Although it’s commonly suspected that migratory birds fly in a ‘V’ formation due to this saving energy for the birds in the slipstream, understanding the exact aerodynamics behind this and how it affects the way that the birds use their wings to maintain this optimal pattern. After all, unlike airplanes and cars, our feathered avian dinosaur friends need to flap their wings if they want to have any chance of staving off plummeting back to Earth. Recent research by Brown University researchers now have provided a simulated model that answers many questions.
The major question was how this would work in the up- and down-wash zones created in this type of formation, with every bird following the lead bird dealing with the vortices created by the flapping of the wings of the bird before them. These wake vortices are quite complex, and thus required careful modelling to make sense of them.
As described in the paper by [Olivia Pomerenk] et al., the model is based on northern bald ibises, taking into account live-bird measurements for validation of the model. The main effect that can be observed is a reduced flapping amplitude, leading to an 11% energy savings for the birds in the leader’s wake.
The main advantage of having such a model is of course that it provides insight into the kinematic and aerodynamic mechanisms, meaning the ability to model virtual flocks of birds, predict the efficiency of specific in-flight configurations, and apply the lessons to swarms of drones, or whatever else we want to put in the air.
OPINION OpenAI has acknowledged its models powered the autonomous agents that compromised HuggingFace infrastructure. It might be taken as a convoluted marketing stunt, were it not the perfect advertisement for China-based competition. The company's AI-culpa fits the narrative spun by US rival Anthropic about its Mythos models, which it deemed too dangerous to release except to totally trustworthy corporations and governments. OpenAI says: "The incident makes clear that advanced models can discover and exploit novel attack paths in real-world systems without source-code access. It highlights that advanced cyber capabilities must be developed alongside stronger safeguards and defensive tools." Are we surprised? It's been clear that AI models have the potential to go rogue and damage computers for several years. Academics have repeatedly warned about this possibility - even those affiliated with OpenAI and Anthropic. And anyone who has used AI models for software development has probably seen them code unexpected and perhaps unwanted workarounds to fulfill some directive. On Tuesday, the UK's AI Security Institute published findings about how frontier models all cheat. OpenAI's admission that its models devised a sandbox escape to obtain internet access and found a zero-day flaw to exploit, all to solve a benchmark evaluation problem, may be unprecedented in terms of the scale and prominence of the systems affected. But it's a reenactment of every Claude or Codex prompt in which the model responds to a disallowed command by trying an alternative. We were warned. The compromise of HuggingFace's systems is no more surprising than locking a bear in a supermarket and finding a mess the following day. AI models are billed as artificial intelligence, but when they power agents handling tools in a loop to achieve some objective, it's the equivalent of a brute force attack – the agent will keep trying things until something works or breaks. The surprising part came when HuggingFace sought to employ US frontier models to defend itself. It failed. That should raise eyebrows. "When we started the log analysis, we first used frontier models behind commercial APIs," the AI model-mart said in its blog post last week. "This did not work: the analysis required submitting large volumes of real attack commands, exploit payloads, and C2 artifacts, and these requests were blocked by the providers' safety guardrails, which cannot distinguish an incident responder from an attacker." Stymied by model refusals – which developers have been complaining about for months – HuggingFace had to rely on GLM 5.2, an open-weight AI model made by China-based Z.ai, to conduct its forensic analysis. And it did so on its own infrastructure, so nothing sensitive got sent to a cloud-based model provider. Coincidentally, the leaders of OpenAI and Anthropic have reportedly been warning the US government about the threat posed by increasingly capable Chinese models like Kimi K3 and GLM 5.2. And the US government is said to be mulling possible responses to limit competition from China. That won't work. It's just naïve to think that the US government and a handful of worthy organizations – however that is defined – will be able to enforce a global monopoly on highly capable AI. The infrastructure required to run open weight models that more or less rival the current state of the art is available for a price. And potential consumers of those services are not going to be satisfied with model refusals when there are other options, particularly if they're more cooperative and more affordable. The best course for governments, industry, and the public is to push for AI services that are open and available to all. For that to work, lawmakers around the world need to act fast to set some common ground rules that grapple with AI's impact on jobs, and find a way to compensate those whose work fuels machine learning. Some industry leaders appear to realize that. David Sacks, an external White House adviser and tech investor, recently urged Silicon Valley to rally around openness. "The leading closed labs, already a duopoly in terms of AI model revenue, want the government to eliminate their open source competition," he wrote in a social media post. "They have laid their cards on the table. It is time for the rest of Silicon Valley — the vast majority that still values open competition — to do the same." The fact is that US AI companies have sandboxed themselves into a corner: They've created demand for a product that they can't be relied upon to provide. And when they do make their most capable AI models available, they hobble them and demand terms tailored to serve their vast debt rather than their customers. OpenAI said that it has invited HuggingFace into its trusted access program so the company can use its most capable models. Chinese AI companies, meanwhile, have invited the world. ®
Alphabet's Google Cloud reports a $514 billion backlog amid rising AI demand. Alphabet as the second-largest company by market cap on July 31 at 3.4% YES.
