widely regarded as the first entry point for RWAization due to its clear residual value, high degree of standardization, and strong demand. Beyond hardware, compute lease contracts offer an additional layer — their contractual and predictable cash flow models make them particularly suitable for securitization.

Looking further, robotics hardware and service contracts also carry RWA potential. Humanoid and specialized robots, as high-value equipment, could be mapped on-chain via financing lease agreements. However, robotics is far more operationally intensive, making execution significantly harder than GPU-backed assets.

In addition, data centers and energy contracts are worth attention. Data centers — including rack leasing, electricity, and bandwidth agreements — represent relatively stable infrastructure cash flows. Energy contracts, exemplified by green energy PPAs, provide not only long-term revenue but also ESG attributes, aligning well with institutional investor mandates.

Overall, AI asset RWAization can be understood across different horizons:

• Short term: centered on GPU and related compute lease contracts.

• Mid term: expansion to data center and energy agreements.

• Long term: breakthrough opportunities in robotics hardware and service contracts.

The common logic across all layers is high-value hardware + predictable cash flow, though the execution pathways vary.

Among the many non-standard AI assets, GPUs may represent one of the most practical directions for exploration:

• Standardization & Clear Residual Value: Mainstream GPU models have transparent market pricing and well-defined residual value.

• Active Secondary Market: Strong resale liquidity ensures partial recovery in case of default.

• Real Productivity Attributes: GPU demand is directly tied to AI industry growth, providing real cash flow generation capacity.

• High Narrative Fit: Positioned at the intersection of AI and DeFi — two of the hottest narratives — GPUs naturally attract investor attention.

As AI compute data centers remain a highly nascent industry, traditional banks often struggle to understand their operating models and are therefore unable to provide loan support. Only large enterprises such as CoreWeave and Crusoe can secure financing from major private credit institutions like Apollo, while small and mid-sized operators are largely excluded — highlighting the urgent need for financing channels that serve the mid-to-small enterprise segment.

It should be noted, however, that GPU RWAization does not eliminate credit risk. Enterprises with strong credit profiles can typically obtain cheaper financing from banks, and may have little need for on-chain financing. Tokenized financing often appeals more to small and medium-sized enterprises, which inherently face higher default risk. This creates a structural paradox in RWA: high-quality borrowers do not need tokenization, while higher-risk borrowers are more inclined to adopt it.

Nevertheless, compared to traditional equipment leasing, GPUs’ high demand, recoverability, and clear residual value make their risk-return profile more attractive. The significance of RWAization lies not in eliminating risk, but in making risk more transparent, priceable, and tradable. As the flagship of non-standard asset RWAs, GPUs embody both industrial value and experimental potential — though their success ultimately depends on off-chain due diligence and enforcement, rather than purely on-chain design.

Beyond computing hardware, the robotics industry is also entering the RWAization landscape, with the market projected to exceed $185 billion by 2030, signaling immense potential. The rise of Industry 4.0 is ushering in an era of intelligent automation and human–machine collaboration. In the coming years, robots will become ubiquitous—across factories, logistics, retail, and even homes. By enabling the adoption and deployment of intelligent robots through structured, on-chain financing, while creating an investable product that allows users to participate in this global shift. Feasible pathways include:

1. Robotics Hardware Financing

   • Provides capital for production and deployment.

   • Returns come from leasing, direct sales, or Robot-as-a-Service (RaaS) models.

   • Cash flows can be mapped on-chain through SPC structures with insurance coverage, reducing default and disposal risks.

2. Data Stream Financialization

   • Embodied AI requires large-scale real-world data.

   • Financing can support sensor deployment and distributed data collection networks.

   • Data usage rights or licensing revenues can be tokenized, giving investors exposure to the future value of data.

3. Production & Supply Chain Financing

   • Robotics involves long value chains, including components, manufacturing capacity, and logistics.

   • Unlock working capital through trade finance, and mapping future shipments and cash flows on-chain.

Compared with GPU assets, robotics assets are far more dependent on operations and real-world deployment. Cash flows are more vulnerable to fluctuations in utilization, maintenance costs, and regulatory constraints. Therefore, it is recommended to adopt a shorter-term structure with higher overcollateralization and reserve ratios to ensure stable returns and liquidity safety.

The RWAization of AI assets is moving from concept to implementation. GPUs have emerged as the most practical on-chain asset class, while robotics financing represents a longer-term growth frontier. To give these assets true financial attributes, it is essential to build an economic layer that can bridge off-chain financing, generate yield-bearing instruments, and connect seamlessly with DeFi liquidity.

