About GAIB Part 1

GAIB — The First Economic Layer for AI & Compute

Introduction

GAIB is the economic layer for AI and compute future. We enable anyone to own a piece of AI. The name “GAIB” draws inspiration not only from the movie Dune, symbolizing “the unseen” or “the future”, but also from our core pillars: GPU, AI, and Fi (Financialization). In the AI era, GPUs are the new assets, and compute is the new currency akin to spice in Dune, GAIB is liberating a trillion-dollar AI & compute market.

GAIB focuses on creating a new commodity asset class — GPUs, with yields backed by real AI cashflow. GAIB financializes and tokenizes enterprise-grade GPUs and creates a vibrant economy around it. GAIB addresses the growing demand for high-performance computing resources in the AI era by transforming how high-end GPUs are financed, traded, and utilized.

GAIB emerges from the recognition that the current landscape of high-performance computing, particularly within artificial intelligence, machine learning and the extended compute ecosystem, faces significant challenges in terms of resource allocation, financing, and accessibility.

Mission

To create a more liquid, accessible, and vibrant commodity market for compute assets.

The AiFi Economy

GAIB is building the AiFi economy, which signifies a paradigm shift in how we perceive and utilize computational resources, particularly in the context of artificial intelligence and machine learning. As AI continues to transform industries and drive innovation, compute power, especially that provided by high-performance GPUs, is becoming an increasingly critical resource — akin to a new currency in this evolving economic landscape.

Currently, the decentralized compute tech stack consists of several well-developed layers:

• Hardware layer: GPU manufacturers
• Network layer: Decentralized compute networks
• Service layer: Middleware service providers and aggregators
• Consumer layer: End-users and AI companies

Yet, the full potential of this AI economy has yet to be realized due to a crucial missing component: an economic layer. GAIB bridges the gap between physical computing resources and financial markets, enabling the transformation of GPU compute power into a tradable, financialized asset class.

Background

This missing Economic Layer has inspired GAIB to validate the idea that as AI technologies advance, the demand for powerful compute resources, especially enterprise-grade high-end GPUs, is skyrocketing.

GAIB financializes and provides liquidity for the on-chain AI economy

• The foundational idea of tokenizing on-chain compute stems from the observation that in the AI era, compute power is becoming akin to a form of currency.
• The financialization of tokenized on-chain compute draws parallels with how commodity markets evolved. For instance, just as Real Estate Investment Trusts (REITs) allowed for more liquid and accessible investment in property markets or gold ETF (and other products) allowed for more direct and accessible ways to get gold exposure, GAIB creates a similar model for high-performance computing resources.

Challenges in Financializing Compute

Just as gold once served as the backbone of monetary systems, we at GAIB believe that GPU compute power could become the foundation for a new digital economy in the AI era. However, unlike gold, GPUs are not easily divisible or tradable in their physical form, especially when it comes to the enterprise-grade hardware that GAIB focuses on.

We draw parallels between tokenizing compute resources and gold to highlight a fundamental challenge in the high-performance computing market:

Enterprise-grade GPUs represent the pinnacle of computing power, but their physical nature creates significant barriers to widespread accessibility and tradability.

Consider a single NVIDIA H100 GPU card. This powerful piece of hardware comes with a hefty price tag of ~US$30,000. However, these GPUs are rarely used in isolation. They’re typically deployed in clusters or systems, such as NVIDIA’s DGX H100, which houses eight H100 GPUs in a single machine. Such a system can easily cost over ~$300,000. This high unit cost alone creates a substantial barrier to entry for many potential investors or users, let alone missing the investment instruments and channels.

Furthermore, GPUs lack the fungibility that makes gold so easily tradable.

Unlike gold, which can be divided into smaller units without losing its intrinsic properties, a GPU cannot be split. You cannot take an H100 GPU and break it into smaller, functioning parts. This indivisibility is a crucial difference.

• In the world of precious metals, one ounce of pure gold is essentially interchangeable with another ounce of the same purity.
• GPUs, on the other hand, can have subtle variations in performance due to manufacturing processes.

Their value also varies based on factors like age, usage history, and specific model variations. This non-fungibility complicates the process of valuation and exchange.

Operational complexity presents another significant challenge. Gold can be stored with minimal ongoing costs, whereas GPUs require constant maintenance, regular software updates, and operational support to retain their value and functionality. This adds layers of complexity to owning and trading these assets that do not exist with precious metals.

Finally, the value of a GPU is primarily derived from its computational capabilities. When a GPU is idle, it is essentially a depreciating asset — consuming electricity and requiring maintenance without generating value. This is in stark contrast to gold, which retains its value even when stored unused in a vault, often serving as an inflation hedge.

GAIB’s approach to tokenization seeks to overcome these challenges by creating a digital representation of GPU compute assets that can be easily divided, traded, and utilized. By tokenizing GPU clusters and their yields, rather than individual units, and enabling fractional ownership through NFTs, GAIB makes these valuable computing resources more accessible and liquid.

Financializing Compute Through GAIB

GAIB’s strategy is inspired by financial innovations from other markets. Just as Real Estate Investment Trusts (REITs) made property investment more liquid and accessible, GAIB aims to create a similar model for high-performance computing resources.

Historically, commodity markets began with the direct exchange of physical goods. Traders would gather at specific locations to buy and sell tangible products like grain, livestock, or precious metals. While functional, this system had significant limitations: it required physical storage and transportation, was geographically constrained, and often lacked liquidity due to challenges in matching buyers and sellers with precise needs.

