Key Insights
Foresight Ventures believes AI x Crypto could be the most exciting industry of the next 50 years. Crypto enhances AI by addressing centralized control, data privacy, and security issues, making AI more trustworthy and efficient. AI can empower crypto with intelligent capabilities, enabling smart contracts to make AI-driven decisions, giving blockchains the ability to perceive the physical world, and improving the user experience of blockchain apps.
The intersection of AI and crypto can be categorized into three layers: infrastructure, model, and application. Innovations in the infrastructure layer, such as decentralized computing power and data storage, will lower costs while boosting the efficiency and security of AI applications, bypassing traditional cloud providers. The model layer will enable peer-to-peer model inference networks, fostering collaboration and innovation in AI, reducing costs, and allowing small businesses to engage in AI advancements. Additionally, AI-driven smart contracts will enhance blockchain applications like biometric authentication, fraud detection, and AI trading bots. Finally, the application layer will integrate the infrastructure and model layers into a variety of consumer products.
The infrastructure and model layers of AI x Crypto are relatively mature, but application development is still in its infancy. Significant opportunities exist for expanding the application layer to leverage the developed infrastructure and models.
Al x Crypto has brought forth numerous new research areas with vast research potentials, such as ZKML, FHE-ML, distributed ML training, network quantization, decentralized databases, fully homomorphic encryption, Al hardware, and FHE hardware.
Foreword
“Blockchain has revolutionized the means of production, while AI has transformed the production processes. AI x Crypto may well be the most exciting industry of the next 50 years.”
Forest (Co-founder of Foresight Ventures)
AI x Crypto Introduction and Overview
AI x Crypto projects have shown strong asset returns over the past two years. The Intersection of AI and crypto holds significant value. Crypto makes us trust AI, and AI makes blockchain smarter.
AI x Crypto systems can be divided into three layers: infrastructure layer, model layer, and application layer.
The infrastructure layer provides the computational and storage capabilities necessary for the efficient execution of models and applications. Projects such as io.net, Akash, APUS, PingPong, and numerous others fit into the infrastructure layer computing power category. Projects like 0G, Glacier, and SpaceAndTime, provide decentralized data storage for AI.
The model layer involves the algorithms and models used in AI systems. Model networks establish peer-to-peer inference networks or create new foundational models through community contributions. Projects like Bittensor, PIN AI, Cerbo AI, and Sentient fall into this category. On-chain AI, a subset of model networks, differs in that its inference results can be utilized in smart contracts, allowing them to make decisions with AI. Projects such as Ora, TheoriqAI, Nesa, and Modulus are advancing On-chain AI. They may use the infrastructure layer compute and storage providers to power these models.
AI applications, such as MyShell, Story Protocol, and Sleepless AI, package the lower-level layers into a cohesive consumer product.
AI x Crypto Infrastructure Layer
Decentralized Computing Power Projects: gather GPUs and CPUs from underutilized sources, such as independent data centers, crypto miners, and hardware networks like Filecoin and Render. They offer decentralized and cost-effective computing power, bypassing cloud oligopolists like AWS. Decentralized computing power addresses the increased GPU demand driven by AI and offers competitive pricing advantages. For example, an A100 on AWS is roughly $4.10 per hour, while io.net charges $0.76 per hour. Although decentralized computing generally offers lower quality than large data centers, this is beginning to change.
Decentralized Database/Filesystem/DA Layer: provides data storage for decentralized AI, enabling people to own, control, and utilize AI assets in a decentralized manner. Decentralized storage systems offer cost-effective storage solutions and promote a collaborative AI development environment. Key design challenges for decentralized storage systems include the economic model, storage verification algorithms, the degree of decentralization, and improving retrieval performance. These four factors are interrelated and involve trade-offs.
AI x Crypto Model Layer
Model Networks: establish a peer-to-peer model inference network that incentivizes the development of machine intelligence. Model networks facilitate openness and collaboration in AI. By tokenizing AI models and agents, enhances the quality of AI product outputs. They also help reduce AI costs and encourage the growth of small businesses.
On-chain AI Model Networks: enable smart contracts to make decisions with AI, giving blockchains the ability to perceive the physical world. AI model networks utilize ZKML (Zero-Knowledge Machine Learning), OPML (Optimistic Machine Learning), AI Oracles, and AIVM (Artificial Intelligence Virtual Machine) to ensure that AI inference is both trusted and accessible within blockchain smart contracts. Users can leverage AI for decision-making in smart contracts. For example, they can participate in DeFi projects and earn profits based on AI predictions, or use AI for facial recognition to enable smart contracts to identify individuals.
AI x Crypto Application Layer
Data Collection Dapps/Apps: use label-to-earn and contribute-data/bandwidth-to-earn mechanisms to gather data efficiently and cost-effectively while protecting contributors' rights. The data collection and labeling market is vast. Data collection apps use crypto incentives to create a trustless global labor market, reducing costs and enabling worldwide participation. They also employ gamification to make labeling tasks easier and more enjoyable.
