Learn more about value accrual in the modular stack with insights from our guest author, Gabe.

Gabe was formerly with the listings team at Coinbase, and is an author from Shoal Research, a firm specializing in DeFi and infrastructure research.

 have been all the rave, but one often overlooked aspect of them is that they fragment value. In a world where we have one monolithic blockchain, all value accrues to this blockchain’s ecosystem — but that’s not the case with modular blockchains.

This is due to their inherent design. Modularity, as it relates to core blockchain components, means that different layers specialize (i.e., do what they’re best at), and the best layers for data availability and consensus, settlement and execution are coupled into one blockchain, which when presented to the end user allows them to get a better product at a lower price. (The reasons why blockchain components such as data availability and consensus are grouped will be touched upon later in this post, as well as execution and settlement.)

Elaborating on this theme, the modular stack’s main benefit materializes with users being able to access cheaper and better blockspace (better in the sense that this specialization allows for total blockspace to expand exponentially; more on this below). As the number of blockchains proliferates, it will unlock applications that we haven’t even thought of yet — much the way broadband unlocked social media for us, as well as better security guarantees. Developers of applications also need to worry less about the “ideal” stack for them; they can just plug and play, subsequently deploying their app. So when the functions of all these core components are carried out by different blockchains, where exactly does value accrue?

But before getting to that, let’s get a little deeper into modular blockchains. One reason the modular blockchain narrative is going to be instrumental for the paradigm shift into blockchain technology and web3, in general, is that it allows us to scale bandwidth without compromising on the very reasons blockchains are so interesting — censorship resistance, vitality and credible neutrality.

In essence, with modular blockchains, we can try to make the best trade-offs on the blockchain trilemma (see above) by scaling in layers. Take Ethereum as an example: with modular blockchains, Ethereum can be used as a settlement layer, since it has the most (and the most geographically distributed set of) validators (as well as a lot of solo stakers and overall less cloud concentration, see 

). In addition, Ethereum’s chain is arguably being secured by the best crypto money after Bitcoin — Ether. But effectively, Ethereum is well suited to be a settlement layer, making it a place to have the 

, as well as dispute resolution (such as for fraud/fault proofs).

Now, with regard to scalability, we do this on layers built on top of Ethereum, much like we do in TradFi (for example, Stripe or something like PayPal is built on top of many financial layers, and usually banks, say every week or so, settle up on the base layer using 

, i.e., the Federal Reserve settlement system). Nic Carter, in 

 with Lex Fridman, breaks it down well (it’s worth noting that TradFi is at an advantage since it utilizes centralized databases to record transfers, etc., while blockchains are distributed ledgers that require cooperation of thousands of nodes to append and verify). 

This mechanism takes the form of rollups and other scaling solutions, rollups being the predominant one, which solely specialize in execution ( basically, just running code in an execution environment, which takes the form of the 

 for Ethereum and Ethereum rollups), and can hence make some trade-offs when it comes to decentralization and security (this is another post in and of itself). Rollups also need 

 and, by extension, consensus in order to function, and while this can be done by Ethereum, it can be outsourced (trade-offs here, too) to blockchains like 

A nice example of a project that embraces modularity is 

, which uses Ethereum as a settlement layer and Celestia as a DA+consensus layer, achieving execution by itself using the 

 (Solana virtual machine) as its execution environment. The SVM is creating a lot of buzz right now as one of the only multithreaded virtual machines, allowing for 

 (basically transactions to be processed in parallel to each other), unlike the EVM, which is single-threaded. Hence, sequential transactions are the norm and parallelization isn’t possible.

Let me precede all this by saying that Ethereum in and of itself 

a modular blockchain, in the sense that it can do everything (data availability, consensus, execution and settlement) by itself, but can be used by other blockchains and layers of the modular stack (for example, execution layers like rollups) for functions such as settlement, which then makes Ethereum a component of 

The way this meme can be understood is that everything is a modular blockchain, and everything is a monolithic blockchain (performing all the functions on the base layer, like Solana), depending upon how you look at it. For example, if I built a rollup on Solana, is Solana itself a monolithic blockchain, or a modular one? Likewise for Ethereum. Even Celestia can achieve execution and settlement as well, but if it’s only utilized for data availability and consensus, then it's a modular blockchain (you get the point).

