Last Updated: 6/29/2023 | 17 min. read
ChatGPT is the fastest growing consumer application of all time; it reached 100mm users by January 2023—just two months after its launch. Its quick popularity underscores the profound impact that artificial intelligence (AI) has already had, and will continue to have, on our society. That said, the technology will continue to evolve, and our society will need to evolve in parallel to balance AI’s promise with its potential risks. In light of this, we believe the properties of blockchain technology, including features of transparency, open-source, and global permissionless development, can help to address and may even prevent some of the societal risks of AI and related technologies.
While it is still very early days, there are already a variety of exciting projects at the intersection of AI and blockchain technologies, ranging from decentralizing access to machine learning training models to fully digital “metastars” using generative AI to produce music. In this piece we’ll explore:
- The ways in which crypto and blockchain technologies can combat or solve for potential risks posed by AI, such as
- The various crypto companies and protocols that are working to address concerns and opportunities of the continued proliferation of AI
- The broader synergies between crypto and AI technologies
Figure 1: Chat GPT gains 100 million users in 2 months
Source: World of Statistics
Blockchain Solutions for AI Challenges
While the convergence of crypto and AI is still in its infancy, the topic has already garnered significant investor interest. So far in 2023, venture capitalists have invested $422 million[1] in crypto applications related to AI, privacy, and identity. In total, the crypto-AI intersection represents more than 10% of total crypto venture capital (VC) funding[2] to date including two out of the four largest funding rounds. Figure 2 below captures the largest funding rounds across crypto based AI, Privacy and Identity, and protocols since the inception of the crypto industry; the largest six rounds have all come within the last 12 months.
Figure 2: Largest Six Fundraises for Crypto-based AI, Identity, and Privacy Protocols
In the section to follow, we’ll explore some of the companies receiving funding from VCs to illustrate how each company or protocol has leveraged crypto to address each of the three potential problems created by AI (verification and identity, centralization risk, and data ownership and privacy):
Figure 3: Rise of Deepfakes
Source: AIAAIC, from 2012 to 2021
Verification and Identity: Generative AI significantly lowers the barrier to content creation, but also instigates a flood of misinformation and deepfakes. Between 2022 and the first half of 2023, deepfakes as a proportion of content in the US increased almost 13x from 0.2% to 2.6%. According to the Department of Homeland Security[3], AI-generated deepfakes can lead to incitement of violence, corporate sabotage, and election manipulation among other serious outcomes. To address this risk, blockchain-based entrepreneurs have been exploring how to establish a consensus on the authenticity of information–a feature that is at the core of blockchain technology.
Enter Worldcoin, a verification and identity-based protocol that raised a $115 million Series C in May 2023. Co-founded by OpenAI CEO Sam Altman, Worldcoin’s blockchain-based “proof of humanity” system uses retinal scans to authenticate human users. The company was built to combat the increasing presence of bots online–a trend that is likely to continue to pervade our society in the age of AI.
Worldcoin is working to create a digital identification system called World ID–an identification that is generated using a person’s iris, but has embedded features that focus on preserving that person’s privacy. World ID aims to enable verification of personhood and also verify the authorship or authenticity of a piece of online content or interaction through the blockchain. This represents potential solutions for the proliferation of bots and deepfakes. So far, Worldcoin has attracted over 1.9 million sign-ups from dozens of countries.
Figure 4: Increasing costs of GPU Training
Source: Epoch AI, This graph depicts the increasing costs of training machine learning (“ML”) models. The high costs of such models empowers incumbents to the detriment of builders.
Centralization Risk: AI’s capital-intensive nature could centralize power among an oligopoly, which may result in limited alternative options for consumers. As a result of network effects and economies of scale from owning massive data facilities, there is a risk that a few winners in the AI market could be positioned to gatekeep users and developers by charging exorbitant fees or generating user lock-in effects. These dynamics are already at play, as increased demand for training ML models and computation requirements have caused a GPU shortage and a corresponding price hike for Nvidia[4] Graphics Processing Units (GPUs)[5]. Blockchain technology has the ability to counter these forces and democratize AI development by offering decentralized data and computation marketplaces.
