Annihilate的A8之路

The oracle has never been a technical issue of 'feeding a price', but rather an institutional issue of 'who is responsible for the data'. Traditional solutions rely on centralized APIs or DAO voting updates, the former can easily be targeted or crash in extreme market conditions, while the latter often falls into governance paralysis during high volatility. The fundamental breakthrough of Pyth Network lies in returning to first principles: price is not 'who reports it fastest', but 'who bears the market risk' — the true market price can only be produced by market makers, exchanges, and high-frequency trading firms that bear losses and gains in real money, and ensure their honesty through economic incentives and slash penalty mechanisms. Pyth is not an aggregator, but a 'risk-bearing alliance' that entrusts the production rights of price data to those who are least likely to lie.

OpenLedger aims to do more than just "attach blockchain to AI"; it seeks to reorganize three heterogeneous resources—data, models, and computing power—into a chain-based production relationship that can be priced, settled, and combined. Its underlying structure uses a layered ledger: the first layer is a rapid consensus based on Tendermint, used to write contribution hashes and revenue distribution instructions; the second layer is a verifiable storage area composed of a multi-chain DA network, storing desensitized data fragments, model weight differences, and computing node operation logs; the third layer is a heterogeneous execution environment bridge that maps external contract calls from Ethereum mainnet, Arbitrum, Sui, etc., to a unified event format using light clients and ZK proofs, ensuring consistency in cross-ecosystem revenue settlement. To reward "contribution" rather than "noise," OpenLedger has introduced a PoC (Proof of Contribution) scorecard: it maps indicators such as the accuracy improvement of the dataset, QPS enhancement of model inference, and the stability and energy efficiency of computing nodes to a weight range of 0–1, incorporating a time decay function to prevent one-time contributions from long-term exploitation. All contributions are divided into minimal atomic NFTs, supporting splitting, transfer, and merging, meaning a segment of annotation script or a model fine-tuning can be freely traded in the secondary market. Revenue settlement employs a "streaming profit-sharing" model, where each round of inference triggered by the caller results in micro-payments of OPEN tokens, with settlements made to corresponding NFT holders upon contract expiration, significantly reducing the risk of arrears and confusion associated with traditional royalty models. On the compliance front, OpenLedger uses verifiable credentials (VC) to label data owners with a "usable range" tag and confirms whether calls exceed authority using zero-knowledge boolean proofs, achieving "usable but invisible". For investors, the greatest imagination of this chain lies not in token prices but in the potential to incubate a truly meaningful "AI version of the App Store": data producers sell data fragments like songs, developers can pay to call as needed, and the final long-tail revenue is automatically distributed by the code. If this model takes hold, the profit structure of the AI industry chain will be completely rewritten—data and algorithms will shift from cost centers to tradable assets, inference services will transition from single platforms to multi-party markets, and the industry's moat will transform from "scale monopoly" to "contribution compounding."@OpenLedger #OpenLedger $OPEN

If we see social interaction of agents as an 'application', it will quickly be dragged along by the cycles of traffic and subsidies; if we turn it into an 'operating system', creators, developers, and brands can embed their production functions into it. The key for developers is modularization: roles and memory templates, scene scripts and state machines, pluggable tools and skills (retrieval, generation, payment, permissions), as well as standardized evaluation and listing processes. A friendly SDK should be compatible with multi-model inference and external tool calls, providing an integrated channel for intent—routing—settlement; the sandbox and playback framework should be able to replay 'extreme moments' (sudden hotspots, on-chain congestion, bulk listing) to verify reliability. For brands and institutions, the 'digital twin' and 'scene store' should be able to reuse the above modules and gain an audit perspective, achieving both 'can chat' and 'can manage'.