By embracing modular blockchains, different blockchains can specialize in what they do to fulfill the requirements to have an “optimized” blockchain, as I’ve elucidated above.

Which one of these layers (data availability/DA for short, consensus, settlement or execution) will capture the most amount of value (have the most value accrual)?

This post was inspired after discovering the following 

1) For a DA layer to work, you need some kind of ordering on that layer (hence, DA layers come with their own consensus, i.e., ordering protocols), so in this modular stack, consensus and DA aren’t two separate things. Just imagine using data available on one chain in order to create proofs, but this data (because it's on a blockchain) is ordered in some other way by another chain. It’s just a mess.

2) Execution layers like Arbitrum have pricing (discrimination) power, while DA layers like Celestia do not. This is because Celestia provides a homogeneous service (data availability), while Arbitrum (and other rollups like Optimism; I’m just taking Arbitrum as a main example) provides an execution environment for some of the best crypto apps not found elsewhere. This in itself is one reason why Arbitrum makes a significant amount of revenue (some hundreds of thousands of dollars per day), while Celestia makes negligible fees (less than $100 per day at the time of writing, as seen below, though this is also a function of Celestia’s nascency). 

Arbitrum is also closer to the end user, due to their monopoly on sequencing (the foundation runs the only sequencer). While this will change in the future — for example, with the adoption of 

 — the Arbitrum protocol (sequencer, builder, searcher) will still be the only one to receive user fees, and most importantly, MEV and some part of the fees will trickle down to the DA layer as the rollup/execution environment will still write the data to Celestia, etc.! And remember, if DA layers captured most of the value, then rollups today would be charging lower fees to users than the cost to post/write data to the DA layer (i.e., operating at a loss, which is not the case today).

Anatoly Yakovenko (the founder of Solana) 

 this phenomenon in depth on the Lightspeed podcast.

3) Settlement layers are more valuable than DA+consensus layers (and I’d argue execution layers) simply because of the fact that the settlement layer will be secured by the most money/money-like crypto asset, as in the case of the most credibly neutral settlement layer today, Ethereum, which is secured by ETH. A DA+consensus layer will inevitably have more activity/volume flowing through it, relative to the settlement layer (which will only be used for bridging and dispute resolution, so occasionally, block headers will be posted to it from the DA+consensus layer). But the settlement layer’s asset will still be more valuable, albeit the settlement layer is “doing less.” Just look at TRX vs. ETH; the former’s blockchain handles more volume and burns more of its native token than Ethereum’s, and yet it’s valuated at magnitudes less than ETH. 

Simply put, the monetary premium is the multiple at which an asset trades relative to its fundamentals/fundamental utility (due to its “moneyness”). Gold is a good example: it's not used so much in the economy for production processes — and yes, it also looks good — but most of its value comes from its hard money trait. Case in point. 

 for this point, who puts it better than I do:

the most valuable part of the stack is settlement, then execution, and then DA+consensus

, for all the reasons mentioned above (this is why I’m not delineating between DA and consensus).

My argument can be summed up as follows: The settlement layer is the most valuable because of monetary premiums, and execution is much more valuable than DA+consensus because the latter provides a homogenous service where competition is fierce, and costs (and hence revenue for the DA+consensus layer) will trend to 0 (slightly unrelated, but 

 is great and talks about why these sorts of businesses don’t make sense to pursue). Meanwhile, the former (execution) layers can build network effects at a much greater rate and solidify them with mass liquidity! (They’re also much closer to the users, and they don’t compete on fees!)

Let me explain this point a little more. Right now, rollups such as Optimism and Arbitrum pay more than 90% of their costs (which are actually paid by users) for DA (this 

 expands on what I’m saying), something they want to minimize. Therefore, they might switch to Celestia for DA (and hence consensus), thus lowering their cost (and therefore their revenue) drastically (right now, data on Celestia costs pennies for rollups; if Arbitrum wrote as much data as it did today to Ethereum to Celestia, it would only pay a few thousand dollars — 

 has done good research on this). But users don’t care about small fee increments between rollups! I don’t care if I’m paying $0.01 for a swap on Rollup A when I could be paying $0.007 for a swap on Rollup B, simply because I don’t swap that much, and bridging my assets is a hurdle and entails security risks. But for a rollup —which is, after all, a business posting thousands of megabytes of data to the DA layer — these “increments” in cost matter a lot because they add up. Basically, rollups are price-elastic (

 price elastic). But rollup users aren’t, to a large degree.

