Blockchain oracle network Pyth has unveiled what it calls the first continuously updating crude oil composite index, designed to fill pricing gaps left by traditional commodity markets that operate on fixed trading schedules.

The Pyth 24/7 Oil Index aggregates both onchain and offchain data, pulling from institutional trading desks and exchanges during regular hours and from decentralized derivatives venues during nights, weekends, and holidays. The goal is to eliminate stale reference prices during periods when legacy benchmarks like NYMEX WTI futures stop updating.

The launch comes amid extreme volatility in global energy markets. Joint U.S.-Israeli airstrikes on Iran and subsequent Iranian retaliation triggered immediate surges in oil and gas prices and heightened volatility in financial markets.

The cessation of tanker traffic through the Strait of Hormuz and attacks on the region’s oil infrastructure have significantly impacted global supply chains. Roughly 20% of the world’s oil transits the Strait, making any disruption there a systemic risk for global energy pricing.

Pyth noted that onchain commodity trading has surged alongside the crisis. Hyperliquid alone processed over $1 billion in daily WTI oil perpetual volume during recent volatility spikes — activity that occurred largely outside traditional market windows.

Pyth’s oracle model, in which institutional trading firms and market makers publish first-party pricing data directly to the network, gives it a combined view of liquidity across both traditional and decentralized venues.

The oil index is the first in a planned series of proprietary always-on indices spanning commodity, macro, and cross-asset categories.

WASHINGTON, D.C. — The Senate’s stalled crypto market structure bill is making progress behind-the-scenes, the chairman of the body’s Banking Committee said Tuesday.

Senator Tim Scott, who heads the banking panel overseeing the market structure bill, said at the Digital Chamber’s DC Blockchain Summit that lawmakers may see a new draft of at least stablecoin language as soon as this week.

Stablecoin yield has been the most publicly debated issue in the market structure bill, but lawmakers have remained engaged, Scott said.

“I believe that this week we will have the first proposal in my hands to take a look at,” he said. “If that actually happened before the end of this week, and I think that it will, we’ll at least know that the sketch looks like the person. If that’s the case, I think we’re gonna be in much better shape.”

He credited Democratic Senator Angela Alsobrooks, Republican Senator Thom Tillis, and the White House’s Patrick Witt for their efforts on yield.

Other outstanding issues have also been negotiated, particularly over the past month, he said, pointing to concerns lawmakers had about U.S. President Donald Trump and his family’s crypto projects, the lack of bipartisan commissioners at the major regulatory agencies and know-your-customer regulations.

“I think we’re very close to landing the plane on the ethics issue, on quorum,” Scott said. “We know that that’s a big issue for our friends on the other side of the aisle, so we’re fixing that as well. I think we’re moving forward with some [nominations], which is great news that we were able to get some out of the other side. I think the issue of DeFi is something that [Senator] Mark Warner’s held on tightly, AML [anti-money laundering] being a very important part. So I think we’re working on that issue.”

[PRESS RELEASE – George Town, British Virgin Islands, March 17th, 2026]

Aster, a privacy-focused trading ecosystem backed by YZi Labs, today announced the official launch of Aster Chain Mainnet. This purpose-built Layer 1 blockchain is designed to dismantle the “transparency trap” of modern DeFi, offering institutional-grade privacy and CEX-level performance to professional and retail traders worldwide.

Ending the Era of Onchain Position Hunting

Transparency is a defining characteristic of decentralized finance, supported by public ledgers, verifiable transactions, and open protocols. However, transparency between protocols and users differs from transparency among market participants. When trading activity, including order placement, position size, and liquidation levels, is fully visible on-chain, such information may be observed and used by other participants in the market.

Position hunting – where traders identify a large position, see its liquidation price, and coordinate to trigger a forced liquidation – has cost traders millions of dollars on fully transparent platforms. Infamously, in March 2025, a trader opened a $375 million BTC 40x short on a fully transparent platform. Traders quickly began openly coordinating on Twitter to pool funds and hunt the position.

Aster’s default privacy removes that attack surface entirely.

The Aster Thesis: Privacy is a Fundamental Right

Unlike existing solutions that treat privacy as an opt-in feature or a third-party wrapper, Aster Chain embeds encryption directly into the execution layer. On Aster, privacy is the default, not a privilege.