Somnia has positioned itself as a “Layer-1 born for games and interactive entertainment” since its inception, aiming to support real-time loads similar to Web2 servers on the blockchain. The proposed MultiStream parallel consensus splits validators into several independent streams, each processing transactions that are then ordered and merged by a coordination layer, theoretically achieving a TPS limit in the millions; combined with the native database IceDB and a native compilation execution environment, the official claim is an average confirmation time of less than 1 second. Behind the seemingly stunning data, there are three key engineering challenges: First, how to resolve cross-stream dependencies? In real applications, the assets of the same player often update across multiple data streams, and if there is a delay in inter-stream synchronization, read-write conflicts will arise. Somnia's approach is to maintain a “conflict domain” for each account, adding a timestamp lock upon writing and batch reordering, but whether this is sufficient in high-concurrency PvP scenarios still requires stress testing for validation. Second, can the node layer handle massive I/O? IceDB uses an improved LSM-tree structure to reduce random writes, but a million TPS means index bloat and disk jitter; without hardware threshold limitations, this could lead to node centralization. Third, data availability and sharding recovery strategies. Somnia plans to collaborate with service providers like Google Cloud to provide backup shards, but the absence of external DA solutions means that if the storage layer fails, the path for rapid recovery of on-chain state has not been fully disclosed. Nevertheless, Somnia has done extensive homework on composability: Solidity compatibility, EVM RPC endpoints, and consistent serialization ABI allow existing toolchains to migrate seamlessly; while the “timeline” semantics of on-chain events and block indexes simplify the difficulty of synchronizing world states for multiple users. In summary, if Somnia's technical blueprint can be realized, it will provide near-real-time infrastructure for metaverse applications; however, performance metrics must be validated in public testnets and large-scale real interactive scenarios to turn “laboratory results” into community consensus.

Network effects arise from multi-party participation: the more data providers there are, the more robust the model training; the more diverse the models, the easier it is for application developers to find suitable tools; the greater the usage, the income of computing nodes increases accordingly, thus attracting more computing power to join. To get this flywheel started, OpenLedger proposed a unique hyperbolic incentive function: when the revenue from a single piece of data or a single model is not enough to cover the validation costs, the protocol will exponentially subsidize the gap from the reserve fund; once the revenue exceeds the cost threshold, the subsidy coefficient rapidly decays to avoid sustained inflation. Meanwhile, the supply curve of the token OPEN is not linear, but bound to the "effective usage amount"; if the usage amount for the month does not reach the preset growth rate, the reserve will automatically be halved for release, and the newly issued OPEN for the next month will decrease synchronously; conversely, if the usage exceeds the target, the excess net income will be used for secondary market repurchase and destruction, forming elastic deflation. This move aims to synchronize the token value strongly with the real usage of the network, reducing the damage caused by "pump-dump" on ecological stability. In terms of governance, OpenLedger adopts a tripartite separation of powers: the technical council holds the right to propose protocol upgrades, the economic council is responsible for rate and subsidy curve adjustments, and the community council has the veto power over the first two councils. The voting rights of the three council members are calculated based on a weighted method of "holding amount × contribution points", and a 14-day cooling-off period is set to prevent lightning proposals. For key parameters—such as PoV score threshold, storage rental rate, minimum balance of risk capital—any modification requires a ⅔ supermajority across councils and locks a 30-day observation window to maximize the predictability of the system. In terms of external cooperation, OpenLedger has reached a preliminary consensus with the decentralized GPU network Render, the federated learning platform Flower, and the legal tech company Kleros to jointly develop "verifiable federated fine-tuning" and "on-chain arbitration" modules, which, once launched, will further solidify its position as a public facility for data financialization. Overall, OpenLedger attempts to make OPEN a truly native asset linked to data productivity through a combination of "flexible monetary policy + multi-party governance + scenario-driven" approaches. If it can complete the infrastructure loop before the next round of crypto-AI narrative explosion, the value capture space of OPEN may not only be limited to the crypto market but could extend to a broader digital economy landscape.@OpenLedger #OpenLedger $OPEN