From fat protocols to fat applications, modeling value accrual in the blockchain landscape isn’t a new endeavor. The advent of modularity introduces new components to the public blockchain landscape, as well as new economic and value dynamics. Modular blockchains represent a paradigm shift in the blockchain stack — from building a complete integrated network that can serve all four blockchain functions on the base layer, to building networks which use specialized layers for fulfilling these functions optimally.

 is the most valuable component of the stack, underpinned by the monetary premiums associated with the underlying asset. 

 layers follow closely behind. In contrast, 

 despite providing essential functions, face growing competition and diminishing revenue potential due to their semblance to commodities.

In short, the order of value accrual in the modular stack is as follows:

Intermediate

value accrual in the modular stack featured image

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Value Accrual in the Modular Stack: Unpacking Where Value Might Accrue in a Modular Blockchain Future

Dive into the expert insights regarding the 2023-2024 NFT landscape with our guest author and explore the latest trends from metaverse interoperability to gaming NFTs and social tokens.

: Elsa is the head of research at NFTGo, which is the #1 insight-driven gateway to the NFT ecosystem. 

 space continues to evolve. We can observe most NFT-based applications gathering around the following points.

 — In 2023, many brands and creators launched proprietary virtual worlds and NFTs, but they remained fragmented. By 2024, cross-platform ecosystems could achieve unified digital identities and assets across different metaverses, driving transferable virtual experiences across the world.

 — While the "play-to-earn" model faced criticism in 2023, gaming NFTs will evolve into tools for creation, customization and governance. User-generated game metaverses leverage NFTs to prove ownership of digital assets.

 — Social NFTs allow rapid social media growth by establishing exclusive channels with creators. However, in 2024, we may see a shift from NFT speculation to models that directly share revenue through tokens, such as Farcaster’s DEGEN. These tips may provide creators with monetization in a more sustainable manner.

According to data, it’s evident that both 

 and trading volume have decreased as compared to the previous year. Market cap experienced a significant decline, dropping by 41.79% and reaching a low of 3.3 million 

. Peak trading activity occurred on February 20, with daily trading volume soaring to an annual high of 240,000 ETH. However, this momentum didn’t sustain itself throughout the year. Anticipated updates and releases of games like 

 failed to meet community expectations, leading to a cooling of market enthusiasm. As a result, trading volume remained subdued mid-year. Nonetheless, signs of rebound began to appear from November onward.

 underwent an adjustment of about 70%, indicating an overall suppression. However, toward the end of 2023, some persistent signs of resilience appeared as the index rebounded from its low of 4,488 points in October 2023 to 5,000 points by the end of the year. This may indicate that demand for high-quality collectibles still exists.

Looking ahead to 2024, there’s a collection leading the NFT bull market: 

. The market may oscillate as a result of speculation and be accompanied by temporary volatility spikes.

 the 2023 NFT trading volume reveals that blue-chip collectibles still dominate the market. 

 (BAYC) alone accounted for 10.45% of the total trading volume, with 

nd and third, respectively. The combined trading volume of the top nine collectibles accounts for nearly 50% of overall trading activity. While new collectibles frequently emerge, data indicates that the most reliable blue-chip NFTs continue to drive the majority of trading activity.

The chart above shows that PFP remains the cornerstone of NFT applications, with a total market value of about 4 million ETH. In contrast, the art category surpasses gaming, collectibles and utility, rising in the NFT space with a market value approaching 500 million ETH. This surge is likely driven by significant advancements in AI, significantly boosting the market. Additionally, domain categories have become more prominent in the NFT space since last year.

PFP will continue to be the cornerstone of the NFT industry, providing a foundation for various NFT collectibles to expand their influence. Notable developments include Yuga Labs launching new games, innovative collections and elements introduced by Azuki and DeGods, and the collaboration between Pudgy Penguins and Walmart. 

The integration of AI technology injects new momentum into the industry, promoting an increase in video and generative art NFTs. Looking ahead to 2024, we expect to see more innovative efforts to further activate the market.

The gaming category has the highest liquidity, having risen by about 380%. The issuance of NFTs for classic games like OVERWORLD 

 and Pixelmon further activates the market. Liquidity in the art and land categories is also significant, both of which exceeded 200% of other categories.

