From Worthless to 89000 What Has the Cryptocurrency Market Experienced Along the Way

The trading volume has exceeded $85.4 billion.
Although we have not yet fully realized a “ownership network,” we have seen the vibrant innovation that cryptocurrencies have brought to the current internet.
For example, stablecoins such as Tether (USDT) and Circle (UDSC) are quietly changing the landscape of the global payment network.
According to Coinbase’s research report, stablecoins have become the fastest-growing payment method. Stripe recently completed the acquisition of the stablecoin infrastructure project Bridge for a whopping $1.1 billion, the largest acquisition in the crypto world.
Blackbird, founded by one of Resy’s co-founders, focuses on changing the dining experience by allowing customers to pay for their meals with cryptocurrencies, particularly their own token, $FLY.
This platform aims to connect restaurants and consumers through a cryptocurrency-driven application, while also serving as a loyalty program.
Worldcoin, co-founded by Sam Altman, is a cutting-edge movement that promotes universal basic income and relies on zero-knowledge proof technology.
Users scan their irises through a device called Orb, which generates a unique identifier called “IrisHash” to ensure that each participant is a unique human, thereby combating the growth of false identities and bot accounts in the digital space. Worldcoin has over 10 million participants worldwide.
If we go back to the summer of 2017, we probably wouldn’t have imagined what the next seven years would mean for the crypto industry – the growth of so many applications on the blockchain or the storage of billions of dollars in smart contracts.
How AI mirrors cryptocurrencies
Now let’s talk about the similarities and differences between cryptocurrencies and AI. After all, many people often compare the two.
Comparing cryptocurrencies to AI is like comparing apples to oranges.
But if we look at today’s AI investments from the perspective of cryptocurrency investors, we may find some similarities: both are comprehensive technologies with their own infrastructure layers and application layers.
But the confusion is similar: it is still unclear which layer will accumulate the most value, the infrastructure layer or the application layer?
“What if the headline does what you want to do” – this may be a nightmare for all entrepreneurs.
The history of internet development has proven that this nightmare is not unfounded, from Facebook and Zynga breaking up to do their own mobile games; to later Twitter’s live streaming and Meerkat, the resource advantages of big companies make it difficult for startups to compete.
In the crypto industry, because the economic models of the protocol layer and the application layer are different, not every project’s focus is on every layer of the ecosystem.
Take public chains (ETH, Sol, etc.) as an example. The economic model determines that the more people use this network, the higher the gas revenue and the higher the token value. Therefore, the top projects in the crypto world invest most of their energy in ecosystem construction and attracting developers.
Only when popular applications appear can the use of the underlying public chain be increased, thereby increasing the project’s market value. Early infrastructure projects may even directly provide subsidies ranging from tens of thousands to millions of dollars to eligible application developers.
Our observation is that the value capture of the infrastructure and application layers is difficult to determine, but for capital, both the infrastructure and application layers will take turns to be hot, but the winners take all.
For example, with a large influx of capital into public chains, leading public chain projects have improved performance, giving rise to new application models and eliminating mid-to-low-tier public chains; capital flows into new business models, user bases grow, leading applications occupy capital and users, and demand for underlying infrastructure increases, driving infrastructure upgrades.
So what can we refer to for investment? The simple truth is that investing in both infrastructure and application layers is not wrong, but the key is to find the top players.
Let’s fast forward to 2024 and see which public chains have survived. Here are three simple conclusions:
Disruptive technology plays a small role in a project’s success. Previously, “Ethereum killers” that were pursued and promoted by Chinese and American VCs and focused on professor and academic concepts (such as Thunder Core, Oasis Labs, Algorand, etc.) only Avalanche ultimately came out, and it was under the premise of professors leaving and full compatibility with the Ethereum ecosystem.
On the other hand, Polygon, which was not favored by investors because of its lack of novelty (forking ETH), has now become one of the top five ecosystems in terms of on-chain assets and users.
Unfortunately, projects like Near Protocol, which focuses on sharding technology and has TPS that can surpass Ethereum, with nearly $400 million in funding and a current on-chain asset value of only around $60 million.
Of course, the numbers fluctuate daily with market conditions, but the trend is clear.
Stickiness of developers and users comes from the ecosystem. For public chains, users not only include end users but also developers (this ignores miners, which is a completely different model).
For end users, the ecosystem with rich applications and more transaction opportunities will have greater stickiness.
For developers, the ecosystem with more users and better infrastructure, such as wallets, block explorers, and decentralized exchanges, will be considered first for development. Overall, it shows a flywheel effect driven by developers and users.