The Aster privacy stack utilizes a ZK-verifiable encrypted architecture:

• ZK-Verifiable Encryption + Stealth Address Mechanism: Every order is ZK-verifiable encrypted before it reaches the chain; with Account Privacy enabled, orders are routed through unique stealth addresses, ensuring no link between users’ wallets and their trading activity, and preventing any third party from tracing, correlating, or reconstructing trades.
• Selective Disclosure: While asset transfers remain traceable for compliance, the execution layer shields strategic intent. Users who want their activity visible can choose to make it public. With Account Privacy enabled, users can generate a Viewer Pass to share with selected parties, allowing only those with access to the pass to view their private orders.
• Zero Performance Trade-off: Aster Chain achieves peak throughput of 100,000+ TPS and a median block time of 50ms, all without gas – performance that matches the speed traders expect from a centralized exchange.

“Transparency between a protocol and its users is a fundamental feature, but transparency between a trader and their competitors is a critical vulnerability,” said Leonard, CEO at Aster. “Aster Chain is the only architecture that treats privacy as a fundamental requirement for a fair market, neutralizing predatory attacks at the base layer.”

CEX Speed Meets DEX Principles

Aster Chain delivers the sub-second finality and high-leverage experience of a CEX while upholding the core tenets of decentralization: self-custody, verifiability, and permissionless access. Trading privacy removes the last reason to stay on a centralized exchange. The network is supported by a native bridge to BNB Chain and proprietary oracles to ensure high-fidelity price data.

Fuelling the Next Wave of Innovation

The mainnet launch marks the start of a phased expansion. Beyond the flagship Aster trading UI, the ecosystem is inviting builders to create specialized vaults and collaborative DeFi products through Aster Code.

To coincide with the launch, Aster will initiate a Staking Program within a week to reward early supporters and liquidity providers.

About Aster

Aster is a privacy-first onchain trading platform backed by YZi Labs, with unique features like Hidden Orders to protect user trading activity. It offers perpetual contracts across crypto, stocks and commodities, as well as crypto spot trading, and is powered by Aster Chain, a Layer 1 blockchain built to power the future of decentralized finance.

Users can learn more about Aster on the official website or follow Aster on X.

The U.S. Securities and Exchange Commission and the Commodity Futures Trading Commission have jointly released a sweeping interpretive guidance that formally classifies major crypto assets and activities under federal securities law, a long-awaited move that ends years of regulatory ambiguity that industry participants described as “regulation by enforcement.”

The guidance, Release No. 33-11412, establishes a five-category taxonomy for crypto assets and clarifies the legal status of a range of on-chain activities including staking, mining, airdrops, and token wrapping.

A New Taxonomy

At the heart of the document is a classification system that divides crypto assets into five categories: digital commodities, digital collectibles, digital tools, stablecoins, and digital securities.

The most consequential determination for the market is the SEC’s explicit designation of 16 major tokens as digital commodities — assets that derive their value from the programmatic operation of a functional crypto network rather than from the managerial efforts of a centralized party. The list includes Bitcoin (BTC), Ether (ETH), Solana (SOL), XRP, Cardano (ADA), Avalanche (AVAX), Chainlink (LINK), Dogecoin (DOGE), and eight others. As digital commodities, these assets are not securities and fall outside SEC jurisdiction, though they could be subject to CFTC oversight as commodities under the Commodity Exchange Act.

NFTs, Meme Coins, and Fan Tokens

The guidance also formally addresses NFTs and meme coins, classifying them as digital collectibles — assets with artistic, entertainment, social, or cultural value. Examples cited include CryptoPunks, Chromie Squiggles, and the meme coin WIF. The SEC notes that meme coins are typically acquired for non-investment purposes, their value driven by supply and demand rather than any issuer’s efforts, and are therefore not securities.

However, the agencies drew one notable bright line: fractionalizing a digital collectible — splitting a single NFT into multiple ownership interests — could constitute a securities offering, because it introduces elements of shared investment and reliance on managerial efforts.

Fan tokens received a nuanced treatment, with the SEC noting they have “hybrid characteristics” and could also be classified as digital tools.