One great example of this is Gensyn, which raised a $43mm Series A round in May 2023. Gensyn is a blockchain protocol designed to “connect and verify off-chain deep learning work.” While there are a variety of decentralized compute[6] marketplaces in crypto, Gensyn specifically tailors its approach to machine learning. The decentralized nature of Gensyn’s model eliminates intermediary service providers (like AWS) and connects developers looking to train their AI models directly with the “long-tail” of available compute. This processing power could come from dedicated service providers, or nontraditional sources around the world, whether Central Processing Units (CPUs)[7], GPUs, or personal gaming computers.
In contrast with centralized compute providers, Gensyn aligns platform incentives with its users through crypto, ensuring lower costs for developers to train their models and enabling compute providers around the world to monetize what would otherwise be idle compute. This is particularly relevant given the global GPU shortage and idle compute resources around the world. Not only does Gensyn combat the centralization risk inherent in the LLM[8] market, but it also exemplifies how crypto can help aid AI development by lowering barriers to entry, thereby increasing market competition and overall AI innovation.
Data Ownership and Privacy: User data monetization often accompanies centralization, network effects, and mass consumer utilization. For example, companies like Google, Facebook, and 23andme derive significant income from monetizing various forms of user data. It’s feasible that powerful AI systems could follow suit as consumer applications continue to increase in popularity– a trend that would not only be prevalent in AI-powered chatbots, but also other AI-powered systems, such as AI voice assistance (e.g. Amazon Alexa), smart home devices (e.g. Google Nest), and data-collecting wearable devices (e.g. Apple Vision Pro).
Regardless of whether or not the companies behind these new AI-powered products decide to monetize user data, consumers’ ability to maintain privacy over this data remains paramount. In the most extreme risk, access to and exploitation of confidential information could lead to harmful consequences, such as identity fraud, unauthorized access to banking info, potential discrimination, or even blackmail.
We believe blockchain can enable individuals to combat the trend of data monetization and centralized privacy risks by enabling individuals to maintain sovereign ownership over their personal data in a privacy-preserving manner.
Auradine is an AI and privacy-focused web3 infrastructure B2B solution, which raised an $81 million Series A in May 2023. Auradine is developing hardware and software infrastructure solutions for existing Layer 1 protocols. While the company currently serves Layer 1 blockchains, its long-term vision includes integrating into legacy, bureaucratic sectors, such as healthcare and government with web3 infrastructure[9]. If it can fulfill this vision, Auradine would challenge current notions of the blockchain trilemma[10], as the company attempts to “allow [blockchains] to scale without sacrificing security or user privacy.” In doing so, Auradine could ultimately enable individuals to own their personal, sensitive data and choose when and if to share their personal data externally in a privacy preserving manner.
Additional Crypto and AI Synergies
Beyond crypto-specific use cases that can be applied in addressing potential AI-induced risks, it’s also worth highlighting and understanding the synergies between these two transformational technologies, at least as they stand today.
Consider the metaverse: AI can be a powerful tool for creating, maintaining, and managing persistent virtual experiences. For example, Altered State Machine is a game that enables players to own, train, and trade sophisticated AI agents[11]. Additionally, Hume Collective is a web3 record label comprised of virtual metastars, like Angelbaby, a popular artist signed by talent agency CAA[12] who uses AI to generate music and synthesize voices[13].
It’s important to note that cross-industry applications aren’t limited to consumer entertainment, and there are wide-ranging use-cases from infrastructure to consumer:
Figure 5: Crypto X AI Market Map
Sources: Grayscale Research, Messari, SevenX Ventures, CV Labs. This Market Map contains examples of various companies and protocols in the crypto and AI intersection. It is for illustrative purposes only
The confluence between these two technologies could create several instances of more equitable access to financial resources and opportunities.