GAIB was born in this context. Rather than directly tokenizing AI hardware, it brings on-chain the financing contracts collateralized by enterprise-grade GPUs or robots, thereby building an economic bridge between off-chain cash flows and on-chain capital markets.

Off-chain, enterprise-grade GPU clusters or robotic assets purchased and used by cloud service providers and data centers serve as collateral; On-chain, AID is used for price stability and liquidity management (non-yield-bearing, fully backed by T-Bills), while sAID provides yield exposure and automatic compounding (underpinned by a financing portfolio plus T-Bills).

GAIB partners with global cloud providers and data centers, using GPU clusters as collateral to design three types of financing agreements:

• Debt Model: Fixed interest payments (annualized ~10–20%).

• Equity Model: Revenue-sharing from GPU & Robotics income (annualized ~60–80%+).

• Hybrid Model: Combination of fixed interest and revenue-sharing.

Risk management relies on over-collateralization of physical GPUs and bankruptcy-isolated legal structures, ensuring that in case of default, assets can be liquidated or reassigned to partnered data centers to continue generating cash flow. With enterprise-grade GPUs featuring short payback cycles, financing tenors are significantly shorter than traditional debt products, typically 3–36 months.

To enhance security, GAIB works with third-party underwriters, auditors, and custodians to enforce strict due diligence and post-loan management. In addition, Treasury reserves serve as supplementary liquidity protection.

• Minting & Redemption: Qualified users (Whitelist + KYC) can mint AID with stablecoins or redeem AID back into stablecoins via smart contracts.In addition, non-KYC users can also obtain it through secondary market trading.

• Staking & Yield: Users can stake AID to obtain sAID, which automatically accrues yield and appreciates over time.

• Liquidity Pools: GAIB will deploy AID liquidity pools on mainstream AMMs, enabling users to swap between AID and stablecoins.

• Lending: AID can be integrated into lending protocols to improve capital efficiency.

• Yield Trading: sAID can be split into PT/YT (Principal/ Yield Tokens), supporting diverse risk-return strategies.

• Derivatives: AID and sAID can serve as yield-bearing primitives for derivatives such as options and futures.

• Custom Strategies: Vaults and yield optimizers can incorporate AID/sAID, allowing for personalized portfolio allocation.

In essence, GAIB’s core logic is to convert off-chain real cash flows — backed by GPUs, Robotic Assets, and Treasuries — into on-chain composable assets. Through the design of AID/sAID and integration with DeFi protocols, GAIB enables the creation of markets for yield, liquidity, and derivatives. This dual foundation of real-world collateral + on-chain financial innovation builds a scalable bridge between the AI economy and crypto finance.

GAIB uses an SPC (Segregated Portfolio Company) structure to convert off-chain GPU financing into on-chain yield certificates. Investors deposit stablecoins to mint AI Synthetic Dollars (AID), which can be staked for sAID to earn returns from GAIB’s GPU and robotics financing. As repayments flow into the protocol, sAID appreciates in value, and holders can burn it to redeem principal and yield — creating a one-to-one link between on-chain assets and real cash flows.

GAIB requires assets to be backed by robust collateral and guarantee mechanisms. Financing agreements must include monthly monitoring, delinquency thresholds, over-collateralization compliance, and require underwriters to have at least 2+ years of lending experience with full data disclosure.

Process flow:  Investor deposits stablecoins → Smart contract mints AID (non-yield-bearing, backed by T-Bills) → Holder stakes and receives sAID (yield-bearing) → the staked funds are used for GPU/robotics financing agreements → SPC repayments flow back into GAIB → the value of sAID appreciates over time → investors burn sAID to redeem their principal and yield.

• Over-Collateralization — Financing pools maintain ~30% over-collateralization.

• Cash Reserves — ~5–7% of funds are allocated to independent reserve accounts for interest payments and default buffering.

• Credit Insurance — Cooperation with regulated insurers to partially transfer GPU provider default risk.

• Default Handling — In case of default, GAIB and underwriters may liquidate GPUs, transfer them to alternative operators, or place them under custodial management to continue generating cash flows. SPC’s bankruptcy isolation ensures each asset pool remains independent and unaffected by others.