Staking and Mining Get a Safe Harbor

One of the most practically significant sections of the guidance covers protocol staking and protocol mining, both of which the SEC determined are not securities transactions. The ruling covers solo staking, third-party custodial staking, and liquid staking arrangements — provided that staking providers do not guarantee fixed returns, do not use deposited assets for speculation or rehypothecation, and function as administrative agents rather than active managers of investor funds.

Liquid staking receipt tokens — the tokenized receipts issued to depositors in liquid staking protocols — are similarly deemed non-securities when they represent non-security underlying assets. This determination is significant for protocols like Lido and Rocket Pool, which issue tokens such as stETH and rETH.

Wrapped Tokens Also in the Clear

The guidance also provides clarity on token wrapping, concluding that redeemable wrapped tokens — one-for-one representations of an underlying crypto asset, such as wrapped Bitcoin (WBTC) — are not securities when the underlying asset is itself a non-security. The SEC specifies that wrapped token providers cannot use deposited assets for any purpose, including lending or trading, for this safe harbor to apply.

From “Regulation by Enforcement” to a Written Framework

The joint release comes after years of industry frustration with SEC enforcement actions against crypto firms, which many characterized as the agency’s primary tool for defining the regulatory perimeter. The guidance explicitly acknowledges those criticisms, noting that the SEC’s previous approach prompted complaints that it was pursuing actions rather than “developing a tailored regulatory framework that accommodates crypto asset innovation.”

The new framework grows out of work by the SEC’s Crypto Task Force, established in January 2025 under then-Acting Chairman Mark T. Uyeda, and was formalized as “Project Crypto” under Chairman Paul S. Atkins following a White House working group report on digital asset markets released in July 2025. On January 29, 2026, Atkins and CFTC Chairman Michael S. Selig announced the initiative would proceed jointly between both agencies.

The SEC emphasized that the guidance does not replace the Howey test — the Supreme Court precedent used to determine what constitutes an investment contract — but rather articulates how the agency interprets its application to crypto assets. Importantly, the guidance supersedes prior SEC staff statements on topics including meme coins, stablecoins, proof-of-work mining, and staking.

What Remains a Security

The document makes clear that assets structured as digital securities — tokenized stocks, bonds, or other traditional financial instruments recorded on a blockchain — remain fully subject to securities law regardless of their on-chain format. It also reaffirms that any non-security crypto asset can become subject to an investment contract if issuers make explicit promises of profit tied to their own managerial efforts — the classic token sale model — and that such investment contracts must be registered or exempt.

The agencies are soliciting public comment on the guidance and indicated the framework may be revised or expanded based on feedback.

This article was written with the assistance of AI workflows. All our stories are curated, edited and fact-checked by a human.

Tether has unveiled a cross-platform AI training framework that the company says can fine-tune large language models on consumer hardware, including smartphones and non-NVIDIA GPUs. The system, part of Tether’s QVAC platform, leans on Microsoft’s BitNet architecture and LoRA techniques to shrink memory and compute demands, potentially lowering the cost and hardware barriers for developers. The announcement positions the framework as compatible with a broad spectrum of chips—from AMD and Intel to Apple Silicon—along with mobile GPUs from Qualcomm and Apple. In internal tests, engineers reportedly fine-tuned models with up to 1 billion parameters on smartphones in under two hours, with smaller models achievable in minutes, and supported models as large as 13 billion parameters on mobile devices.

Key takeaways

• Tether’s QVAC framework leverages a 1-bit model architecture (BitNet) to drastically cut VRAM usage, enabling larger models to run on constrained hardware.
• LoRA-based fine-tuning is extended to non-NVIDIA hardware, broadening compatibility across AMD, Intel, and Apple Silicon platforms, as well as mobile GPUs from Qualcomm and Apple.
• On-device training and federated learning are highlighted as potential use cases, pointing to reduced reliance on centralized cloud compute for model updates.
• Performance gains extend to inference, with mobile GPUs reportedly delivering faster results for BitNet models than traditional CPU workloads.
• The move fits a broader industry trend of crypto firms expanding into AI compute and high-performance computing, touching on AI data center capacity and autonomous software agents.