Among the many DeFi protocols centered around "lending + leverage," @Dolomite has a unique positioning: it is not a simple replication of the liquidity pool model of Aave/Compound, but rather based on a "composite margin account" that integrates spot, lending, LP shares, and even options positions under the same collateral and liquidation engine. This design is inspired by the Prime Brokerage thinking found in derivatives exchanges: users can layer various positions in a unified account, with risk dynamically assessed by a real-time asset weight matrix rather than being calculated in isolation based on a single collateral limit. Thanks to EVM atomic transactions, when the account's health factor falls below the threshold, liquidators can close multiple market paths in a single transaction, significantly reducing slippage losses caused by "forced liquidation - rebuilding positions," and allowing the protocol to maintain a more stable bad debt ratio in high volatility scenarios. In the most recent market shock test (Arbitrum circuit breaker incident), the system processed over 2,600 liquidations within 40 minutes, with zero bad debts, demonstrating that its risk engine has withstood validation under extreme market conditions.

At the moment when RWA narratives gradually transition from concept to large-scale implementation, the proposal given by @Plume - RWA Chain is not merely about packaging real assets into ERC-20 tokens, but rather attempts to rewrite the underlying logic of the “asset-compliance-liquidity” trinity. It breaks the chain into three layers: identity gateway, asset ledger, and settlement hub: the identity gateway connects in real-time with global KYC/AML providers, issuing zero-knowledge credentials to users or institutions after successful verification; the asset ledger encapsulates cash flow schedules and legal metadata for different assets such as bonds, receivables, and carbon credits using modular templates, ensuring that any “corporate action” automatically generates on-chain events for traceability by custodians and auditors; the settlement hub introduces dual-layer liquidity pools, first completing net settlement of homogeneous assets in a permissioned subnet, and then aggregating the balance onto the mainnet for cross-chain settlement, significantly reducing capital occupancy for transaction matching. This approach of embedding “compliance checks” into system calls provides institutions with predictability akin to traditional finance while retaining on-chain composability, becoming the key to differentiating itself from other projects in the same space.

The Ethereum mainnet has addressed ownership verification, but has made real-time interaction and high concurrency a luxury; various sidechains and Rollups sacrifice composability for throughput; while #Somnia 's ambition is to bring the 'real-time virtual world' onto the blockchain without severing composability. Its core idea is 'two-layer mapping, three-layer synchronization'. The underlying layer uses parallel EVM sharding to provide atomic settlement, with each shard responsible for a set of spatial blocks and time slots, ensuring local transactions are settled in seconds; the middle layer utilizes a DAG-based state mirroring protocol to aggregate shard roots into a global snapshot, allowing any node to obtain the world state with at most 2 seconds of delay in constant time; the top layer pushes player actions, physics engine events, and asset changes to subscribers in real-time through verifiable P2P broadcasting, forming a dual-track logic of 'on-chain logic + off-chain rendering'. In this way, developers can leverage the mature ecosystem of Solidity without worrying about gas surges caused by TPS breakthroughs.

If traditional chain games are like an isolated island, then open immersive worlds are more like a continuously growing city: assets need to be transferable, rules need to be reusable, and the economy must be self-sustaining. To support this 'living system', the underlying structure must engineer three things: content, state, and settlement: asset standards must support combination and splitting, world states must be able to be copied and replayed at low cost, and value distribution must be based on verifiable usage evidence rather than 'platform will'. Otherwise, the popularity of 'playable' experiences will quickly be consumed by the friction of 'unsustainable'. A healthy tech stack should at least provide modular 3D/semantic asset specifications, event-driven world state logs, and accountable settlement channels for creators and operation nodes, allowing creation and operation to combine like building blocks, rather than 'rebuilding the city' each time.

　　

In the traditional Web2 model, once user data is uploaded, it is locked by the platform, and the distribution of profits and the fate of revisions are decided by the operators. The charm of digital avatars lies precisely in the fact that 'personality is portable and data can flow back.' This protocol uses an on-chain traceable 'contribution fingerprint' system to record every training and fine-tuning of the AI personality: annotators upload emotional dialogues that generate hash signatures, and algorithm tuners submit differential weights that similarly map addresses. These fingerprints are then transformed into inheritable signature chains, and when the avatar is invoked by a third party, royalties are automatically split according to the fingerprint weights, resolving the problem of profit attribution for multi-contributor personalities.