In addition, the GAIB Credit Committee is responsible for setting tokenization standards, credit evaluation frameworks, and underwriter admission criteria. Using a structured risk analysis framework — covering borrower fundamentals, external environment, transaction structure, and recovery rates — it enforces due diligence and post-loan monitoring to ensure security, transparency, and sustainability of transactions.

Structured Risk Evaluation Framework (Illustrative reference only)

GAIB introduces AID (AI Synthetic Dollar) — a synthetic asset backed by U.S. Treasury reserves. Its supply is dynamically linked to protocol capital:

• AID is minted when funds flow into the protocol.

• AID is burned when profits are distributed or redeemed.

This ensures that AID’s scale always reflects the underlying asset value. AID itself only serves as a stable unit of account and medium of exchange, without directly generating yield.

To capture yield, users stake AID to receive sAID. As a yield-bearing, transferable certificate, sAID appreciates over time in line with protocol revenues (GPU/robotics financing repayments, U.S. Treasury interest, etc.). Returns are reflected through the exchange ratio between sAID and AID. Holders automatically accumulate yield without any additional actions. At redemption, users can withdraw their initial principal and accrued rewards after a short cooldown period.

• AID provides stability and composability, making it suitable for trading, lending, and liquidity provision.

• sAID carries the yield property, both appreciating in value directly and supporting further composability in DeFi (e.g., splitting into PT/YT for risk-return customization).

In summary, AID + sAID form GAIB’s dual-token economic layer: AID ensures stable circulation and sAID captures real yield tied to AI infrastructure. This design preserves the usability of a synthetic asset while giving users a yield gateway linked to the AI infrastructure economy.

The relationship between AID and sAID is comparable to Ethena’s USDe / sUSDe and Lido’s ETH / stETH:

• The base asset (USDe, AID, ETH) itself is non-yield-bearing.

• Only after conversion to the yield-bearing version (sUSDe, sAID, stETH) does it automatically accrue yield.

The key difference lies in the yield source: sAID derives yield from GPU financing agreement + US Treasuries.  sUSDe yields come from derivatives hedging/arbitrage. and stETH yield comes from ETH staking.

Launched on May 12, 2025, AID Alpha serves as GAIB’s early deposit program ahead of the AID mainnet, designed to bootstrap liquidity while rewarding early participants through extra incentives and gamified mechanics. Initial deposits are allocated to U.S. Treasuries for safety, then gradually shifted into GPU financing transactions, creating a transition from low-risk → high-yield.

On the technical side, AID Alpha contracts follow the ERC-4626 standard, issuing AIDα receipt tokens (e.g., AIDaUSDC, AIDaUSDT) to represent deposits and ensure cross-chain composability.

During the Final Spice stage, GAIB expanded deposit options to multiple stablecoins (USDC, USDT, USR, CUSDO, USD1). Each deposit generates a corresponding AIDα token, which serves as proof of deposit, automatically tracks yield and counts toward the Spice points system, which enhances rewards and governance allocation.

Current AIDα Pools (TVL capped at $80M):

All AIDα deposits have a lock-up period of up to two months. After the campaign ends, users can choose to either convert their AIDα into mainnet AID and stake it as sAID to earn ongoing yields, or redeem their original assets while retaining the accumulated Spice points.

Spice is GAIB’s incentive point system launched during the AID Alpha phase, designed to measure early participation and allocate future governance rights. The rule is “1 USD = 1 Spice per day”, with additional multipliers from various channels (e.g., 10× for deposits, 20× for Pendle YT, 30× for Resolv USR), up to a maximum of 30×, creating a dual incentive model of “yield + points.”

In addition, a referral mechanism further amplifies rewards (Level 1: 20%, Level 2: 10%). After the Final Spice event concludes, all points will be locked and used for governance and reward distribution upon mainnet launch.

Fremen Essence NFT:  GAIB also issued 3,000 limited Fremen Essence NFTs as early supporter badges: Top 200 depositors automatically qualify.Remaining NFTs distributed via whitelist and minimum $1,500 deposit requirement. Minting is free (gas only).NFT holders gain exclusive mainnet rewards, priority product testing rights, and core community status. Currently, the NFTs are trading at around 0.1 ETH on secondary markets, with a total trading volume of 98 ETH.

GAIB maintains a high standard of transparency across both assets and protocols. 

• On-chain, users can track asset categories (USDC, USDT, USR, CUSDO, USD1), cross-chain distribution (Ethereum, Sei, Arbitrum, Base, etc.), TVL trends, and detailed breakdowns in real time via the official website, DefiLlama, and Dune dashboards. 