As 2023 came to a close, the NFT market experienced less volatility as compared to the previous year. The first four months were characterized by increased activity. NFTGo's data shows a decrease in overall market activity in 2023, while active traders decreased significantly, down 47.51% from 2022. Despite this decrease in trading activity, the number of NFT holders saw significant growth, increasing by 132.44 over the previous year and reaching a total of 6.42 million.

The above data shows that the ratio of daily buyers to sellers in 2023 ranged from 0.52 to 1.02, with an overall average of 0.85, indicating a relatively balanced market between buyers and sellers. September had the highest monthly average ratio (0.92), indicating the upcoming "Uptober."

 dominated the market with a trading volume of 7.74M ETH, six times higher than its next competitor. However, 

, a newcomer, saw explosive traffic growth after its release in October 2022, surpassing OpenSea's daily trading volume by December.

This growth continued more steadily in 2023, with Blur accumulating a total trading volume of 4.33M ETH, 2.5 times that of OpenSea's 1.7M ETH. However, OpenSea maintained its lead in terms of sales volume with 7.9 million, compared to Blur's 4.1 million. This suggests a higher average transaction value on Blur.

In the past month, Blur has had 292,000 active traders, including 187,000 buyers and 210,000 sellers. OpenSea had a total of 642,000 buyers and 719,000 sellers, but Blur attracts more high-value 

Key factors contributing to Blur's growth include its zero platform fees, token incentives and features catering to professional traders, such as bulk purchasing. Traders are more inclined toward markets with features like multi-chain trading, highest liquidity and security.

Overall trading volume and number of traders have significantly increased over 2023, indicating a growing interest in 

 NFTs. Weekly total trading volume between the two markets increased from approximately $1.5 million at the beginning of January to over $11 million by the end of December. The number of active weekly traders increased from about 80,000 to over 110,000 during the same period.

The number of unique collections traded weekly increased from around 5,000 in January to over 15,000 in December, indicating a growing diversity of NFTs traded on Solana.

Meanwhile, the number of active traders of NFTs on Solana surged in 2023, with total weekly traders on Magic Eden and TensorSwap more than tripling from January to December and surpassing 100,000 by December.

Average weekly transaction size decreased over the year, from approximately $850 in January to $550 in December, with Magic Eden’s average transaction size consistently larger than that of TensorSwap.

Although Magic Eden accounted for the majority of trading volume and traders, TensorSwap saw growth in Q4 2023. Magic Eden's share of total weekly trading volume decreased from 90% in the first quarter to 60% in the fourth quarter, while TensorSwap's share increased from 10% to 40%. This indicates increasing competition between the two markets.

 disrupted the industry with innovative inscription concepts, gaining attention from all investors. Since January 2024, the total number of inscriptions has exceeded 56 million. As shown above, from April to September 2023, there was a period of significant growth as most markets began to support Ordinals and the 

. Although the number of daily inscriptions temporarily decreased in October, a series of favorable market conditions, such as the launch of UniSat's Brc20-swap, contributed to the recovery.

Types of Ordinals. Source: Dune Analytics

Initially, Ordinals were primarily used for images. However, with the development of the market and the introduction of BRC-20, the lack of file format restrictions in Ordinals made it possible to embed JSON files (mainly text formats) into BTC. With the help of a Indexer, BRC-20 can replicate functionality similarly to ERC-20, including minting and asset transfer. This progress has made text the most popular type of Ordinals, accounting for nearly 90% of daily inscriptions. It’s noteworthy that the number of text inscriptions periodically exceeded 400,000.

Market development is closely related to the progress of Ordinals. UniSat marks an important milestone in this development. Over time, major exchanges such as Bybit began listing the $ORDI token, significantly increasing trading volume. As of January 2024, over $1.8 billion worth of transactions have been executed, highlighting the strong growth of Ordinals and their increasing market acceptance.

Since the beginning of 2023, Ethereum has been at historic lows, and the floor price of NFTs has remained relatively low. It’s noteworthy that the ratio peaked in February, coinciding with Ethereum's lowest price of $1,429 during the year. This indicates that although there’s an overall correlation between the NFT market and the Ethereum market, the NFT space demonstrates its unique stability.

Throughout 2023, the NFT/ETH market value ratio showed a downward trend, decreasing from around 0.06 to below 0.04.