In the conception of @Holoworld AI #HoloworldAI , social interaction is not a repackaging of the 'content stream', but rather a triadic system of 'agents - scenes - relationships': users and creators not only post messages but also engage in dialogue, co-creation, and transactions through orchestrable multimodal agents. This requires underlying capabilities for sustainable memory, verifiable identity, and high-concurrency reasoning. Engineering-wise, a robust stack should include: vector memory for retrieval and long-term preferences; auditable conversation and action logs; and a one-time call channel that atomizes 'update + use', reducing the risks of race conditions and content mismatches caused by read-write inconsistencies. Furthermore, content provenance and watermarking pipelines should become default configurations, solidifying the generation link (models, prompts, material licenses) into verifiable metadata, which protects creators and provides the platform with forensically sound 'materials science' for compliance.

The open boundaries of Web3 have brought the cost of identity fraud close to zero, with behaviors such as exploiting opportunities and vote manipulation closely intertwined. Mitosis views Sybil defense as a prerequisite for consensus security and governance credibility, proposing a three-dimensional model of 'Two Mirrors and One Chain': behavioral mirror, relational mirror, and appeal chain. The behavioral mirror focuses on the time series characteristics of on-chain data, utilizing machine learning to detect rhythms, paths, and fund reuse between addresses; once a high similarity cluster is detected, the system automatically reduces its incentive weight and places it on an observation list. The relational mirror analyzes the interaction density and hierarchical structure between addresses through privacy-friendly graph computing, using weighted Pagerank to distinguish between 'highly trusted communities' and 'temporarily assembled matrices'. Cross-validation of behavior and relationships reduces the false positive rate to an acceptable range, while forcing attackers to simultaneously fabricate activity trajectories and social contexts, significantly increasing costs.

User cold start, content supply, performance realization, and governance self-restraint. The appeal of its narrative lies in creating a closed loop of "identity - creation - transaction - governance", attempting to avoid the vicious cycle of the previous generation of metaverse projects of "land - speculation - desolation". If identity can be migrated, contributions can be measured, and profit sharing can be realized, SOMI can create real demand when participation increases; if we further add mechanisms like "partial transaction fee burning + validator rewards", the long-term discount rate is expected to decrease. However, the reality outside of roadshows is three major challenges. First, supply side: quality content is not a pile of whitelists; creators need clear upload standards, testable toolchains, and predictable profit sharing; without top content quickly establishing "play templates", it is difficult for DAU to truly retain. Second, demand side: the universal value of cross-application assets must be higher than the experience cost of a single application, especially in the first hour for new users entering the space. Whether they can seamlessly complete wallet creation, identity minting, and basic asset acquisition determines retention the next day. Third, security and compliance: large-scale users and immersive interactions will attract more complex attacks and gray economies. Anti-cheating, copyright disputes, and protection of minors all require a supporting mechanism of "on-chain evidence + off-chain enforcement"; otherwise, risk control costs will quickly externalize to creators and platforms. Investors should focus on a set of verifiable health indicators: 30/60/90 day retention, the proportion of "non-financial behaviors" in on-chain interactions, royalty realization rates and average settlement delays, the degree of decentralization of validators, client rollback rates, and the matching degree of token release and ecological growth. If these indicators can continue to improve, even with short-term price fluctuations, it indicates that "the endogenous demand of the ecosystem is growing". Conversely, if data relies on short-cycle incentives and airdrop tasks or if transactions mainly involve "volume-fluffing financial interactions", then significant discount risk expectations are needed. Regarding SOMI's role positioning, the safest path is "utility-first, governance power released later": first hard-bind fees, settlements, and rewards, then link governance rights with long-term locking, development contributions, community audits, etc., to reduce the risk of voting being manipulated by short-term capital. From a longer-term perspective, the key to Somnia's success or failure actually boils down to one thing: can it make "the reliability of real-time interaction" an industry-recognized public good? Once this line is protected, content and capital will gather with lower friction; the remaining issues are just a matter of time and execution.@Somnia Official #Somnia $SOMI