• Off-chain, the official site discloses portfolio allocation ratios, active deal amounts, expected returns, and selected pipeline projects.
  

• GAIB Official Transparency Portal: https://aid.gaib.ai/transparency

• DefiLlama: https://defillama.com/protocol/tvl/gaib

• Dune: https://dune.com/gaibofficial
  

Asset Allocation Snapshot

As of October 7, 2025, GAIB manages a total of $175.29 million in assets. This “dual-layer allocation” balances stability with excess returns from AI infrastructure financing.

• Reserves account for 71% ($124.9M), mainly U.S. Treasuries, around 4% APY

• Deployed assets account for 29% ($50.4M), allocated to off-chain GPU and robotics financing with an average 15% APY.

On-chain fund distribution: According to the latest Dune Analytics data, Ethereum holds 83.2% of TVL, Sei 13.0%, while Base and Arbitrum together make up less than 4%. By asset type, deposits are dominated by USDC (52.4%) and USDT (47.4%), with smaller allocations to USD1 (~2%), USR (0.1%), and CUSDO (0.09%).

Off-chain asset deployment: GAIB’s active deals are aligned with its capital allocation, including:

• Siam.AI (Thailand): $30M, 15% APY

• Two Robotics Financing deals: $15M combined, 15% APY

• US Neocloud Provider: $5.4M, 30% APY

In addition, GAIB has also established approximately $725M in projects pipeline reserves, with a broader total pipeline outlook of over $2.5B within 1–2 years:

• GMI Cloud and Nvidia Cloud Partners across Asia ($200M and $300M), Europe ($60M), and the UAE ($80M).

• North America Neocloud Providers ($15M and $30M).

• Robotics asset providers ($20M).

This pipeline lays a solid foundation for future expansion and scaling.

GAIB’s ecosystem consists of three pillars — GPU computing resources, robotics innovation enterprises, and DeFi protocol integrations — designed to form a closed-loop cycle of: Real Compute Assets → Financialization → DeFi Optimization.

Within the on-chain financing ecosystem for AI infrastructure, GAIB partners with a diverse set of compute providers, spanning both sovereign/enterprise-level clouds (GMI, Siam.AI) and decentralized networks (Aethir, PaleBlueDot.AI). This ensures both operational stability and an expanded RWA narrative.

• GMI Cloud: One of NVIDIA’s six Global Reference Platform Partners, operating seven data centers across five countries, with ~$95M already financed. Known for low-latency, AI-native environments. With GAIB’s financing model, GMI’s GPU expansion gains enhanced cross-regional flexibility.

• Siam.AI: Thailand’s first sovereign-level NVIDIA Cloud Partner. Achieves up to 35x performance improvement and 80% cost reduction in AI/ML and rendering workloads. Completed a $30M GPU tokenization deal with GAIB, marking GAIB’s first GPU RWA case and securing first-mover advantage in Southeast Asia.

• Aethir: A leading decentralized GPUaaS network with 40,000+ GPUs (incl. 3,000+ H100s). In early 2025, GAIB and Aethir jointly conducted the first GPU tokenization pilot on BNB Chain — raising $100K in 10 minutes. Future integrations aim to connect AID/sAID with Aethir staking, creating dual-yield opportunities.

• PaleBlueDot.AI: An emerging decentralized GPU cloud provider, adding further strength to GAIB’s DePIN narrative.

GAIB has formally entered the Embodied AI (robotics) sector, extending the GPU tokenization model into robotics. The aim is to create a dual-engine ecosystem of Compute + Robotics, using SPV collateral structures and cash flow distribution. By packaging robotics and GPU returns into AID/sAID, GAIB enables the financialization of both hardware and operations.

To date, GAIB has allocated $15M on robotics financing deals aiming at generating ~15% APY, together with partners including OpenMind, PrismaX, CAMP, Kite, and SiamAI Robotics, spanning hardware, data streams, and supply chain innovations.

• PrismaX: Branded as “Robots as Miners”, PrismaX connects operators, robots, and data buyers through a teleoperation platform. It produces high-value motion and vision data priced at $30–50/hour, and has validated early commercialization with a $99-per-session paid model. GAIB provides financing to scale robot fleets, while data sales revenues are funneled back to investors via AID/sAID — creating a data-centric financialization pathway.