In summary, the correlation coefficient between the two markets in 2023 was approximately 0.6. Lower correlations occurred in Q1 and Q2, when the Ethereum market was sluggish. In Q3 and Q4 of 2023, the correlation coefficient remained stable, exceeding 0.8, indicating that NFTs also tend to show strong trading volume in a more active Ethereum market.

In 2023, the average weekly NFT deposit was around 3,500, sometimes exceeding 5,000. The top 10 collectibles accounted for an average of 30–40% of deposits. DeGods and Mutant Ape Yacht Club were the most stable deposit collections throughout 2023. Azuki also ranked in the top five in most weeks.

By the end of June, deposits surged, due to increased volatility in the crypto market. If growth continues at the 2023 rate, we can expect average weekly deposits to range from 4,000 to 5,000 in 2024. Some potential peaks may reach over 6,000 deposits per week. Blue chip NFTs are likely to continue to be the preferred deposit choice.

 Trending Toward Stability After the Hype

NFT Annual Review Overview of NFT Ecosystem

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NFT 2024 Annual Review: Overview of NFT Ecosystem and Market Performance

Learn more about Bitcoin halving and the rise of inscriptions with insights from our guest author, DaosViews.

At the end of April this year, Bitcoin is set to enter another halving period. After this halving, the reward for each Bitcoin block will change from 6.25 to 3.125 bitcoins. The halving is always a significant and symbolic event for the crypto ecosystem. Grayscale®, a major player in the crypto world, has recently published an article entitled 

 that addresses this pivotal upcoming halving event.

In its article, Grayscale analyzes the forthcoming halving from four perspectives: The potential impact of supply changes, the role of miners, ongoing on-chain activity and the impact of 

 on the crypto market. Ultimately, all these perspectives converge on one fundamental question: How will it affect Bitcoin’s future price trend?

Regarding the potential impact of supply changes, the article mainly mentions that each halving further increases Bitcoin's scarcity. The concept of "scarcity" depends upon the perspective from which it’s viewed. For instance, new supply indeed decreases. However, if we consider circulating supply, as long as Bitcoin still rewards block mining its circulating supply is continuously increasing.

This point is where Bitcoin differs from Ethereum: Ethereum has a burn mechanism, making its circulating supply potentially 

 as on-chain activity increases, an effect which truly creates scarcity.

On the other hand, the “scarcity” brought about by Bitcoin halving is more of an emotional reaction. Even if it affects Bitcoin's price, the impact would be more of an emotional nature than a substantial one based on mechanics.

Regarding the role of miners, the Grayscale article highlights two challenges they face: the increasing cost of mining and the decreasing income from block rewards. To address these challenges, miners might have to sell not only the bitcoins they mine but potentially also their reserves. The article mentions that as early as the fourth quarter of last year (2023), some miners began selling their inventory to secure funds in anticipation of the upcoming halving.

 ecosystem in 2023, Bitcoin's on-chain activity has greatly increased, bringing substantial income to miners. The article points out three noteworthy data points:

These developments could have several direct consequences for the Bitcoin ecosystem:

The article mentions one particularly noteworthy data point: Within 15 days after the first ETFs’ approval, the inflow of funds over three months absorbed the selling pressure that might be generated by Bitcoin’s upcoming halving. Thus, the article optimistically supports the view that the approval of ETFs will effectively mitigate selling pressure from miners.

Overall, Grayscale's article outlines the unique advantages of this Bitcoin halving as compared to previous ones, and asserts that these advantages will provide long-term support for Bitcoin's price trend. 

I’ve speculated in earlier articles that 

 could potentially reach $100,000 in the next bull market. At the time of that assertion, Bitcoin didn’t yet have an inscription ecosystem. Now, with the Bitcoin ecosystem beginning to take shape and with external financial support, I maintain a certain optimism that Bitcoin could surpass $100,000 in the bull market.

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Bitcoin Halving and the Rise of the Inscription Ecosystem

 Dive into the cutting-edge world of AI and cryptocurrency with insights from our guest author and all about the top projects, investment opportunities, and future prospects. 

Recently, OpenAI released a new tool called 

 that can generate AI videos based on text. Compared to last year's launch of AI search Q&A, text-to-image and other forms, the introduction of Sora represents a significant advancement in AI technology. The debut of this new tool has not only attracted widespread attention in the tech community but also sparked a frenzy in the cryptocurrency market. Many AI-related projects have seen substantial increases, attracting a significant influx of capital.