The biggest obstacles to deploying AI models on the blockchain are privacy and cost: data must be protected while keeping inference costs affordable. The ZK-FHE hybrid model proposed by Boundless Network combines zero-knowledge proofs with verifiable homomorphic encryption into a dual-stack process of 'compress first, prove later': users encrypt their inputs and send them to the computing nodes, which complete inference in the FHE domain and output ciphertext results; then, a succinct proof is generated to prove 'the result is correct and conforms to the model commitment', allowing verification of the contract to confirm inference validity at constant cost. In this way, users' private data and model weights remain encrypted at all times, with only a short proof and hash saved on-chain, without disclosing any confidential content. Compared to pure FHE, Boundless reduces computational overhead by over 60%; compared to pure ZK, it avoids the risk of model weight leakage, achieving 'double-blind trust'.

In the practical engineering of cross-chain liquidity, the biggest problem is not 'Is there a bridge?' but 'Liquidity is sliced into countless thin pieces, each of which is not thick enough.' Mitosis employs a radial structure centered around 'Hub assets' to consolidate fragmented liquidity across multiple chains: native assets or equivalent certificates are uniformly anchored to a central hub, which maintains an authoritative snapshot of asset balances and states, and then distributes wrapped tokens across various radial chains through controlled minting/burning. The direct benefit of this approach is to use a centralized pool to resist the tearing of funds across multiple chains, while the indirect benefit is to converge cross-chain synchronization from 'N² channels of state reconciliation for each pair of chains' to 'one-to-many synchronization of all radials to the center.' In terms of development experience, the protocol and market makers only need to focus on the central clearing and replenishment process, while the upper-level logic of cross-chain transfer, lending, exchanging, and collateral can all be observed and dispatched on a unified hub panel, significantly reducing complexity.

Somnia aims to solve not just the small matter of 'bringing games onto the chain,' but rather the larger issue of 'treating the chain like a real-time server for interactions.' It focuses on performance and development experience on parallelism and native execution: by using MultiStream to split verification responsibilities across multiple parallel streams, and then coordinating for final sorting and integration; while the contract side is compatible with Solidity, it leans towards native compilation and compact storage (such as engines like IceDB that are closer to high-frequency read/write), attempting to shorten the critical path from invocation to confirmation. For games and entertainment platforms, this orientation of 'making the ledger an event-driven real-time backend' is crucial: moving characters, firing decisions, item trading, and ticket verification are all extremely sensitive to latency, and the traditional 10-15 second endgame model is hard to satisfy. At the experience level, if Somnia wants to make 'blockchain invisible,' it needs to package session keys, gas sponsorship, batch settlements, and intent routing as default capabilities: users only declare actions and constraints, and the system takes responsibility to combine the shortest path and lowest cost in the background, providing predictable degradation strategies under the worst network conditions (such as extending windows, limiting single transactions, or switching to conservative channels). The creator economy is the second pillar: the value closed loop of virtual goods, scenes, and identities depends on 'verifiable contribution measurement - transparent profit-sharing paths - appealable royalty settlements.' If royalties are still enforceable in secondary markets and across applications, and can be replayed through on-chain events, then the willingness to create will form a sustained supply. The value capture of the token SOMI needs to be strongly bound to 'real interaction volume': according to public information, the network allocates transaction fees between verification and destruction; higher on-chain activity means stronger deflation and more stable validator revenue; at the same time, governance and fund usage should be incorporated into delayed execution and public auditing processes to reduce the harm of 'emotional proposals' on long-term stability. What needs to be cautious is the gap between 'benchmark performance - real concurrency' and the tension between 'anti-cheating - decentralization': if real-time interaction relies too heavily on quick endgames, node diversity and geographical distribution may be limited; if a more conservative confirmation strategy is adopted, smarter optimistic rendering and rollback compensation need to be implemented on the client experience side. To measure whether Somnia is on the right track, it is worth focusing on four indicators: P50/P95 confirmation latency for interactive transactions, concurrency and disconnection rates on the same server, actual enforcement rate of royalties in secondary markets, and the stability of wallet-side gasless sessions. Running through these 'heavy engineering facts' will bring the imagination of virtual society and on-chain entertainment to reality.@Somnia Official #Somnia $SOMI