• OpenMind: With its FABRIC network and OM1 operating system, OpenMind offers identity verification, trusted data sharing, and multimodal integration — effectively acting as the “TCP/IP” of robotics. GAIB tokenizes task and data contracts to provide capital support. Together, the two achieve a complementary model of technical trustworthiness + financial assetization, enabling robotics assets to move from lab experiments to scalable, financeable, and verifiable growth.

Overall, through PrismaX’s data networks, OpenMind’s control systems, and CAMP’s infrastructure deployment, GAIB is building a full-stack ecosystem covering robotics hardware, operations, and data value chains — accelerating both the industrialization and financialization of embodied intelligence.

During the AID Alpha stage, GAIB deeply integrated AID/aAID assets into a broad range of DeFi protocols. By leveraging yield splitting, liquidity mining, collateralized lending, and yield boosting, GAIB created a cross-chain, multi-layered yield optimization system, unified under the Spice points incentive framework.

• Pendle: Users split AIDaUSDC/USDT into PT (Principal Tokens) and YT (Yield Tokens). PTs deliver ~15% fixed yield; YTs capture future yield and carry a 30x Spice bonus. LP providers also earn 20x Spice.

• Equilibria & Penpie: Pendle yield enhancers. Equilibria adds ~5% extra yield, while Penpie boosts up to 88% APR. Both carry 20x Spice multipliers.

• Morpho: Enables PT-AIDa to be used as collateral for borrowing USDC, giving users liquidity while retaining positions, and extending GAIB into Ethereum’s major lending markets.

• Curve: AIDaUSDC/USDC liquidity pool provides trading fee income plus a 20x Spice boost, ideal for conservative strategies.

• CIAN & Takara (Sei chain): Users collateralize enzoBTC with Takara to borrow stablecoins, which CIAN auto-deploys into GAIB strategies. This combines BTCfi with AI yield, with a 5x Spice multiplier.

• Wand (Story Protocol): On Story chain, Wand provides a Pendle-like PT/YT split for AIDa assets, with YTs earning 20x Spice, further enhancing cross-chain composability of AI yield.

In summary, GAIB’s DeFi integration strategy spans Ethereum, Arbitrum, Base, Sei, Story Protocol, BNB Chain, and Plume Network. Through Pendle and its ecosystem enhancers (Equilibria, Penpie), lending markets (Morpho), stablecoin DEXs (Curve), BTCfi vaults (CIAN + Takara), and native AI-narrative protocols (Wand), GAIB delivers comprehensive yield opportunities — from fixed income to leveraged yield, and from cross-chain liquidity to AI-native strategies.

The GAIB team unites experts from AI, cloud computing, and DeFi, with backgrounds spanning L2IV, Huobi, Goldman Sachs, Ava Labs, and Binance Labs. Core members hail from top institutions such as Cornell, UPenn, NTU, and UCLA, bringing deep experience in finance, engineering, and blockchain infrastructure. Together, they form a strong foundation for bridging real-world AI assets with on-chain financial innovation.

Kony Kwong — Co-Founder & CEO
Kony brings cross-disciplinary expertise in traditional finance and crypto venture capital. He previously worked as an investor at L2 Iterative Ventures and managed funds and M&A at Huobi. Earlier in his career, he held roles at CMB International, Goldman Sachs, and CITIC Securities. He holds a First-Class Honors degree in International Business & Finance from the University of Hong Kong and a Master’s in Computer Science from the University of Pennsylvania. Observing the lack of financialization (“-fi”) in AI infrastructure, Kony co-founded GAIB to transform real compute assets such as GPUs and robotics into investable on-chain products.

Jun Liu — Co-Founder & CTO
Jun has a dual background in academic research and industry practice, focusing on blockchain security, crypto-economics, and DeFi infrastructure. He previously served as VP at Sora Ventures, Technical Manager at Ava Labs (supporting BD and smart contract auditing), and led technical due diligence for Blizzard Fund. He holds dual bachelor’s degrees in Computer Science and Electrical Engineering from National Taiwan University and pursued a PhD in Computer Science at Cornell University, contributing to IC3 blockchain research. His expertise lies in building secure and scalable decentralized financial architectures.

Alex Yeh — Co-Founder & Advisor
Alex is also the founder and CEO of GMI Cloud, one of the world’s leading AI-native cloud service providers and one of NVIDIA’s six Reference Platform Partners. Alex has a background in semiconductors and AI cloud, manages the Realtek family office, and previously held positions at CDIB and IVC.  At GAIB, Alex spearheads industry partnerships, bringing GMI’s GPU infrastructure and client networks into the protocol to drive the financialization of AI infra assets.