Tickers mentioned: $BTC, $USDT, $USDC, $COIN, $HIVE

Sentiment: Neutral

Market context: The push to bring AI training and inference closer to edge devices mirrors a broader shift toward on-device AI and distributed learning within crypto and fintech ecosystems, alongside ongoing capital allocation to AI compute by mining operators and data-center firms.

Why it matters

For a market built on trust in programmable money and permissionless ecosystems, the ability to run substantial AI workloads on consumer hardware could recalibrate who can train and fine-tune models. By reducing VRAM requirements by up to 77.8% compared with comparable 16-bit models, according to Tether, the BitNet-based framework tackles one of the most persistent friction points in edge AI: memory constraints. This could enable developers to push more experimentation to devices that sit closer to users, potentially enabling privacy-preserving on-device training and federated learning, where updates are aggregated locally rather than uploaded to centralized servers.

Beyond the novelty of running billion-parameter models on smartphones, the initiative hints at a broader strategy: crypto firms are leaning into AI and HPC to support new products and services, from on-chain analytics to autonomous agents that transact or interact with services. The article notes that major players have already begun integrating AI into core operations or exploring AI-driven infrastructure. As crypto mining and data-center operators seek higher-margin use cases, AI compute becomes a natural extension of the sector’s infrastructure footprint. This aligns with a wider trend of institutional players diversifying into AI workloads, underscoring how blockchain-native firms view AI as a critical component of long-term scalability and product development.

On the technology side, the cross-platform capability signals a shift away from Nvidia-dominated AI stacks toward more hardware-agnostic approaches. The combination of a 1-bit model architecture with LoRA fine-tuning on non-NVIDIA hardware expands the potential hardware pool for AI development, a move that could accelerate experimentation and reduce barriers for smaller teams or individual developers who rely on consumer devices. This development is also likely to influence how AI agents—autonomous programs that interact with services and execute tasks—are trained and updated on-device, potentially strengthening privacy-preserving use cases by minimizing data transfer to cloud endpoints.

The broader industry backdrop includes crypto firms expanding into AI-enabled services and data centers. For example, strategic moves by miners and infrastructure vendors to scale AI compute capacity have been reported in recent quarters, with several large players pursuing AI-centric data-center deployments and partnerships. While the immediate impact of Tether’s framework remains to be demonstrated at scale, the emphasis on cross-platform interoperability and on-device capabilities suggests a future where AI tooling becomes more accessible to a wider range of devices, including those with limited compute budgets.

What to watch next

• Adoption pace: Will other crypto firms and AI developers publicly deploy BitNet-based training on consumer hardware, and what applications emerge first?
• Cross-platform expansion: How quickly will the LoRA-enabled workflow extend to additional non-NVIDIA GPUs and mobile accelerators?
• On-device AI pilots: Will we see real-world federated learning deployments or on-device training pilots that demonstrate data privacy benefits?
• Competitive benchmarks: Independent tests comparing BitNet-based training to traditional GPU-centric workflows across edge devices and data centers.
• Ecosystem partnerships: Any collaborations with wallet providers, AI agents, or on-chain analytics platforms that integrate edge-trained models into user-facing products.

Sources & verification

• Tether’s QVAC launch announcement detailing the cross-platform BitNet/LoRA framework and its aims. Verify at the official Tether news page linked in the announcement.
• The QVAC/BitNet framework’s claimed VRAM and parameter-strength reductions, as described in Tether’s release.
• HIVE Digital Technologies’ reported AI/HPC-driven revenue and performance metrics cited in industry coverage from Cointelegraph.
• World’s AgentKit and related AI agent verification and payment capabilities, as described in World’s official communications and coverage.
• Coinbase’s wallet infrastructure for AI agents and the Alchemy system enabling access to blockchain data via USDC, as reported in coverage cited in the article.

What to watch next

Keep an eye on updates from Tether on QVAC milestones, including any broader platform integrations or additional hardware compatibility announcements. Monitor whether other crypto-native or fintech firms begin publishing performance benchmarks or pilot deployments that validate on-device training claims. Finally, track moves by AI and crypto industry players toward federated learning and privacy-preserving on-device inference, which could reshape how models are trained and updated in distributed networks.

