Background
On 19 December 2022, I made a post on my Twitter profile (now X) in which I said that in 2023, in my opinion, AI would become a major trend in the cryptocurrency world.
Although it may seem like a short period of time, we were at the dawn of the rise of generative AI. In that post, I recommended following the technological evolution of a number of AI-related cryptocurrencies, among which Fetch.ai (FET) stood out, which, in my opinion, would have the opportunity to dominate the crypto scene due to the development potential of AI ‘autonomous agents’.
And so it was with regard to an important KPI in the crypto world, the price of the token. On that day, FET quoted 8 cents, while at the time of writing it is worth $3. This exponential growth in price is a sign of the expansion and focus of an entire industry, led by companies like OpenAI and Nvidia in the mainstream, outside of Web3.
Not all that glitters is gold in the crypto world
The rise in prices of AI-related cryptocurrencies, driven by the run-up in Bitcoin (BTC) but also and perhaps most importantly by Nvidia, has not been accompanied by the actual development of use cases that could lead to token scarcity and thus justify their appreciation, the main use case continuing to be staking which is far from being a unique value proposition for the industry. The current token scarcity is generated by the accumulation of tokens by speculators and not by spending in the ecosystem on services, as is at least partly the case with Ethereum.
The Web3
The explanation for this difficulty of alignment between real technological impact and industry movement lies upstream. Web3 and all related use cases in the cryptocurrency world are currently struggling, or at least have not yet managed to reach a critical mass to match the turnover and performance of realities offering centralised experiences. It is illuminating just to stop and count how many Web3 software solutions we use on a daily basis versus how many centralised solutions we use to appreciate how far the road to Web3 is still uphill.
The future of Web3 remains uncertain. The success of this new vision of the web will depend on its ability to win the trust of users, institutions and companies.
Web3 is still in a development phase and has several critical issues that hinder its widespread adoption. There are several reasons why Web3 is not yet fully functional:
- Complexity: The use of technologies such as blockchain and cryptocurrencies can be complex for the average user, creating a barrier to entry. On the other hand, interoperability with multiple services makes their use complex.
- Scalability: The blockchains currently in use are not capable of handling large numbers of transactions, limiting the use of Web3 for large-scale applications.
- Vulnerabilities: Web3 technologies are still new and could be subject to vulnerabilities and cyber attacks.
- Regulation: The lack of a clear regulatory framework for cryptocurrencies and decentralised applications creates uncertainty and hinders adoption by institutions and companies.
- Cost: The purchase of cryptocurrencies and the use of decentralised applications can be costly, limiting access to a narrow band of users.
Artificial Intelligence and Commoditisation in the Crypto World
Artificial Intelligence has become a predominant topic of discussion since generative AI entered the mainstream last year, thanks to companies such as OpenAI and the acquisition of Microsoft. Not a week goes by without a new innovation being launched or a new LLM (Large Language Model) claiming to have surpassed its predecessors. Even in the cryptocurrency world, claims about the potential of AI solutions abound, but what are the actual facts?
Unfortunately, decentralisation, while having great philosophical and value significance for the crypto world, in fact represents a major limitation to innovation when applied to projects that have to compete with equal centralised projects, since it prevents the achievement of the critical mass necessary to invest heavily in innovative directions, despite the capitalisation of some projects. The result is AI ‘agents’ that replicate what exists in the ‘centralised’ market, but with the limitations we have already seen on adoption.
There is a further problem with regard to the value that can be created in the world of blockchain-supported software: the direction taken is leading AI software services to increasingly become commodities, and the distance between those developed in a decentralised and centralised manner is likely to favour the adoption of the latter in the crypto world as well, due to their technological, security and cost superiority, undermining the use of crypto-native projects for many activities.
In the near future, we will see an acceleration of the commoditisation of LLM models, while the hardware sector will remain premium, precisely because the push towards large-scale, low-cost use of the software component will increasingly drive the need for computing capacity.
The trilemma blocking decentralised projects
In the crypto sector we can see projects that aim to investigate a solution to real world problems with AI, but even here we don’t have traction: look at the case of Rejuve, which aims at human life extension, but a blockchain model is too stringent to scale up quickly, in startups we have different funding levels achievable in different rounds (A,B,C), in the crypto world we only have one ICO and reserve funds that don’t work as elastically as the funding model of traditional startups.
In the traditional world, on the other hand, we have much more numerous and visionary initiatives that can even aim to change even the still premium sectors such as CPUs by challenging their leadership, as startups such as Rain.ai are doing, which are creating chips for AI by exploiting a similar functioning to the human brain, processing data directly in memory, even competing Nvidia’s approach. These initiatives are centralised, funded and focused on a single purpose by a hierarchical team. In the crypto world, this paradigm is challenged by attempting to apply democracy and parcelling out initiatives, but these, as in Buterin’s trilemma, lead to lack of execution speed.
Yet, there is a potential winning use case
Processing capacity is the great absentee, it is the scarcest resource and the one for which an aggregation of decentralised capacities can make the most sense.
- The experience of Bitcoin mining has already led to large decentralised processing capacities being made available to secure the network.
- The blockchain was born to keep records and facilitate exchanges, yet all the pioneering projects involving the sharing of processing capacity and its pooling to run AI have not yet been successful in the crypto world.
The absolute pioneer was Matrix AI (MAN), whose Whitepaper 1.0 envisaged precisely this purpose, but since it was never commercially successful, it moved on to a Whitepaper 2.0 and then 3.0 that focuses on brainwave processing as a more appealing communication theme. Nunet.ai (NTX), which is part of the Synglularity.ai (AGIX) ecosystem, has never achieved high visibility compared to projects that focus their communication on AI ‘autonomous agents’.
Nevertheless, sharing decentralised processing capacity to run AI could prove to be a winning use case and justify the use of blockchain and a token.
Conclusions: Artificial Intelligence, Blockchain and Crypto: a Winning Failure for the Web3?
The year 2023 saw the rise of Artificial Intelligence as a major trend in the cryptocurrency world. The growth in the price of tokens such as FET (Fetch.ai) is clear proof of this.
However, there has not yet been any real development of use cases that could lead to the scarcity of tokens and thus explain their appreciation.
Web3, with its promise of a decentralised and democratic Internet, still remains a utopia. Complexity, scalability, vulnerability, regulation and cost are just some of the factors hindering its widespread adoption.
Artificial Intelligence, while promising, is at a standstill in the crypto world. Decentralisation, while a core value, limits innovation and value creation. Commoditisation of AI services is an imminent reality, and centralised projects, due to their technological, security and cost superiority, are bound to prevail unless there is a paradigm shift that fully exploits the possibilities of blockchain and decentralisation.
In the future, we will see a growth of the hardware sector for AI, while software will increasingly become a commodity. Centralised start-ups (as in the Rain.ai example), will have a significant advantage over decentralised crypto projects.
To be successful, Web3 will have to overcome its criticalities and find a way to make the most of Artificial Intelligence. The challenge will be to strike a balance between decentralisation and innovation, creating an ecosystem that is secure, efficient and attractive to users, institutions and companies.
Ultimately, the future of Web3 is to be written, it remains uncertain, but it is possible that it could overcome its challenges and become the new frontier of the Internet, perhaps also thanks to the right balance of centralisation and decentralisation of technological solutions.
The price of tokens, in all of this, will likely continue to have little correlation with commercial success and follow a purely short-term speculative logic resting on ambitious expectations for the future, but in the crypto world this is normal: an old saying in the tight-knit community is ‘we’re here for the technology, not the price!’.
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