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Non-fungible tokens are commonly associated with digital art and public collectibles, but the Dusk Foundation is advancing a far more consequential use case: regulated real-world assets (RWAs). Through its grants program, the Foundation is funding teams that are building NFT platforms designed specifically for environments where confidentiality, compliance, and selective disclosure are non-negotiable.
At the core of this initiative is the concept of “dark” or private metadata. Unlike conventional NFTs, where all metadata is publicly visible, these platforms allow sensitive information to remain encrypted or hidden by default. Ownership, provenance, and transferability are still verifiable on-chain, but the underlying data—such as legal documents, financial terms, or personal identifiers—is accessible only to authorized parties under predefined conditions. This architecture aligns closely with regulatory requirements while preserving the transparency guarantees of blockchain systems.
This approach unlocks practical tokenization of assets such as property deeds, private equity shares, fund interests, and other regulated instruments. Institutions can issue NFTs that represent legal ownership or entitlement without exposing confidential documentation to the public ledger. Regulators, auditors, or counterparties can be granted controlled access to specific data fields, enabling compliance checks and due diligence without compromising privacy.
By supporting NFT platforms with private metadata, the Dusk Foundation is positioning its network as a foundational layer for compliant digital asset infrastructure. These efforts demonstrate that NFTs are not limited to public-facing use cases, but can serve as secure, privacy-preserving wrappers for high-value, real-world assets. In doing so, Dusk is bridging the gap between decentralized technology and the stringent requirements of regulated financial markets, expanding the role of NFTs from collectibles to institutional-grade instruments.
@Dusk #dusk $DUSK

Decentralized finance has delivered unprecedented transparency and composability, but these strengths have also exposed a structural limitation: radical openness. On most public blockchains, every trade, liquidity position, and strategy is permanently visible. For institutional participants and privacy-conscious users, this level of disclosure is not merely inconvenient—it is commercially and legally untenable. Recognizing this gap, the Dusk Foundation has positioned privacy as a first-class primitive and is actively funding teams to build a new generation of DeFi infrastructure designed for confidential participation.
At the center of this effort is the development of private Automated Market Makers (AMMs) and lending protocols. Unlike conventional DeFi platforms, which reveal wallet balances, trading behavior, and liquidity positions in full, these privacy-preserving primitives enable users to interact with financial markets without broadcasting sensitive information. Liquidity providers can deploy capital without exposing their total holdings, while traders can execute strategies without inviting front-running or competitive surveillance.
The Foundation’s grant recipients are leveraging Dusk’s zero-knowledge–based architecture to strike a critical balance between confidentiality and verifiability. Transactions remain provably correct and compliant with protocol rules, yet the underlying financial details—such as trade size, counterparties, or portfolio composition—are shielded from public view. This approach preserves the trustless nature of DeFi while aligning it with real-world expectations around financial privacy.
The implications are significant. Private AMMs and lending markets on Dusk offer a pathway to on-chain liquidity without sacrificing regulatory obligations or proprietary strategies. For individual users, they restore a basic principle long taken for granted in traditional finance: the right to transact without complete public disclosure.
@Dusk #dusk $DUSK

Since the launch of its mainnet, the Dusk Foundation has continued to advance its core protocol through a series of structured upgrades, each designed to strengthen the network’s role as a foundation for privacy-preserving financial applications. These upgrades are delivered as named releases, reflecting coordinated improvements across consensus, execution, and network layers. The most significant of these to date is the Citadel release.
Citadel represents a major step forward in enhancing the security, stability, and performance of the Dusk mainnet. Rather than introducing surface-level features, the release focuses on deep protocol optimizations that are critical for supporting regulated, high-throughput financial use cases.
At the heart of Citadel are improvements to Dusk’s SBA (Segregated Byzantine Agreement) consensus mechanism, which is designed to provide fast finality while maintaining strong security guarantees. These optimizations improve block propagation efficiency and reduce coordination overhead among participating nodes, resulting in smoother and more predictable network operation under load.
In parallel with consensus upgrades, Citadel introduces refinements to the underlying virtual machine, improving execution efficiency and reliability for smart contracts. These changes reduce friction for developers building privacy-aware financial logic while ensuring deterministic behavior across the network.
The release also delivers more efficient staking mechanics, optimizing validator participation and incentive alignment. This strengthens decentralization and enhances the overall robustness of the network by ensuring that security scales alongside adoption.
While largely “under the hood,” the Citadel release is strategically important. Financial applications demand more than basic uptime—they require predictable performance, strong security assumptions, and resilience during periods of high transaction volume. Citadel positions Dusk to meet these requirements by reinforcing the protocol’s foundational layers.
@Dusk #dusk $DUSK

