Investment firm cyber.Fund, recognized for early support of Ethereum (ETH), has committed $100 million to projects at the convergence of blockchain technology, artificial intelligence (AI), and the Internet of Things (IoT). cyber.Fund, known for previous investments in Cosmos, Solana, and Polkadot, aims to cultivate the growth of the “cybernetic economy,” where blockchain serves as the foundational element.

Defined by cyber.Fund as an interconnected and automated economic framework, the cybernetic economy integrates blockchain, AI, and IoT. This move aligns with the rising popularity of AI-based tokens within the cryptocurrency industry, propelled by the success of mainstream AI tools like ChatGPT.

The increasing synergy between blockchain and artificial intelligence has prompted predictions of an imminent bull cycle. Konstantin Lomashuk, co-founder of cyber.Fund, expressed the firm’s readiness to lead in this transformative era, emphasizing their commitment to being at the forefront of the cybernetic economy’s evolution.

By directing substantial investment into projects at the intersection of blockchain, AI, and IoT, cyber.Fund aims to propel advancements in these fields and shape the trajectory of the cybernetic economy.

AI and Crypto: Exploring New Frontiers

Coinbase’s research report in June highlighted the significant opportunity at the intersection of artificial intelligence and blockchain. The report underscored the potential to create innovative solutions for societal challenges presented by AI by combining both technologies.

David Duong, head of research at Coinbase, emphasized the maturation of applications within AI and blockchain, leading to collaborative areas and new use cases for crypto in addressing specific societal challenges posed by AI.

The report identified decentralized data marketplaces as a potential use case, addressing the demand for a verified and diverse set of data to train AI models. Token-based incentive mechanisms were proposed to enhance data quality sourced from these marketplaces.

Additional use cases included providing computational power from decentralized networks using graphics processing units for AI projects, improving data authenticity, making AI algorithm decision-making processes auditable, and addressing issues like algorithmic bias and digital identity verification.

Blockchain’s transparency potential was highlighted to scrutinize the logic and reliability of AI-produced outcomes, tackling challenges such as disinformation risks and establishing the provenance of digital media through non-fungible tokens.