Auki's Posemesh: A Decentralized Network for Machine Perception

A year ago, the Tor Project made a significant decision to remove all ATOR Relays from their network, which sparked a vision for a new decentralized future. Instead of surrendering, the team aimed to create a self-scaling, trustless network designed to enhance privacy for users worldwide. Their goal is to disrupt the VPN market by combining speed, reliability, and user-friendliness through bespoke hardware, ultimately making private browsing accessible to billions. This vision has now materialized with the launch of the Anyone Network, which boasts an impressive 5000 active relays, establishing itself as one of the largest and fastest mixnets globally. Reflecting on the past year, the team expresses gratitude to their community for their unwavering support during challenging times. Despite the difficulties, the project demonstrated resilience and strength, showcasing the power of decentralization and community alignment. The leadership and engineering teams remained intact throughout the transition, empowering former community members to take on more significant roles within the ecosystem. The project has evolved into an open-source initiative, expanding from a single Smartweave registration protocol to over 30 active repositories contributing to blockchain technology, privacy, hardware, and applications. Looking ahead, the team acknowledges the journey is far from over, with plans to further decentralize the network following the transition to their AO distribution protocol. They emphasize that community governance will play a crucial role in maintaining the network's safety and performance. The spirit of ATOR is now emblematic of overcoming setbacks in the Web3 space, and the team is committed to transparency through regular updates. As they tackle the larger challenge of global privacy adoption, they remain dedicated to building a Web3 ecosystem that has the potential to transform lives.

Retrieval-augmented generation (RAG) has emerged as a pivotal method for integrating large language models (LLMs) into specialized business applications, enabling the infusion of proprietary data into model responses. Despite its effectiveness during the proof of concept (POC) phase, developers often face significant accuracy drops when transitioning RAG into production. This issue is particularly pronounced during the retrieval phase, where the aim is to accurately fetch the most relevant context for a given query, a metric known as context recall. This article delves into strategies for enhancing context recall by customizing and fine-tuning embedding models, ultimately improving RAG's performance in real-world applications. RAG operates in two main steps: retrieval and generation. In the retrieval phase, the model converts text into vectors, indexes, retrieves, and re-ranks these vectors to identify the top matches. However, failures in this phase can lead to missed relevant contexts, resulting in lower context recall and less accurate generation outputs. One effective solution is to adapt the embedding model, which is designed to understand relationships between text data, to produce embeddings that are specific to the dataset being used. This fine-tuning allows the model to generate similar vectors for similar sentences, enhancing its ability to retrieve context that is highly relevant to the query. To improve context recall, it is essential to prepare a tailored dataset that reflects the types of queries the model will encounter. This involves extracting a diverse range of questions from the knowledge base, paraphrasing them for variability, and organizing them by relevance. Additionally, constructing an evaluation dataset helps assess the model's performance in a realistic setting. By employing an Information Retrieval Evaluator, developers can measure metrics like Recall@k and Precision@k to gauge retrieval accuracy. Ultimately, fine-tuning the embedding model can lead to substantial improvements in context recall, ensuring that RAG remains accurate and reliable in production environments.

On November 22, 2024, the Sui Foundation announced a strategic partnership with Franklin Templeton Digital Assets, aimed at driving innovation within the Sui blockchain ecosystem. This collaboration is set to enhance the development of Sui, a Layer 1 and smart contract platform, by creating value opportunities for builders of blockchain-based solutions. Jameel Khalfan, Head of Ecosystem Development at Sui, highlighted that the partnership is a validation of Sui's technology, which was inspired by challenges in decentralized finance that Franklin Templeton is addressing. Franklin Templeton Digital Assets has been actively involved in blockchain technology for several years, focusing on building solutions, running node validators, and developing investment strategies. Their dedicated digital assets research team employs tokenomic analysis and data science insights to guide product development and investment decisions. Tony Pecore, SVP and Director of Digital Asset Management at Franklin Templeton, expressed excitement about the advancements being made by the Sui team, noting that blockchain technology has often faced technical limitations despite its growing interest. The Sui ecosystem is already home to innovative projects such as DeepBook, a decentralized finance solution akin to a central limit order book, and Karrier One, which supports a decentralized mobile network. Additionally, Sui has recently launched native USDC, providing users with direct access to a widely used stablecoin while mitigating risks associated with bridged assets. As a secure and scalable platform, Sui is positioning itself as a premier destination for application builders across various sectors, including gaming, DeFi, and tokenized securities.