As these markets evolved, financial innovations emerged to address these issues. One of the most notable advancements was the introduction of futures contracts, which allowed traders to agree on a price for a commodity to be delivered at a future date. This innovation separated the financial aspect of trading from the physical delivery of goods, enabling traders to speculate on price movements or hedge risks without needing to take possession of the actual commodities.

GAIB’s model leverages a similar concept by using NFTs to represent ownership in GPU clusters and their yields. This approach echoes the early stages of financialization in commodity markets, where the focus was on creating tradable representations of physical assets.

In GAIB’s system, each NFT signifies fractional ownership of a GPU cluster and its yield. This is akin to how early commodity markets used certificates or warehouse receipts to represent ownership of physical goods stored at a specific location. These certificates facilitated easier trading without the need for physically moving the commodities — a particularly relevant feature for GPU clusters, which cannot be easily relocated.

Key Advantages of GAIB’s NFT-Based System:

1. Fractional Ownership: By tokenizing GPU clusters and their yields, GAIB allows investors to own a portion of these valuable resources, lowering the barrier to entry.
2. Improved Liquidity: NFTs can be traded more easily than physical GPU hardware, fostering a more liquid market for high-performance computing resources.
3. Transparency: The on-chain nature of NFTs ensures a clear, traceable record of ownership, usage, and transactions.
4. Yield Distribution: NFT holders can earn a share of the revenue generated by the GPU clusters, much like commodity owners receive income from leasing their assets.

GAIB’s NFT-based system sets the stage for further developments in the financialization of GPU compute power. Creating a standardized, tradable representation of GPU resources is a vital first step toward building a more sophisticated and dynamic market.

The First Economic Layer for AI & Compute Economy

As mentioned earlier, GAIB aims to build the AI & compute economy much like how gold or real estate markets were established.

Creating an economy involves two fundamental steps: financialization and liquidity.

Gold, for example, is inherently illiquid and comes with high trading frictions. To improve its liquidity, various tradable instruments have been developed, including futures, options, ETFs, and notes. The process of creating these “currency-like” tradable instruments that offer exposure to gold assets is what we refer to as financialization. However, having a tradable instrument alone is insufficient — liquidity and markets are essential to facilitate trading. This is why numerous exchanges, brokerages, banks, and investment institutions exist to support the trading of these instruments. Through these two steps, a vibrant economy around gold assets has emerged, and the same principle applies to real estate and other markets.

Similarly, GPUs are also illiquid and face high trading frictions, with even more complexities than gold, as previously discussed. GAIB seeks to address these challenges by creating a dynamic commodity market for GPUs, akin to the markets for gold and real estate.

“Economic Layer = Financialization + Liquidity”

To build a vibrant AI and compute economy, GAIB applies the same two steps: financialization and liquidity.

Through financialization, illiquid fixed compute assets are converted to digital, yield-bearing assets. DeFi use cases (e.g. GPU backed stablecoins, lending/ borrowing, etc.) are further built to provide liquidity to facilitate a thriving AI Compute economy.

There are a lot of possibilities that GAIB can open up

• Direct exposure: Offering direct exposure into the AI and compute economy through tokenized GPU assets, as compared to indirect exposure through Nvidia or other semiconductor stocks
• Yield products: Providing superior yields comparing to traditional yield products, especially under the macro backdrop of rate-cutting cycle
• Payment: Facilitating GPU-backed stablecoins as a native currency for compute resources
• Speculation: Opening up markets for speculation on GPU assets and compute power prices
• Hedging: Providing tools for hedging against compute asset and power costs. For instance, an AI company can hold the tokenized GPU NFTs to hedge against their computation costs for using the underlying GPUs for AI inferencing/ trading as they can share part of the revenue
• Liquid secondary market: Creating a secondary market for GPU assets and associated compute power trading, which did not exist before. If needed, physical delivery of the compute resources through the underlying compute provider is also possible given our network and resources
• Portfolio strategy: ETFs or complicated investment strategies can be formulated using the tokenized assets as underlying instruments to customize the investment needs
• Diversified products: through the DeFi use cases, different structured products or derivatives can be created cater to a variety of risk profiles, for instance PT (low risk low return) or YT (high risk high return) tokens

These are only selected use cases that we envision can be made possible with GAIB — the financial infrastructure for AI and compute economy.

Moving Forward

GAIB’s vision goes beyond merely tokenizing GPU resources. We are laying the foundation for a new financial ecosystem built around compute assets, aiming to establish them as a fundamental asset class in their own right.

In the coming months, we plan to fundamentally reimagine the role of compute assets and power within our economy and financial systems. By establishing this new financial ecosystem, we are positioning ourselves at the forefront of a transformative shift in how we value and utilize one of the most critical resources of the AI era.

We may witness the rise of specialized compute power trading firms, akin to today’s commodity trading firms, or new tech companies focused on optimizing the utilization and financialization of GPU resources.

Why not both? GAIB is building the Economic Layer anyway.

In the next few weeks, we will provide more insights into our product, architecture, business models, and the key ecosystems we have been collaborating with.

Stay tuned, fellow Fremen!

🟠 About GAIB (/ga-yeeb/) — The Economic Layer for AI & Compute

GAIB is the first economic layer for AI and compute future. We help anyone own a piece of AI. We create a new yield bearing asset that tokenizes GPUs and their yield.

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