Nel 2026, lo storage non riguarda più solo "dove" si trova i dati, ma il costo totale per mantenerli disponibili. Per le imprese che gestiscono grandi dataset per l'IA o contenuti ad alta risoluzione, il modello tradizionale della nuvola (AWS S3) è diventato un "Hotel California" dei dati: facile da entrare, ma incredibilmente costoso da lasciare.
Walrus, alimentato dall'encoding Red Stuff, offre un'alternativa strutturale che mira ai costi nascosti delle nuvole Web2.
1. Confronto dei costi: Il "prezzo nascosto"
Mentre AWS S3 Standard sembra economico a circa 23$/TB al mese, il prezzo di listino è ingannevole per i dataset attivi. Walrus semplifica questo processo con un modello più trasparente e con costi iniziali chiari

The Walrus Protocol isn't just a technical achievement in 2D erasure coding; it is a meticulously designed economic engine. The WAL token acts as the "performance bond" that ensures storage nodes don't just store data, but do so with the high-speed reliability that Red Stuff enables.
1. The WAL Token Utility
WAL is the native asset of the Walrus network, serving three critical pillars:
Storage Payments: Users pay for storage upfront in WAL. The protocol then distributes these funds to nodes over the duration of the storage period.
Security (Staking): Walrus uses a Delegated Proof-of-Stake (dPoS) model. Nodes must stake WAL to join the active committee, and users can delegate their WAL to nodes to earn a share of rewards.
Governance: Token holders vote on protocol parameters, such as the base price of storage and the severity of penalties for underperformance.
2. The Incentive Flywheel
Walrus incentivizes honesty and performance through a "Stake-Weighted" reward system:
Epoch-Based Selection: The network operates in Epochs. During each epoch, a committee of nodes is selected based on their total stake (self-staked + delegated).
Probability of Work: Nodes with higher stake are assigned more data "slivers" to store. Since rewards are tied to the amount of data successfully stored and proven, high-stake nodes earn more—but also carry more risk.
Early-Stage Subsidies: To bootstrap the network, 10% of the WAL supply is earmarked for subsidies. This keeps storage costs low for users while ensuring node operators remain profitable as the network grows.
3. Slashing and "The Performance Bond"
In Walrus, staking is treated as a Service Level Agreement (SLA). If a node fails to meet its obligations, it faces financial consequences:
Liveness Penalties: If a node is offline and fails to respond to storage challenges, a portion of its stake is penalized.
Data Loss Slashing: If a node cannot provide a "Proof of Availability" (PoA) for the slivers it was assigned, a significant portion of its staked WAL is slashed and burned.
Economic Filter: Because a percentage of slashed tokens is permanently removed from the supply, the system naturally filters out unreliable operators, leaving only professional-grade nodes in the committee.
4. Market-Driven Pricing
Unlike centralized providers that set fixed prices, Walrus uses a Stake-Weighted Percentile mechanism to determine storage costs:
Every node in the active committee proposes its own price.
The protocol sorts these proposals by the node's stake weight.
The price is set at the 66.67th percentile. This prevents a few "cheap but low-quality" nodes from driving prices down to unsustainable levels, while ensuring the price reflects the consensus of the most reputable, highly-staked operators.
@Walrus 🦭/acc
#walrus
$WAL

As artificial intelligence systems become increasingly data-hungry, the economic and technical limitations of today’s data infrastructure are becoming impossible to ignore. Data is abundant, yet access, ownership, and verification remain fragmented across centralized platforms that extract value without adequately compensating data creators or users. Walrus addresses this imbalance by enabling verifiable, decentralized data markets designed specifically for the AI era—markets where builders and users can control, verify, and create value from the world’s data.
At its core, Walrus introduces a decentralized storage and data availability layer optimized for large-scale, high-throughput datasets. Rather than treating data as a passive asset, Walrus transforms it into an active, programmable resource. Through advanced erasure coding and cryptographic verification mechanisms, data stored on Walrus can be proven to exist, remain intact, and be retrievable without requiring trust in any single storage provider. This verifiability is foundational for AI applications, where training data quality and integrity directly affect model performance and safety.
Walrus also reshapes data ownership. In traditional AI pipelines, data contributors often lose control once their data enters centralized systems. Walrus enables fine-grained access control and programmable permissions, allowing data owners to define how their data is used, shared, or monetized. Builders can consume datasets with cryptographic guarantees around provenance and authenticity, while contributors retain sovereignty over their assets. This alignment of incentives lays the groundwork for sustainable data markets rather than extractive data silos.
For developers, Walrus unlocks new economic primitives around data. Datasets can be priced dynamically, licensed programmatically, and integrated directly into on-chain or cross-chain applications. AI builders can source high-quality, domain-specific data on demand, while automated enforcement ensures that usage terms are respected. This reduces legal and operational friction, enabling faster experimentation and deployment of AI systems.
In the broader context of Web3 and AI convergence, Walrus acts as the connective tissue between raw data and intelligent systems. By making data verifiable, composable, and economically expressive, it enables open data markets that reward contribution, ensure transparency, and scale with AI’s growing demands. In doing so, Walrus empowers both builders and users to move from being passive data sources to active participants in a global, decentralized data economy—one built for the realities of the AI era.
$WAL
@Walrus 🦭/acc #walrus