The first is in regards to investing, specifically in the private capital markets. As of 2020, only around 10% of US households[14] are accredited investors with access to private markets to invest in pre-IPO companies. This is relevant as private equities have historically outperformed all public equities, averaging almost 10.5% return on invested capital per year versus 5.9% for the S&P 500 Index between 2000 and 2020[15]; as a result, most of the country (and the world) was excluded from investing in what at times has been the highest returning asset class.
And while inequitable access to the private markets is certainly not unique to AI, the advent of AI might further aggravate this disparity. If AI is going to power the future of intelligent computing across all industries, we believe there will likely be a Cambrian explosion of innovation and capital, as a result. In just 2022, AI venture investing totalled $46bn in over three thousand[16] pre-IPO companies, yet only a small fraction of America is able to benefit from these potential capital returns.
We believe crypto, however, flips that paradigm to broaden investor access. If even only a small fraction of AI models are brought on-chain through crypto, about 90% of the US[17] and much of the developing world could gain exposure to the potential return of early stage AI projects. This could counteract potential effects of AI displacement and automation.
The second is in regards to self determination. ChatGPT and other LLMs have made education globally and instantly accessible to an even greater degree than the internet did in the 1990s. With an AI-powered Chatbot, anyone with internet access has a 24/7 tutor that can help improve access to resources focused on financial literacy, as well as education and certifications for specific skills, like software development.
These developments align with and augment the globally permissionless and open nature of crypto. For example: an individual who lives in a country with less access to formal education can now use an AI-tutor to learn how to create a smart contract, deploy it on a permissionless blockchain, and the ability to access capital, developers, and users around the world. This is the potential power of AI alongside crypto.
Figure 6: The performance of AI and non-AI cryptocurrencies
Source: Saggu and Ante, as of October 2022 to February 2023. Past performance is not indicative of future results
Conclusion
Though it’s still early days, we are already experiencing the impact of these technologies (AI and blockchain) at a mass scale. Despite the significant global decline in total VC investment in 2023, funding for AI companies has been remarkably resilient, which could lead to additional and expeditious advancements in technologies’ evolution.
AI assets on the blockchain have already benefited significantly since the launch and popularity of ChatGPT in November 2022, leading to an outperformance of AI crypto assets versus non-AI crypto asset counterparts (Figure 6). We believe this price action largely has more to do with “the hype” around the recent AI news rather than actual gains in underlying protocol utilization thus far.
That said, as AI systems continue to develop, the accompanying challenges and solutions will also evolve, which we believe will only deepen the intersection and synergies between crypto and AI. At Grayscale, we have long believed in the transformative power of blockchain and have been proponents of the crypto ecosystem. AI presents an interesting and relevant use case for the power of crypto – specifically regarding blockchain technology’s potential to support and protect individuals and mitigate societal risks that may be brought about as AI and related technologies continue to develop and impact the way humans live, work, and play. We will be tracking this intersection closely, and look forward to sharing more learnings as this trend develops.
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[1] Messari
[2] Messari
[3] Department of Homeland Security
[4] Digital Trends
[5] A highly parallel processor capable of performing complex computations across a wide range of applications
[6] The processing power and capability of a computer system, which is typically powered by specialized hardware such as high-performance CPUs (Central Processing Units) or GPUs (Graphics Processing Units) that execute the necessary calculations and algorithms.
[7] A computer component responsible for executing instructions and performing calculations in a computer system
[8] LLMs, or Large Language Models, are advanced artificial intelligence systems designed to understand and generate human-like text based on extensive training on a vast amount of language data.
[9] Axios
[10] A theory of blockchain design that only two of the three factors (decentralization, security, and scalability) can be prioritized while the other factor is compromised.
[11] A software program or system that uses artificial intelligence techniques to perceive its environment, make decisions, and take actions to achieve specific goals.
[12] Mirror.xyz
[13] Blockster
[14] DQYDJ
[15] Investopedia
[16] CB Insights
[17] DQYDJ
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