While most DeFi protocols still use the 'fund pool + independent business module' template, @Dolomite chooses to completely overturn the financial architecture: it places user accounts rather than fund pools at the origin of the coordinates, allowing for atomic settlement of collateral, trading, lending, and yield reinvestment to be completed within the same balance sheet through a set of 'account as portfolio' underlying design. This sounds like a marketing slogan, but it actually hides profound engineering trade-offs and financial philosophy.

First is the contractization at the account layer. Traditional lending protocols require you to deposit assets into a pool and then obtain rights in the form of 'shares', resulting in the fragmentation of liquidity, yield rights, and trading rights into three parts, making cross-protocol scheduling extremely difficult. The approach of #Dolomite is to deploy independent account contracts for each user, with assets always recorded in the individual's name, and the protocol only adjusts your positive and negative exposure at the accounting level. This paradigm of 'asset ownership not leaving home' brings two direct benefits: first, the staking rewards generated by yield-bearing collateral (stETH, plvGLP, rwAVAX, etc.) will automatically flow back to the account instead of entering a public pool, truly achieving 'collateral equals yield'; second, all positions share a unified collateral rate, equivalent to stacking multiple strategies in the same collateral box, thus enhancing capital efficiency by one dimension.

Plume's economic model revolves around two key objectives: to ensure that real cash flows cover on-chain operational and security costs, and to direct the remaining value to long-term participants based on 'contribution rather than holding tokens'. The network fees consist of three parts: execution fees, compliance verification fees, and data custody fees, all priced in the native token PLUME. During daily settlements, the system first replenishes the risk fund by 35%, addressing clearing errors, asset redemption runs, and black swans; 25% is used for on-chain operations and audit expenses; 15% is allocated for secondary market repurchases and immediate destruction; the remaining 25% is distributed among issuers, liquidity providers, and verification nodes based on 'capital utilization rate × duration × reputation coefficient'. The design intent of this formula is to encourage long-term funding and high-quality assets, rather than short-term speculation. To improve their ranking weight, verification nodes must maintain both 'asset audit pass rate' and 'data real-time service level agreements' (SLA) in addition to staking PLUME; if they fail to meet standards for two consecutive settlement periods, their stake will be penalized at a rate of 1.2 times to replenish the risk pool. In terms of governance, Plume introduces a bicameral structure: one chamber for token holders and another for KYC-verified institutional issuers and service providers; any proposal must receive over 60% support from both chambers to take effect, with a mandatory 72-hour delay before execution. This design prevents purely capital-driven hijacking while ensuring the rule-making power of professional nodes. Regarding token release rhythm, the team's and investors' shares are all linearly unlocked over 36 months, with a commitment not to sell in advance until the on-chain average daily fee reaches $200,000; ecological incentives are linked to asset scale, with a $100 million increase in TVL automatically releasing 0.5% of mining quotas to subsidize market-making and user gas fees. Through a closed loop of 'real income → risk pool → repurchase and destruction', the net circulation of PLUME theoretically continues to shrink with network usage, forming a scarcity expectation positively correlated with business volume. However, the effectiveness of this model depends on two points: 1) the regulatory friendliness determines whether assets can be scaled onto the chain; 2) the capital market's patience for 'slow-growing cash flows'. If the macro environment tightens suddenly or user yield expectations rise quickly, Plume needs backup on-chain debt tools or counter-cyclical incentives to maintain liquidity. Overall, Plume's economic and governance framework attempts to embed 'safety cushion priority' into code, reducing tail risks through institutional means and supporting long-term value with real cash flows. This is a rare rational design in the RWA track and provides the possibility for the token to traverse bull and bear markets.@Plume - RWA Chain #Plume $PLUME