In 2023, OpenAI’s chatbot product, ChatGPT, with its excellent performance and wide range of application scenarios, quickly became a global focal point in the AI field, igniting an AI craze. This also sparked a bullish trend in the AI track within the cryptocurrency market, with various AI-related projects emerging. This year, OpenAI has launched a new product, Sora, leading people to anticipate whether it can continue the AI wave and bring more innovation and breakthroughs to the industry.

AI (artificial intelligence) is the capability to use computation and machines to mimic human reasoning and problem-solving. With the continual development and application of AI technology alongside the booming cryptocurrency market, the application of AI in the crypto field has gradually become a focal point. 

In the crypto field, the AI theme track covers a range of projects and applications that utilize AI technology to solve problems in cryptocurrency and blockchain.

According to CoinGecko’s data, as of February 22, 2024, the total market capitalization of AI-track tokens has already exceeded $17.4 billion.

2. Applications of AI in the Crypto Domain

As the cryptocurrency market continues to mature and AI technology finds broader applications, the AI-themed crypto project track is showing a trend toward diversification and innovation. Various projects are attempting to implement and promote the application of AI through blockchain technology.

3. Top 10 Representative Potential Projects in the AI Track

4. Investment Opportunities and Risk Analysis of the AI Track

As an important segment in the crypto domain, the AI track offers rich investment opportunities, along with certain risks.

: The AI track is a demand-driven segment. It’s believed that in the near future, the integration of AI with cryptocurrencies will become a dominant trend. This integration is expected to enhance development efficiency, audibility and security of 

, and user accessibility. Such integration isn’t limited to the crypto domain, also bringing new enhancements and additions to the experience of on-chain developers and users.

: AI projects in the crypto domain meet the market's urgent needs for smart contracts, data management and machine learning, etc. As the adoption of cryptocurrencies and blockchain applications continues to expand, the demand for intelligent solutions will keep growing.

Market Potential as the Result of Technological Innovations

: These projects utilize innovative AI technologies and blockchain solutions, bringing unprecedented market potential to the crypto domain. For example, the intelligence and audibility of smart contracts will be significantly enhanced, thus improving the security and credibility of blockchain applications.

: Some projects have already received support and funding from renowned institutions and investors, providing strong financial and resource support for project development.

: AI technology hasn’t yet matured, and there are still challenges regarding the stability and performance of algorithms. Investors need to carefully evaluate the technological risks involved.

: Some projects' technical solutions aren’t fully mature either, so it remains to be seen whether they’re merely hype and concepts, requiring continuous observation and verification.

: AI applications involve a large amount of user data, and the risks of data privacy breaches and misuse still exist.

: The AI track is highly competitive, with varying project qualities. Accordingly, there may be instances of low-quality projects attempting to exploit the market, necessitating careful scrutiny of project teams’ capabilities, product functionalities and technical strengths.

5. Outlook on the Development Prospects of the AI Track

The rise of AI in the cryptocurrency domain has brought unprecedented innovation and opportunities to the entire industry. Consequently, many remarkable developments can be expected in the future.

In summary, the AI-themed track in the crypto domain will continue to attract market attention and investment favor, with projects continually growing in aspects such as technological innovation, marketing and team building. With further technological advances and exploration of commercial applications, the integration of cryptocurrency and AI technology will bring about a more intelligent, efficient and secure digital economic ecosystem.

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AI Leading the Future of Cryptography: Analysis and Outlook on the AI and Crypto Track

Unlock the evolving market landscape of AI and Crypto with insights from our guest author as they dissect market cycles, categorize projects, and highlight emerging trends in assetization.

More than a year since the release of ChatGPT, discussions about AI+Crypto have once again heated up in the market. AI is seen as one of the most important tracks in the bull market of 2024–2025, and Vitalik Buterin himself published an article entitled 

, exploring possible directions for future AI+Crypto exploration.

This article won’t make too many subjective judgments, but will instead simply summarize the entrepreneurial projects combining AI and crypto observed over the past year from a primary market perspective. It will examine the perspectives from which entrepreneurs have entered the market, the achievements made so far, and which areas are still being explored.

Throughout 2023, we’ve talked to dozens of AI+Crypto projects, among which distinct cycles can be observed.

