Token Economy (Part.1) — Token Velocity
The concept of the token economy is complex and intricate, but not too difficult to understand. At its heart lies the digitization of value and the capturing of changes in value over time. In this article we’ll explore the core elements of the token economy and the role of tokens within the AI Network, and we’ll do this using an example of Starbucks’ digital coffee coupons.
Our goal here is to understand token velocity, through understanding the value a single sentence chat holds within the token economy and how this value changes over time.
Starbucks and Digital Coffee Coupons
Let’s assume Starbucks issues digital coffee coupons. These coupons are provided to customers in the form of digital tokens which can be used to purchase coffee. In this system, the important factors are the issuance and consumption rates of the tokens. That is, how quickly customers use their coupons. If coupons are used too quickly, Starbucks might need to increase the supply. Conversely, if the coupon usage rate is slow, issuing new coupons before the existing ones are fully utilized may lead to inefficiencies and oversupply.
To keep things simple, let’s assume Starbucks sells 100 cups of coffee a day, with a revenue of $3 per cup (totaling $300 revenue per day). Now, imagine Starbucks enhances this by issuing digital coffee coupons as tokens. The consumption rate of these coupons becomes a very important variable in the token economy.
Coupon Usage Speed and Quantity Needed
The speed at which coffee coupons are used is a key element in designing the token economy. For instance, if people delay using their coupons for an average of 10 days, the total quantity of coupons in circulation could be 10 times the initial estimate (because of the difference between the rates of coupon issuance and use). At this rate, the market capitalization of Starbucks coffee coupons would be 10 times the daily revenue of $300, equating to $3,000.
Token Velocity is the speed of token issuance and the rate of token use, and essentially means the speed of exchange of a token or currency.
The Value of a Single Sentence Chat in the AI Network
In-keeping with our Starbucks example, we can liken a single sentence of chat within the AI Network to a digital coffee coupon, in that to understand the value of that single sentence, it’s essential to consider the usability within the network and the amount of value generated through it (just as digital coffee coupons generate value through their usability within Starbucks to purchase coffee).
Analyzing how user participation enhances the network and how this enhancement affects token value is crucial.
Cost of Generating a Sentence in a LLM and Number of Users
Let’s say OpenAI, ChatGPT’s operator, uses tokens to generate responses to users in ChatGPT. Assuming the price per token is $60.00 per 1M tokens, each token’s value would be $0.00006. The number of tokens required to generate a sentence in response to a user’s question can vary depending on the service’s requirements and the complexity of the request. Assuming 100 tokens are needed for a simple response, the cost per sentence would be $0.006. Therefore, to generate $300 in revenue at $0.006 per sentence, 50,000 sentences need to be created.
Given an average of 20 sentences generated per user, the required number of users (DAU) to generate $300 would be 2,500. The number of users needed can vary depending on how many sentences each user generates.
1 $AIN Token’s Significance
Thus, if 1 $AIN token is worth $0.10, 1 $AIN will generate approximately 16.67 sentences. Given an average of 20 sentences generated per user, users will spend slightly more than 1 $AIN per day.
The token economy’s market cap, determined by user participation and token velocity, is a vital factor. Similar to the Starbucks digital coffee coupon example, the coupon’s consumption rate and issuance volume are crucial elements. Likewise, in the AIN project, user participation and token circulation directly impact the market cap.
This indicates that to achieve a market cap of $3,000, 2,500 active users are necessary.
Comparison Through TPS (transactions per second)
With 86,400 seconds in a day, to generate 50,000 sentences, the required Transactions Per Second (TPS) would be:
TPS = 50,000 sentences / 86,400 seconds = 0.58
Meaning, to process 50,000 sentences a day, an average of about 0.58 transactions per second is necessary. While Ethereum, which executes smart contracts rather than sentences, cannot be directly compared, a 0.58 TPS is about 1/30th of Ethereum’s 15 TPS, suggesting a network value of around $15M compared to Ethereum’s market cap.
The Difference Between a $3,000 vs. $15M Market Cap
Comparing the market cap based on a realistic circulation speed of digital coffee coupons and the network’s technical processing speed reveals a significant discrepancy. While designing a token economy keeping speed in mind is crucial, there are many other factors that need to be considered.
We can look at Ethereum as an example. Ethereum’s smart contracts can be applied across various sectors, enhancing network value significantly. Conversely, the assumed market cap of $3,000 in our example is limited to a specific use case, e.g., digital coffee coupons or charging per sentence. Ethereum enjoys a broad user base worldwide, generating network effects that exponentially increase its value. Additionally, Ethereum has built a robust developer community and ecosystem, facilitating sustainable growth and innovation. The more support from developers and projects, the more the platform’s value increases. Ethereum’s reputation as a widely recognized blockchain platform enhances investor trust, leading to an increased market cap through confidence and token use & purchase.
Despite various blockchain technologies striving to surpass Ethereum, its position remains unparalleled when considering the actual user base and network value. Numerous projects claim to achieve tens of thousands, even millions, of TPS and boast millions of users. However, these figures often don’t directly correlate with actual network usability, indicating many blockchain projects are still overvalued in terms of theoretical performance and potential user base.
If Ethereum’s TPS is 15, it can process approximately 1,296,000 transactions a day. Assuming each user generates 20 sentences a day (back to our single sentence example), theoretically, Ethereum could handle up to 64,800 users daily. Paradoxically, this suggests that even with around just 50,000 blockchain users, a significant network can be built.
Therefore, when assessing the true value of blockchain technology and networks, it’s crucial to objectively examine publicly available figures and performance indicators, focusing on actual use cases and the network’s ability to create true value. This understanding is vital in bridging the gap between the technology’s current state and the potential for the sustainable advancement it could achieve in the future.
This process isn’t easy; it requires extensive trial and error and continuous effort. However, ultimately, creating services that genuinely offer value to users is key to ensuring technology projects achieve sustainable success in the market, and value is ultimately what tokens provide and measure.
AI Network is a decentralized AI development ecosystem based on blockchain technology. Within its ecosystem, resource providers can earn $AIN tokens for their GPUs, developers can gain access to GPUs for open source AI programs, and creators can transform their AI creations into AINFTs. The ultimate goal of AI Network is to bring AI to Web3, where everyone can easily develop and utilize artificial intelligence.
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