In the development of artificial intelligence (AI) infrastructure, "computing power, algorithms, and data" are regarded as the three indispensable pillars. In the first two years since the launch of GPT, the deployment of computing power became the core narrative of AI infrastructure. Major companies have been investing in graphics cards and data centers, with various Web3 mining companies, represented by Coreweave, fully transforming into AI data centers. Subsequently, distributed computing power, represented by IO and Aether, became the focus of the industry. As the industry progresses, the bottleneck of computing power is no longer the most critical issue at this stage; the expansion on the edge side will be the new focus in this field. The value of blockchain in the computing power domain mainly lies in promoting user participation through token incentives.
The development of algorithms and models is currently the focus, especially with the release of DeepSeek V3, which has caused significant upheaval in the industry. Can the development in this field drastically reduce the costs of AIGC? When running ultra-large models, can a distributed structure be adopted to implement the model architecture in the face of constraints such as electricity and other resources? Additionally, can past frameworks like TEE, secure multi-party computation, federated learning, and homomorphic encryption, which combine privacy protection with distributed computing, be practical? These are key points for the current industry implementation. There are still not many valuable crypto projects in this area, but from the perspective of the entire AI industry, although the road is difficult, solutions can always be found.
The real challenge lies in the data layer—the lifeline of AI development. Do we really have enough clean data for training? Currently, all public domain data has basically been scraped clean by mainstream large companies, which has become the key to Crypto potentially changing the AI industry.
Ensure high-quality, clean training data.
Break down data silos, especially the barriers of private domain data, to achieve data flow while protecting privacy and authenticity.
This is precisely where the Web3 project Roam—a Depin project, decentralized wireless network—makes breakthroughs. Roam's globally open wireless network not only promotes connectivity but also transforms private domain data into accessible and privacy-protected AI usable datasets, turning them into foundational AI data that can be called upon.
How Roam Disrupts Data Acquisition
Roam's innovation lies in addressing one of the most pressing data challenges for AI: the inaccessibility of operator-level data. Traditionally, telecom companies possess rich data related to time, location, and users. However, due to structural barriers, even tech giants like Google and Meta find it difficult to access these datasets. Instead, these companies choose to create their own ecosystems, such as iOS and Android, exacerbating data monopolization and fragmentation. In the AI era, this monopoly hinders comprehensive model training and global data integration.
With the support of the Wireless Broadband Alliance, WiFi Alliance, and GSMA member units, Roam has developed the Global WiFi OpenRoaming + eSIM Top Up product. Starting with the construction of a new generation of WiFi OpenRoaming networks, it builds a new type of network that is free, secure, and globally roamable. At the same time, leveraging its position as a top global eSIM traffic supplier, it transforms previously paid, closed operator services into an open, globally integrated new network. Users participating in the OpenRoaming construction receive free eSIM traffic rewards, and when users travel to any country, the eSIM Top Up product allows their traffic to automatically convert to local traffic. Ultimately, whether at home or on the road, whether in their resident country or traveling, users have a network that they can automatically log into with their on-chain DID, open and without ever paying expensive roaming fees. Compared to traditional operators and even some Web3 operators' business models, Roam represents a truly multinational, cross-linking future operator model. AI companies find it nearly impossible to gain support from all traditional operators and major internet/mobile companies to train specific models. However, Roam opens a channel to provide operator services through WEB3, and in return, the data generated in this process, under privacy protection, can become a data source for all AI companies.
Roam provides a mechanism for how Web3 can change data generation and management, thereby breaking the private domain data barriers encountered by AI and achieving the real flow of traditional private domain data. The transformation of business models often leads to rapid evolution; by Q4 2024, Roam has become one of the largest decentralized physical infrastructure (DePIN) projects globally. The Roam Discovery Program further expands boundaries by integrating multiple DePIN ecosystem partners to enrich AI training datasets. Roam can not only provide operator-level data to AI but also collaborate with ecosystem partners to provide weather data, CDN data, energy data, authentication data, payment and lending data, and even data on AI agents' social interactions, payments, and operational status to AI models.
In addition to breaking traditional business models and opening a path to utilize WEB3 to provide a large amount of previously confined data for AI society, Roam also has some additional important contributions to the data layer of AI infrastructure.
Firstly, the security and privacy protection of cross-device and cross-regional data. The core technology of Roam is to upgrade public WiFi to a secure login model combined with DID. At the same time, it achieves cost-free roaming of WiFi and eSIM integrated networks. The user's blockchain private key, DID private key, WiFi OpenRoaming certificate, and the certificates behind eSIM are all unified and coordinated. All of this can be managed and encrypted through a TEE-based KMS (Key Management System) within Roam's existing devices. Roam's data interactions comply with W3C DID and verifiable credential standards, and combined with ZK technology, it can alleviate concerns about data security. Roam's technical team has also done some of the earliest work in the world to combine blockchain-based digital identity with eSIM, WiFi, and Bluetooth chips.
Secondly, leveraging these new multidimensional spatial data such as time, space, and identity to help analyze which data is generated by real society and which is produced by AI. A combination of Roam's 3W data (Who, When, Where) along with payment data generated by WiFi fingerprint payment terminals, combined with markers from different data collection devices, can ensure that this data is not generated by AI but is produced by real life. A similar broad-spectrum, multidimensional spatial data evaluation system is key to ensuring the value of AI training data. Roam's R&D team has a long-term accumulation of 10 years in this field.
Thirdly, it facilitates AI agents to expand into new living spaces and generate new data. They currently exist in Twitter and TG, but with Roam's help, they can inhabit various smart home devices. The core support Roam receives from industry giants like Samsung is that these companies' devices are almost all WiFi devices. Currently, the only way these devices connect to the network is through manual input of usernames and passwords, which is very insecure and not automatic. In Roam's world, AI agents, people, and devices are all uniformly marked with DID. They all have corresponding WiFi OpenRoaming certificates. This builds a network foundation for AI agents to automatically transition from the internet world to the IoT world. During the process of an AI agent moving from one device to another, all data generated is encrypted and protected by its private key with the help of TEE, and combined with OpenRoaming WiFi and blockchain, secure transmission and distribution can be achieved. The entry of AI agents into the IoT world while achieving cross-domain data interoperability means they can truly become companions to humans. Human interaction with them no longer requires humans to focus on a screen. Regardless of the scenario, they can record in real-time, respond quickly, and simultaneously construct a true avatar of humans. This is also the first step in the transition of human physical existence to silicon-based civilization.
Roam, with its open and secure global network, redefines the data infrastructure of the AI era. From breaking traditional operator models to supporting the construction of the AI data layer, Roam is driving the deep integration of AI society and Web3 through dual innovations in technology and business models. In this transformation led by Roam, we not only see a significant enhancement in global network services but also the emergence of the early forms of silicon-based civilization.
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