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AI Dapps: package the infrastructure and model layers into a cohesive consumer product. Crypto AI platforms use asset tokenization to assist AI creators with funding challenges and enhance profitability. They establish a sharing economy for AI, create opportunities for new business models, and offer users a more secure and privacy-focused experience. There are several types of AI dApps and apps, including AI creator platforms, AI-enhanced social, gaming, and entertainment apps, AI apps for predictions, trading, AMM, and DeFi, as well as various AI tools.
Conclusion, Future Trends, and Social Impact
In conclusion, generative AI is set to drive significant business transformation in the next 50 years, fueled by substantial capital influx and rapid technological advancements. Crypto enhances AI by addressing centralized control, data privacy, and security issues, making AI more trustworthy and efficient. AI x Crypto intersection is still in its early stages and holds significant value. The infrastructure and model layers of AI x Crypto are relatively mature, but application development is still in its infancy. Significant opportunities exist for expanding the application layer to leverage the developed infrastructure and models.
Future trends in the AI x Crypto landscape include several key developments:
Decentralized Infrastructure: Innovations in decentralized computing power and data storage will reduce costs and enhance the efficiency and security of AI applications, bypassing traditional cloud providers.
Model Networks: Peer-to-peer model inference networks will promote collaboration and innovation in AI, reducing costs and enabling small businesses to participate in AI advancements.
On-chain AI: AI-driven smart contracts will enhance blockchain applications, including biometric authentication, fraud detection, and AI trading bots.
Data Collection Dapps: The integration of AI and crypto will make data collection more efficient and cost-effective, with projects focusing on gamified data labeling and enhanced user rights protection.
AI Dapps/Apps: New AI-driven decentralized applications will emerge across various sectors, offering enhanced security, privacy, and user experience through blockchain integration.
Regulatory and Ethical Considerations: Clear regulations and best practices will be essential for fostering innovation while protecting user rights and data privacy in the evolving AI x Crypto landscape.
The social impact of AI x Crypto could be significant over the next 50 years. Blockchain has reshaped the means of production, while AI is transforming production processes. We eagerly anticipate an unprecedented explosion as these two disruptive innovations collide. We envision a future where AI wields immense power, a power unsuitable for centralized control. This brings an urgent need to establish decentralized networks to govern larger AI systems, starting with computing power and data, and gradually extending to algorithms and applications.
Blockchain reshapes the means of production: Blockchain technology, with its distributed ledgers and smart contracts, enhances transparency and efficiency in asset management and transfer. For instance, blockchain can be applied in supply chain management to ensure that every stage, from production to sale, is traceable.
AI reshapes production processes: The application of AI in manufacturing, services, and other fields boosts production efficiency and accuracy. AI-driven automation systems can operate 24/7, reducing human errors and optimizing resource allocation.
Decentralized governance of AI: Decentralized networks, using distributed consensus mechanisms and transparent governance models, have the potential to mitigate the risks of AI centralization. Similar to blockchain, decentralized AI networks can establish transparent and fair governance structures through smart contracts, preventing any single entity from exerting excessive control over AI systems.
As the first and only crypto-focused VC bridging the East and West, Foresight Ventures is dedicated to being at the forefront of AI &crypto innovations. Foresight Ventures has invested in numerous infrastructure and model layer projects and is also excited about use cases such as personal AI assistants, privacy-preserving edge AI models, immersive virtual environment apps powered by AI and integrated with AR and VR technologies, and global labor markets for data collection and AI training.
About Foresight Ventures
Foresight Ventures is dedicated to backing the disruptive innovation of blockchain for the next few decades. We manage multiple funds: a VC fund, an actively-managed secondary fund, a multi-strategy FOF, and a private market secondary fund, with AUM exceeding $400 million. Foresight Ventures adheres to the belief of "Unique, Independent, Aggressive, Long-Term mindset" and provides extensive support for portfolio companies within a growing ecosystem. Our team is composed of veterans from top financial and technology companies like Sequoia Capital, CICC, Google, Bitmain and many others.
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This post is commissioned by Foresight Ventures and does not serve as a testimonial or endorsement by The Block. This post is for informational purposes only and should not be relied upon as a basis for investment, tax, legal or other advice. You should conduct your own research and consult independent counsel and advisors on the matters discussed within this post. Past performance of any asset is not indicative of future results.
Disclaimer: The Block is an independent media outlet that delivers news, research, and data. As of November 2023, Foresight Ventures is a majority investor of The Block. Foresight Ventures invests in other companies in the crypto space. Crypto exchange Bitget is an anchor LP for Foresight Ventures. The Block continues to operate independently to deliver objective, impactful, and timely information about the crypto industry. Here are our current financial disclosures.
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