Financing

• In December 2024, GAIB closed a $5M Pre-Seed round led by Hack VC, Faction, and Hashed, with participation from The Spartan Group, L2IV, CMCC Global, Animoca Brands, IVC, MH Ventures, Presto Labs, J17, IDG Blockchain, 280 Capital, Aethir, NEAR Foundation, and other notable institutions, along with several industry and crypto angel investors.

• In July 2025, GAIB raised an additional $10M in strategic investment, led by Amber Group with participation from multiple Asian investors. The funds will be used to accelerate GPU asset tokenization, expand infrastructure and financial products, and deepen strategic collaborations across the AI and crypto ecosystems, strengthening institutional participation in on-chain AI infrastructure.

Business Logic
GAIB’s core positioning is RWAiFi — transforming AI infrastructure assets (GPUs, robotics, etc.) into composable financial products through tokenization. The business logic is built on three layers:

• Asset Layer: GPUs and robotics have the combined characteristics of high-value hardware + predictable cash flows, aligning with RWA requirements. GPUs, with standardization, clear residual value, and strong demand, are the most practical entry point. Robotics represent a longer-term direction, with monetization via teleoperation, data collection, and RaaS models.

• Capital Layer: Through a dual-token structure of AID (for stable settlement, non-yield-bearing, backed by T-Bills) and sAID (a yield-bearing fund token underpinned by a financing portfolio plus T-Bills), GAIB separates stable circulation from yield capture. It further unlocks yield and liquidity through DeFi integrations such as PT/YT (Principal/ Yield Tokens), lending, and LP liquidity.

• Ecosystem Layer: Partnerships with GMI, Siam.AI (sovereign-level GPU clouds), Aethir(decentralized GPU networks), and PrismaX, OpenMind (robotics innovators) build a cross-industry network spanning hardware, data, and services, advancing the Compute + Robotics dual-engine model.

Core Mechanisms

• Financing Models: Debt (10–20% APY), revenue share (60–80%+), or hybrid, with short tenors (3–36 months) and rapid payback cycles.

• Credit & Risk Management: Over-collateralization (~30%), cash reserves (5–7%), credit insurance, and default handling (GPU liquidation/custodial operations), alongside third-party underwriting and due diligence, supported by internal credit rating systems.

• On-Chain Mechanisms: AID minting/redemption and sAID yield accrual, integrated with Pendle, Morpho, Curve, CIAN, Wand, and other protocols for cross-chain, multi-dimensional yield optimization.

• Transparency: Real-time asset and cash flow tracking provided via the official site, DefiLlama, and Dune ensures clear correspondence between off-chain financing and on-chain assets.

Potential Risks
Despite GAIB’s transparent design (AID, sAID, AID Alpha, GPU Tokenization, etc.), underlying risks remain, and investors must carefully assess their own risk tolerance:

• Market & Liquidity Risks: GPU financing returns and digital asset prices are subject to volatility, with no guaranteed returns. Lockups may create liquidity challenges or discounted exits under adverse market conditions.

• Credit & Execution Risks: Financing often involves SMEs, which face higher default risk. Recovery depends heavily on off-chain enforcement — weak execution may directly affect investor repayments.

• Technical & Security Risks: Smart contract vulnerabilities, hacking, oracle manipulation, or key loss could cause asset losses. Deep integration with external DeFi protocols (e.g., Pendle, Curve) boosts TVL growth but also introduces external security and liquidity risks.

• Asset-Specific & Operational Risks: GPUs benefit from standardization and residual markets, but robotics assets are non-standard, highly operationally dependent, and vulnerable to regulatory differences across jurisdictions.

• Compliance & Regulatory Risks: The computing power assets invested in by GAIB belong to a new market and asset class that does not fall under the scope of traditional financial licensing. This could lead to regional regulatory challenges, including potential restrictions on business operations, asset issuance, and usage.

Disclaimer
This report was produced with the assistance of ChatGPT-5 AI tools. The author has carefully proofread and ensured accuracy, but errors or omissions may remain. Importantly, crypto assets often exhibit divergence between project fundamentals and secondary market token performance. This content is provided for informational and academic/research purposes only, and does not constitute investment advice or a recommendation to buy or sell any token.