Before the release of ChatGPT at the end of 2022, there were few 

 projects related to AI in the secondary market. The main ones that come to mind are 

 (AGIX) and a few other veteran projects. Similarly, there weren’t many AI-related projects available in the primary market.

From January to May of 2023 could be considered as the first concentrated outbreak period for AI projects. After all, ChatGPT’s impact was significant. Many old projects in the secondary market pivoted to the AI track, and almost every week in the primary market AI+Crypto projects were being discussed. Similarly, during this period, AI projects seemed relatively simple. Many of them were based on a “skin-deep” adaptation of ChatGPT, combined with blockchain modifications, with almost no core technological barriers. Our in-house development team could often replicate a project framework in just a day or two. This also led to numerous meetings with AI projects during this period, but ultimately, no action was taken.

From May through October, the secondary market began to turn bearish. Interestingly, during this time, the number of AI projects in the primary market also decreased significantly. It wasn’t until the last month or two that the quantity started to pick up again, and discussions and articles about AI+Crypto became richer. We once again entered a period where we could encounter AI projects every week. Half a year later, it was evident that a new batch of AI projects had emerged with a better understanding of the AI track, the landing of commercial scenarios and an improved integration of AI+Crypto as compared to the first wave of AI hype. 

Although the technological barriers still weren’t strong, the overall maturity level took a step forward. It was only in 2024 that we finally made our first bet on the AI+Crypto track.

Vitalik Buterin, in his article on “promise and challenges,” provides predictions from several relatively abstract dimensions and perspectives, as follows:

We, on the other hand, will summarize the AI projects currently seen in the primary market from a more specific and direct perspective.

Most AI+Crypto projects are centered on the core of crypto, which we’re defining as “technological (or political) decentralization + commercial assetization.”

Regarding decentralization, there isn’t much to say, as it’s all about 

. Therefore, we can roughly divide the categories of assetization into three main tracks:

This is a relatively dense track, as besides various new projects there are also many old projects pivoting. For example, on the 

 side, there’s Akash Network, and on the 

. After pivoting, the tokens have all experienced crazy surges, which also indirectly reflects the market’s optimism toward the AI track. Although 

 (RNDR) primarily focuses on decentralized rendering, it can also serve AI purposes. 

Therefore, many classifications include RNDR-like computing power-related projects in the AI track.

Computing power assetization can be further subdivided into two directions, based on the use of computing power. One is represented by Gensyn, which is “decentralized computing power used for AI training.” The other is represented by most pivots and new projects, or “decentralized computing power used for AI inference” (the ability of machine learning models to base decisions or predictions on previously learned data or models).

In this track, we can observe an interesting phenomenon, or perhaps a chain of disdain:

Traditional AI → Decentralized Inference → Decentralized Training

The main reason lies in the technical aspect — because AI training (especially for large model AI) involves massive amounts of data. What’s even more exaggerated than the data requirement is the bandwidth demand formed by the high-speed communication of this data. In the current environment of transformer large models, training requires a computational matrix composed of a large number of high-end graphics cards like the 4090 series/H100 professional AI cards with communication channels of the hundred-gigabit level formed by NVLink and professional fiber switches. Can you imagine decentralizing this stuff? Hmm …

The demand for computing power and communication bandwidth in AI inference is far less than in AI training. Naturally, the possibility of decentralized implementation is much greater for inference than for training. That’s why most computing power-related projects focus on inference, while training is primarily left to major players like Gensyn and Together AI, which have raised hundreds of millions in financing. However, from the perspectives of cost-effectiveness and reliability, at least at this stage, centralized computing power for inference is still far superior to decentralized options.

This explains why those focused on decentralized inference look at decentralized training and think, “You can’t make it happen at all,” while traditional AI views decentralized training and inference as “unrealistic in terms of training technology” and “unreliable in terms of inference commercially.”

Some say that when BTC/ETH first appeared, the model of having distributed nodes compute everything seemed relatively illogical (as compared to cloud computing). But in the end, didn’t it succeed? Well, that depends upon the requirements for correctness, immutability, redundancy and other dimensions of AI training and inference in the future. Purely in terms of performance, reliability and price, it’s currently impossible to surpass centralized solutions.

This is also a crowded track for projects, and is relatively easier to understand as compared to computing power assetization because one of the most well-known applications after the popularity of ChatGPT is Character.AI. With it, you can seek wisdom from ancient philosophers like Socrates and Confucius, engage in casual conversations with celebrities like Elon Musk and Sam Altman, or even indulge in romantic talks with virtual idols like Hatsune Miku and Raiden Shogun. All of this showcases the charm of large language models (LLMs). The concept of AI Agents has become deeply ingrained in people’s minds through Character.AI.