The network effect of the top players is larger than imagined. The number of Ethereum users and the amount of funds locked in on-chain applications is greater than the sum of all “Ethereum killers.”
When people (especially those outside the industry) think of smart contract platforms, they almost always think of Ethereum (just like when people think of AGI, they think of Open AI). It has almost become the industry standard for developing blockchain applications.
Furthermore, existing top public chains already have a large amount of cash that they can invest or donate to developers, which is something new startups cannot achieve.
Finally, because most blockchain projects are open source, mature top ecosystems allow decentralized applications to have more possibilities.
So what are the significant differences between public chains and large models?
Requirements for infrastructure. According to a16z’s statistics, 80-90% of early-stage funding for most AI startups is spent on cloud services.
AI application companies spend an average of 20-40% of their revenue on fine-tuning costs for each customer.
In simple terms, the money is being earned by NVIDIA and AWS/Azure/Google Cloud.
Although public chains also have mining rewards, the cost of hardware/cloud is borne by decentralized miners, and the current scale of data processed by blockchains is still negligible compared to the billions of data tags required by AI models, so the cost of infrastructure is much smaller than that of large models.
Liquidity, liquidity, liquidity. Public chains that have not yet launched their mainnets can issue tokens, but AI models companies without users and revenue find it difficult to go public.
So while the performance of various “professor chains” may not have been as successful as expected (after all, Ethereum is still undoubtedly the No. 1), from the perspective of investors, they are not likely to lose money and are even unlikely to go to zero.
Large model companies, on the other hand, are different. If they fail to raise the next round of funding and there are no buyers, they are easily doomed. From this perspective, venture capitalists should be more cautious.
Actual productivity improvements. Through ChatGPT, LLM has found its product-market fit and is truly being used on a large scale by B2B and B2C customers, improving productivity.
Although public chains have gone through two bull and bear cycles, they still lack a killer app, and application scenarios are still in the exploration stage.
Perception of end users. Public chains and end users are strongly correlated. If you want to use a decentralized application, you need to know which public chain it is on, and then go through the trouble of moving your assets to that public chain to form a certain stickiness.
AI, on the other hand, is more silent, like the cloud services and processors inside computers. No one cares whether ride-hailing software is powered by AWS or Alibaba Cloud. Because ChatGPT’s memory is very short-term, no one cares whether they are chatting with ChatGPT on its homepage or on an aggregator. So, it is more difficult to retain C-end users.
As for the application scenarios of cryptocurrencies in AI, many teams have given their own insights, and generally, it is believed that decentralized financial networks will become the default financial transaction networks for AI agents. I think the following chart accurately summarizes the current stage.
In the haystack, finding the needle more agilely
When I entered the cryptocurrency industry, I had almost no confidence in the decentralized concept. I think most industry participants felt the same way in the early stages.
People joined this industry for various reasons – for money, technology, curiosity, or just by chance.
But if you ask me today if I have confidence in cryptocurrencies, I will give a definite answer. You cannot deny the entire industry just because there are scams in the crypto industry, just as you cannot deny the entire finance industry because of Madoff’s scandal.
An example that recently happened to me is my friend R (pseudonym).
He successfully turned an idea into a company with 200 employees, positive cash flow, and a market value of over $200 million.
R’s entrepreneurship was based on his understanding of decentralized value.
“My girlfriend is a small internet celebrity on TikTok, but internet celebrities can only get a small portion of the tips from their viewers,” he once told me. The world’s largest creator network is not fair, “I want to build a decentralized version.” At that time, I thought he was joking, but about three years later, he actually launched this project. The platform now has hundreds of thousands of users.
For someone who joined this industry at the age of 24 after graduating, the past seven years have shown me enough aspects of the world: idealists, gold diggers; those who have made excessive returns and those who have lost everything.
I remember my former boss in the article, an OG who made a lot of money in the crypto industry, once said, “You still have to work hard, otherwise, you will become a rich ordinary person.”
I think there is a respected investor who described the work of VCs as “finding a needle in a haystack.” For me, VC investment in the crypto world is also such a process.
The only difference is that the haystack in cryptocurrencies may be moving faster. So we must always remain agile.
The author of this article is JW (@bestmosquito), the founder of Impa Ventures. Impa Ventures is a fund that focuses on early-stage investments in the Web3 industry.
Shiran and James, two other partners at Impa Ventures, and analyst Guo Yunxiao also contributed to this article.
This article is a collaboration and repost from: Deep Chao.