Verida recently achieved a significant milestone by securing second place in the POL Rush Competition, hosted by Polygon during the Aggregation Summit in Bangkok. This recognition awarded Verida 200,000 $POL and highlighted the company's innovative efforts in bridging Web2 user data with AI agent builders. CEO and Co-Founder Chris Were presented Verida's vision on the main stage at Devcon 2024, emphasizing the transformative potential of their technology. This achievement not only showcases Verida's progress in addressing the challenge of secure and private access to personal data but also reinforces its commitment to connecting Web2 and Web3, thereby unlocking new opportunities in the AI landscape. Verida is positioning itself as the "private data on-ramp for AI," allowing users to easily extract personal data from various Web2 sources, including emails, chats, and healthcare data, and connect it to AI agents and data marketplaces. With three years of dedicated development, the Verida Network prioritizes user privacy and data sovereignty, ensuring that all personal information remains secure and under the user's control. The positive feedback from developers and AI enthusiasts at Devcon indicates a strong demand for seamless access to personal data, with Verida ensuring compliance with global standards like GDPR and HIPAA. The conference also highlighted a growing trend towards Trusted Execution Environments (TEEs), which are becoming essential for secure computing. Verida's collaboration with ecosystem partners like TEN and Nillion emphasizes its mission to prioritize data ownership and privacy. With a unique market opportunity as the only project focused on unlocking personal data for AI applications, Verida is well-positioned to lead in this evolving space. The combination of winning the POL Rush competition, positive developer engagement, and interest from AI companies suggests that Verida is at the forefront of a significant shift in how personal data is approached in the AI era.

Aethir is making significant strides in the blockchain space by integrating LayerZero to enhance its capabilities as a multichain AI and gaming ecosystem. This integration aims to bring the omnichain vision closer to reality, allowing for seamless interactions across different blockchain networks. Aethir’s native token, $ATH, will be available for testing on ZKSync, as announced on the platform's official X account. The integration with LayerZero will facilitate cross-chain operations, enabling users to move $ATH tokens effortlessly between various chains, thereby expanding the utility of the token within the ecosystem. The Aethir platform is built on a robust decentralized cloud infrastructure that supports AI and gaming applications. With over 43,000 high-quality GPUs, including more than 3,000 NVIDIA H100s, Aethir is well-equipped to handle complex AI computations. The network also features over 32,000 globally distributed Aethir Edge devices, enhancing its computational capabilities. The $ATH token plays a crucial role in this ecosystem, allowing stakeholders such as Aethir Checker Nodes, Edge device operators, and cloud hosts to participate in the network's growth and functionality. The collaboration with LayerZero will enable Aethir to transition to the Sophon ZK chain, enhancing its multichain capabilities and facilitating the execution of smart contracts across different blockchains. To further bolster its GPU cloud infrastructure, Aethir is also integrating Stargate’s omnichain liquidity protocol, which will simplify the exchange of $ATH tokens. This integration will provide access to unified liquidity pools, instant finality, and various staking and farming options. These advancements are designed to propel Aethir into a multichain future, ensuring that AI and gaming workloads can be accessed directly across multiple blockchain networks. As Aethir continues to innovate, it is set to play a pivotal role in the evolution of decentralized cloud solutions for the AI and gaming sectors.

The Graph, a decentralized indexing protocol that functions similarly to Google for blockchains, has unveiled a new data standard for Web3 known as GRC-20. This initiative aims to enhance the way information is structured, shared, and interconnected across decentralized applications. The announcement coincided with developer Yaniv Tal's Graph Improvement Proposal, which emphasizes the importance of knowledge graphs in creating a more comprehensive understanding of data by linking and labeling information. The GRC-20 standard is set to replace the existing Resource Description Framework (RDF), which has been deemed inadequate for the needs of Web3 due to various technical limitations. The GRC-20 standard introduces core concepts such as Spaces, Entities, Relations, and Types, which will allow developers to define and organize their data more effectively. This new framework is designed to foster a common language for knowledge, ultimately striving to fulfill the vision of an open, verifiable, and composable Web3. The Graph plans to release a suite of tools in the coming weeks to assist developers in implementing the GRC-20 standard. The Graph Improvement Proposal is currently open for community feedback before it is finalized, highlighting the project's commitment to collaborative development. Since its launch in 2018 and the activation of its mainnet in December 2020, The Graph has established itself as a vital resource for developers, enabling them to create decentralized applications (DApps) more efficiently. The platform claims it can significantly reduce development time from months to mere days. With over 70 blockchains indexed, The Graph continues to evolve, recently partnering with Chainstack to provide a hosted service for subgraphs, further enhancing accessibility and usability for developers in the blockchain ecosystem.