What if figures such as Confucius, Elon Musk or Raiden Shogun were all 

So, rather than calling it model assetization, it’s more apt to say it’s the assetization of agents built on top of large models. After all, large models themselves can’t be put on the blockchain. It’s more about mapping agents on top of models into NFTs to create a sense of “model assetization” in the AI+Crypto space.

There are now agents that can teach you English or even engage in romantic relationships with you, among various other types. Additionally, related projects, such as agent search engines and marketplaces, can also be found.

The common issue in this track is first of all that there are no technological barriers. It’s basically just the tokenization of Character.AI. Our in-house tech wizards can create an agent that speaks and sounds like a specific character (such as our co-founder, BMAN) in just one night by using existing open-source tools and frameworks. Secondly, the integration with blockchain is very light. It’s somewhat akin to 

, in which the metadata stored may only be a URL or hash, and the models/agents reside on cloud servers. On-chain transactions only represent ownership.

The assetization of models/agents is still one of the main tracks in AI+Crypto for the foreseeable future. In the future, we hope to see projects with relatively higher technological barriers and closer integration with blockchain that are more native.

Logically speaking, data assetization is the most suitable aspect of AI+Crypto because traditional AI training mostly relies on visible data available on the internet — or, to be more precise, public domain traffic data. This data may only represent a small percentage, around 10–20%, with the majority of data actually lying within private domain traffic (including personal data). If this traffic data can be utilized for training or fine-tuning large models, we can undoubtedly have more professional Agents/bots in various verticals.

Therefore, through AI+Crypto, and under the guidance of decentralized incentives, releasing personal and private domain traffic data and assetizing it to provide better and richer “food” for large models sounds like a logical enough approach. Indeed, there are several teams deeply involved in this field.

However, the biggest challenge in this track is that, unlike computing power, data is difficult to standardize. Using decentralized computing power, the model of your graphics card directly translates into the amount of computing power you have. On the other hand, the quantity, quality and purpose of private data are all difficult to measure. If decentralized computing power is like ERC-20, then assetizing decentralized AI training data is somewhat like ERC-721 — and like having many projects, such as 

 and different NFTs with different traits mixed together. The difficulty in liquidity and market-making is much more challenging than with 

. Therefore, projects focusing on AI data assetization are currently facing significant challenges.

Another aspect in the data track worth mentioning is decentralized labeling. Data assetization operates at the “data collection” step, and the collected data needs to be processed before being fed to AI, which is where data labeling comes in. This step is currently mostly centralized and labor-intensive. With decentralized token incentives, transforming this work into decentralized, labeling-to-earn or (similar to crowdsourcing platforms) distributing work is also a viable approach. A few teams are currently working in this area.

Let’s briefly discuss the currently missing puzzle pieces in this track from our perspective.

You might ask why a VC like us can come up with certain scenarios before entrepreneurs in the market can. That’s because we have seven experts on our in-house AI team, five of whom have PhDs in AI. 

Finally, although from the perspective of the primary market, AI+Crypto is still quite early and immature, this doesn’t prevent us from being optimistic about 2024–2025, when AI+Crypto will become one of the main tracks of this bull market cycle. After all, is there a better way to combine productivity that’s liberated by AI with production relations liberated by blockchain?

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Viewing AI and Crypto from a Primary Market Perspective

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Viewing AI+Crypto From a Primary Market Perspective

Learn more about the gamified decentralized trading experience with insights from our guest author, Hamber Luo.

 is a problem-solving method designed to break down complex problems to their most basic principles or facts, and then build solutions from those fundamentals.

Based on first principles, the problems that a DEX needs to address are as follows:

In order to achieve seamless use, a series of technical user experience (UX) and regulatory issues need to be addressed.

StarkEx and other ZK-rollup technologies have given a significant boost to DEXs in terms of performance and scalability.

Given these improvements, the main challenges now shift to 

user-friendliness, education and awareness

1.3 Changes in User Mindset With the Advent of AI

Under the wave of AI, especially as large models like GPT gradually approach the era of AGI (artificial general intelligence at human level), we indeed see a series of social and technological changes.

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