Join AI researcher and enthusiast in the crypto space, guest_name_1, as he discusses the convergence of AI and blockchains/crypto. Topics covered include deep fakes, proof-of-humanity, big data, language models, user control, privacy, security, zero knowledge, media, art, and more.
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Quick takeaways
AI can benefit from crypto by acting as a decentralized counterweight to the centralizing force of AI models.
Crypto can benefit from AI in various ways, such as using AI to generate code and leveraging zero-knowledge proofs for secure and private computations.
AI and crypto can work together to enhance trust, security, and integrity within the crypto sphere.
Deep dives
AI and crypto as opposing technologies
Crypto and AI are two technologies that oppose each other while also complementing each other. AI thrives on top-down centralized control, while crypto enables bottom-up decentralized cooperation. The tension between centralization and decentralization is a major theme in their interaction. AI can benefit from crypto by acting as a decentralized counterweight to the centralizing force of AI models that rely on more data and complex models. On the other hand, crypto can benefit from AI in various ways, such as using AI to generate code, leveraging zero-knowledge proofs for secure and private computations, and utilizing machine learning to detect and prevent suspicious transactions and minor extractable value (MEV) in blockchain networks.
Decentralizing AI and the technical challenges
One potential application is the decentralized compute aspect of AI, where anyone can contribute GPU compute power to train machine learning models. However, there are technical challenges in terms of verifying the correctness of the training process and coordinating a large community of contributors. Zero-knowledge proofs can help with verifying training correctness, while game-theoretic approaches can address the coordination challenges. Another area where AI can help crypto is in building decentralized social networks that prioritize user control and privacy. Machine learning and AI algorithms can be used to curate content and filter spam in these social networks, providing users with choices and personalized experiences. However, challenges exist in terms of ensuring user privacy and developing effective recommendation algorithms.
AI and crypto in enhancing trust and security
AI and crypto interact in the realm of trust and security. AI can aid in detecting suspicious transactions and providing early warnings to users, enhancing the security and integrity of crypto transactions. Moreover, AI can play a role in defending against minor extractable value (MEV) in blockchain networks by identifying potential MEV opportunities for attackers and enabling users to protect themselves. On the other hand, crypto can help combat the problem of deep fakes by leveraging blockchain timestamps and trusted hardware to verify the authenticity of recorded data. This can be particularly useful for high-profile figures like politicians. Overall, AI and crypto can work together to enhance trust, security, and integrity within the crypto sphere.
Decentralized Marketplace for Sourcing Data and Training Models
There is an opportunity to decentralize the process of sourcing data for training machine learning models. This can be achieved by creating a marketplace where individuals can contribute new data to a large data set used for training models. However, there are challenges in verifying the authenticity and quality of contributed data. To address this, a combination of technological and social solutions, such as reputation metrics, may be necessary. By enabling the contribution of unique data from various sources, this decentralized marketplace can improve the coverage of the data distribution, leading to more comprehensive models and better performance.
Creating Incentives for Contributing Machine Learning Models
Similar to the marketplace for data, a decentralized marketplace can also incentivize the contribution of machine learning models. By creating a platform where models can be evaluated and proven to solve specific problems, contributors can be rewarded for their contributions. However, ensuring the authenticity and security of these models remains a challenge. Techniques like zero-knowledge proofs can be utilized to verify the performance and integrity of these models without revealing proprietary information. This approach can foster the emergence of open, transparent marketplaces that empower a broader community to participate in AI development, countering the dominance of centralized tech companies.
This week's all-new episode covers the convergence of two important, very top-of-mind trends: AI (artificial intelligence) & blockchains/ crypto. These domains together have major implications for how we all live our lives everyday; so this episode is for anyone just curious about, or already building in the space.
The conversation covers topics ranging from deep fakes, bots, and the need for proof-of-humanity in a world of AI; to big data, large language models like ChatGPT, user control, governance, privacy and security, zero knowledge and zkML; to MEV, media, art, and much more. Our expert guests (in conversation with host Sonal Chokshi) include:
Dan Boneh, Stanford Professor (and Senior Research Advisor at a16z crypto), a cryptographer who’s been working on blockchains for over a decade and who specializes in cryptography, computer security, and machine learning -- all of which intersect in this episode;
Ali Yahya, general partner at a16z crypto, who also previously worked at Google -- where he not only worked on a distributed system for a fleet of robots (a sort of "collective reinforcement learning") but also worked on Google Brain, where he was one of the core contributors to the machine learning library TensorFlow built at Google.
The first half of the hallway-style conversation between Ali & Dan (who go back together as student and professor at Stanford) is all about how AI could benefit from crypto, and the second half on how crypto could benefit from AI... the thread throughout is the tension between centralization vs. decentralization. So we also discuss where the intersection of crypto and AI can bring about things that aren't possible by either one of them alone...
pieces referenced in this episode/ related reading:
As a reminder: none of the following should be taken as investment, legal, business, or tax advice; please see a16z.com/disclosures for more important information -- including to a link to a list of our investments – especially since we are investors in companies mentioned in this episode.
Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.
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