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Recently on the YouTube channel "The Rollup", @TrustWallet CEO Eowyn Chen and @OpenledgerHQ core contributor Ram Kumar had an in-depth discussion about their collaboration. Here are some valuable insights: 1) Throwing Cold Water on the "Fat Wallet" Theory In the interview, Andy mentioned the popular "fat wallet" theory - that wallets with user registration channels can vertically integrate various services? However, Eowyn Chen's response was interesting. She frankly stated that B2C retail user business is actually very difficult, involving extensive customer support, higher security responsibilities, and frequent product route adjustments. Many people see Trust Wallet's 200 million downloads and think wallet business is lucrative, but the CEO herself emphasizes the pain of serving retail users. This suggests that a wallet's "fatness" isn't achieved simply by wanting it, and while user relationships are valuable, maintenance costs are also high. This perspective is quite realistic, revealing the true situation of many wallet service providers. More critically, she mentioned that not all value is concentrated at the front end, and value chain segments should develop fairly. This view somewhat throws cold water on the "fat wallet" theory and explains why Trust Wallet is willing to collaborate with infrastructure projects like OpenLedger. 2) Has the Turning Point for Specialized AI Arrived? Ram Kumar's judgment on AI development path is worth noting. He believes AI is evolving from generality to specialization, similar to how Google derived vertical applications like LinkedIn and YouTube from general search. ChatGPT-like general AI will be like an operating system, with more specialized models for specific use cases emerging in the future. This is consistent with my previous analysis of web3 AI industry trend evolution. Trust Wallet discovered that general models cannot solve specific problems in the crypto field, which precisely confirms this trend. Importantly, building specialized AI models requires high-quality vertical domain data, which is exactly what OpenLedger wants to solve. 3) The Dilemma of "Unpaid Labor" in Data Contribution Ram Kumar bluntly criticized AI as a "trillion-dollar industry built on unpaid labor". AI companies train models by scraping internet data, but data contributors don't get a share, which is indeed a structural problem. OpenLedger's solution is to let data contributors obtain long-term profit sharing from AI models, rather than selling data one-time. Combined with the wallet's global payment capabilities, this theoretically enables frictionless cross-border value distribution. However, a core issue remains: how to ensure data quality? Ram himself acknowledges that 90% of open-source contributions on platforms like Hugging Face are useless. If the contributed data itself has limited value, even the best incentive mechanism is futile. Eowyn Chen used the "gun rights" analogy for self-custody, emphasizing that AI functions are optional, and users can choose between convenience and security. This product philosophy is correct, but clearly presenting options tests product design capabilities. Ram also mentioned an interesting observation: crypto wallets might be the only way for users to receive data contribution rewards globally. This means wallets may evolve from mere asset management tools to digital identity and value distribution infrastructure. Note: To learn more, visit 's YouTube channel to watch this interview.

The Rollup
@therollupco
08-05
NEW EP: The New Era Of Distribution with Ram Kumar & Eowyn Chen In today's episode, @ayyyeandy sits down with @Ramkumartweet from @OpenledgerHQ and @EowynChen from @TrustWallet to explore: >The "Fat Wallet Thesis" vs Fat Protocol Theory >How Trust Wallet Plans to Integrate AI
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Disclaimer: The content above is only the author's opinion which does not represent any position of Followin, and is not intended as, and shall not be understood or construed as, investment advice from Followin.
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