Sources & verification

• Tether QVAC launch: https://tether.io/news/tethers-qvac-launches-worlds-first-cross-platform-bitnet-lora-framework-to-enable-billion-parameter-ai-training-and-inference-on-consumer-gpus-and-smartphones/
• HIVE Digital Technologies revenue context: https://cointelegraph.com/news/hive-digital-focus-crypto-mining-ai-data-centers
• World AgentKit and human-verified AI agents: https://cointelegraph.com/news/world-launches-agentkit-coinbase-integration-enable-human-verified-ai-agents-embargo
• Coinbase wallet infrastructure for AI agents: https://cointelegraph.com/news/coinbase-launches-crypto-wallets-built-ai-agents
• Alchemy AI agents data access using USDC: https://cointelegraph.com/news/alchemy-ai-agents-pay-access-blockchain-data-usdc

Key figures and next steps

With Tether positioning QVAC as a cross-platform compute framework and citing substantial reductions in memory requirements, the company signals a strategic pivot toward enabling AI workloads on widely available hardware. If the framework gains traction, developers could see accelerated experimentation on consumer devices, expanding the reach of AI-assisted on-chain tools and analytics. The coming months will reveal whether these capabilities translate into broader developer adoption, practical on-device AI pilots, and tangible reductions in cloud compute demand for crypto-related AI tasks.

What this could mean for users and builders

For end users, the potential exists for faster, more private AI-powered features embedded in wallets and on-chain services. For builders, the framework lowers the barrier to prototype, test, and refine AI models without the need for high-end data-center GPUs. In a sector where compute cost can be a constraint, this shift toward edge AI adoption aligns with long-term goals of decentralization, privacy, and efficiency. It also underscores the ongoing convergence between crypto infrastructure and advanced AI compute, a development that could influence everything from on-chain data services to the design of autonomous agents and governance tools. As with any new technology, scalability, security considerations, and interoperability standards will shape how quickly such capabilities mature and how widely they are adopted across the ecosystem.

Moody’s Ratings has debuted a system to deliver its credit analysis onchain, bringing its ratings data into blockchain-based financial infrastructure.

The system, called Token Integration Engine (TIE), connects Moody’s traditional ratings data to blockchain networks, allowing permissioned participants to access credit insights within blockchain-based financial workflows. It is built for institutional use, with issuers controlling participation while Moody’s retains oversight of its ratings process.

The company claims it is the first credit rating agency to deliver its credit analysis onchain. In June 2025, Moody’s teamed up with a fintech startup called Alphaledger to run a pilot program to explore how traditional credit ratings could be integrated into blockchain systems.

The initial deployment runs on the Canton Network, a permissioned blockchain designed for institutional finance. Moody’s is operating its own node on the network as part of the rollout, and said it plans to expand the system to additional blockchains and asset types.

The system is designed to be network-agnostic, with access controlled by issuers under the company’s existing governance and compliance framework.

Moody’s, a US-based credit rating agency founded in 1909 with operations in more than 40 countries, assesses the creditworthiness of governments, companies and financial instruments, with its ratings widely used by investors across global capital markets.

Related: Crypto accounting startup Cryptio lands $45M as institutions move onchain

The rise of the Canton Network

Moody’s deployment adds to the growing use of the Canton Network as infrastructure for institutional blockchain applications, particularly in tokenized assets and collateral markets.

A growing list of asset managers are integrating tokenized funds into the network. Franklin Templeton expanded its Benji platform to Canton in November, allowing its tokenized assets, including a US government money market fund, to be used as collateral and liquidity within the ecosystem.

Other efforts have focused on market infrastructure and settlement. In December, the Depository Trust and Clearing Corporation (DTCC) said it plans to issue a subset of US Treasury securities on Canton, extending blockchain-based processes into core clearing and settlement systems, with potential expansion to additional asset classes.

Banks and digital asset infrastructure platforms are also building on the network. In January, Digital Asset and Kinexys by JPMorgan said they plan to bring JPMorgan’s dollar deposit token, JPM Coin, to Canton, while Temple Digital Group launched a platform enabling 24/7 trading of digital assets through a central limit order book with non-custodial settlement.

The value of Canton Coin, the network’s native token, has increased about 30% since its launch in November 2025, according to CoinGecko data.

Magazine: China’s ‘50x’ blockchain boost, Alibaba-linked AI mines Bitcoin: Asia Express