Is AI "going down" an opportunity for Web3?
TechFlow Selected TechFlow Selected
Is AI "going down" an opportunity for Web3?
Only when AI truly "sinks down" to every device will decentralized collaboration transform from a concept into a necessity?
Navigating Web3 tides with focused insightsBy Haotian
Recently, observing the AI industry, I've noticed an increasingly "downward" shift: a new trend is emerging that favors local small models and edge computing, diverging from the previous mainstream consensus centered on competing for computational power and large-scale models.
This shift is evident in Apple Intelligence reaching 500 million devices, Microsoft launching Mu—a compact 330-million-parameter model dedicated to Windows 11—and Google DeepMind's robots operating offline, among other examples.
What changes does this bring? Cloud-based AI competes on parameter scale and training data, where financial spending power becomes the core advantage. In contrast, on-device AI emphasizes engineering optimization and scenario-specific adaptation, advancing further in privacy protection, reliability, and practical usability—especially critical as hallucinations in general-purpose models severely hinder penetration into vertical applications.
This shift actually opens greater opportunities for web3 AI. When competition was about general-purpose capabilities (computation, data, algorithms), dominance by traditional tech giants was inevitable. Attempting to apply decentralization concepts to compete with companies like Google, AWS, or OpenAI seemed unrealistic due to lack of resource, technical, and user advantages.
But in a world of localized models and edge computing, the landscape for blockchain-powered AI services changes dramatically.
When AI models run directly on users' devices, how can we prove outputs haven't been tampered with? How can model collaboration occur while preserving privacy? These are precisely the strengths of blockchain technology...
Notably, several emerging web3 AI projects are addressing these challenges. For example, Lattica—the data communication protocol recently launched by @Gradient_HQ with a $10M seed round led by Pantera—aims to tackle data monopolies and opacity in centralized AI platforms. @PublicAI_'s EEG device HeadCap collects real human brainwave data to build a "human verification layer," already generating $14M in revenue. These efforts are fundamentally tackling the issue of trustworthiness in on-device AI.
In short: only when AI truly "descends" to every individual device will decentralized collaboration evolve from a concept into a necessity?
#Web3AI projects—instead of continuing to fight over general-purpose AI—should seriously consider how to provide infrastructural support for the wave of localized AI?
Join TechFlow official community to stay tuned
Telegram:https://t.me/TechFlowDaily
X (Twitter):https://x.com/TechFlowPost
X (Twitter) EN:https://x.com/BlockFlow_News
Haotian | CryptoInsight