Injective has filed Form TA-1 with the US Securities and Exchange Commission to register as a transfer agent, a move aimed at supporting regulated real-world asset infrastructure on-chain.
The filing is about recordkeeping for securities ownership. It is not a registration of the INJ token as a security, and it should not be read that way.
If approved, the transfer agent role would allow Injective to support official ownership records for securities directly through blockchain infrastructure. That could matter for tokenized stocks, funds, credit products, and other regulated real-world assets.
For Injective, the filing gives its RWA strategy a more formal regulatory angle.
TL;DR
Injective has filed Form TA-1 with the SEC to register as a transfer agent.
The filing relates to on-chain recordkeeping for securities ownership.
It does not register INJ itself as a security.
What A Transfer Agent Does
In traditional markets, transfer agents help maintain records of who owns securities.
They handle ownership records, transfers, shareholder lists, and related administrative functions. It is not the flashiest part of market infrastructure, but it is essential.
If securities are going to move on-chain, recordkeeping becomes one of the most important questions.
Who is the official owner? How are transfers recorded? How are shareholder rights tracked? What happens when tokens move between wallets? How does blockchain activity connect to legal ownership?
A transfer agent role can help answer those questions.
Injective’s filing shows that the project is not only talking about tokenization as a broad theme. It is trying to position itself inside regulated market infrastructure.
Why This Matters For RWAs
Real-world assets have become one of crypto’s biggest institutional narratives.
Tokenized Treasuries, private credit, money market funds, equities, and other securities are all being explored by asset managers and blockchain companies. But regulated assets cannot simply be launched like memecoins.
They need legal structures, compliance processes, investor records, custody arrangements, transfer restrictions, and clear ownership rights.
That is why transfer agency matters.
A blockchain can move tokens quickly, but regulated markets still need official books and records. If Injective can support that function, it may become more useful for RWA issuers looking for blockchain-native infrastructure.
This does not guarantee adoption.
Filing a form is only one step. The market still needs issuers, investors, legal comfort, and operational execution. But it gives Injective a more serious role in the tokenization conversation.
The INJ Token Distinction Is Important
The filing should not be misunderstood as a statement about INJ’s own regulatory status.
Injective is seeking registration for a transfer agent function tied to securities recordkeeping. That is different from registering the INJ token itself as a security.
That distinction matters because crypto regulatory headlines are often misread quickly.
A filing with the SEC can sound dramatic, but the details determine what it actually means. In this case, the focus is infrastructure for regulated RWAs.
For INJ holders, the possible long-term relevance is indirect. If Injective becomes useful infrastructure for tokenized securities, that could strengthen the ecosystem. But the filing does not automatically create token demand or change INJ’s legal status.
Injective Wants A Bigger Institutional Role
Injective has historically been associated with DeFi, trading, and financial applications.
An SEC transfer agent filing pushes the project toward more regulated financial infrastructure. That aligns with the broader direction of the market. Crypto networks are no longer only competing for retail trading activity. They are competing to host tokenized financial products.
Ethereum, Avalanche, Solana, Stellar, Polygon, Sui, Aptos, and other ecosystems are all trying to win parts of the RWA market. Injective’s angle is to lean into finance-specific infrastructure and regulated recordkeeping.
That could help it stand out if the registration process advances.
But the next steps matter.
Investors will want to see whether the filing is accepted, whether Injective can attract issuers, and whether regulated RWA products actually launch using its infrastructure.
Without that follow-through, the filing remains a strategic signal.
With it, Injective could become part of the back-office layer for on-chain securities.
Tokenization Needs More Than Hype
The RWA market has already moved past simple tokenization slogans.
Institutions need systems that can handle compliance, reporting, ownership records, and investor protections. Blockchain networks that ignore those requirements may struggle to host regulated assets at scale.
Injective’s filing shows it understands that reality.
Instead of only promoting tokenized markets, it is trying to address one of the core pieces of regulated securities infrastructure. That is a more serious step than a generic RWA announcement.
For the broader crypto market, this is another sign that tokenization is becoming more formal and more regulated.
The next wave will not only be about putting assets on-chain. It will be about connecting blockchain rails with the legal and administrative systems that make securities markets function.
Injective is trying to place itself in that layer.
dYdX Chain’s v5.1 upgrade introduces smart contract capability and permissionless market listings, giving users a path to launch perpetual markets without relying on governance intervention.
That is a major shift for a derivatives-focused chain.
Perpetual exchanges depend on market coverage, liquidity, speed, and risk management. If users can create new markets more easily, dYdX may be able to support a broader range of assets and trading opportunities without waiting for every listing to move through governance.
The caveat is that technical flexibility does not automatically create trading volume.
New markets still need liquidity, demand, oracle support, and risk controls. But v5.1 gives the chain more flexible infrastructure.
TL;DR
dYdX Chain v5.1 adds smart contract capability.
The upgrade enables permissionless perpetual market listings.
The change may expand market coverage, but it does not guarantee higher volume.
Why Permissionless Listings Matter
Centralized exchanges can list new markets quickly because listing decisions sit with the exchange operator.
Decentralized exchanges often move more slowly, especially when governance approval is required. That can protect users from weak markets, but it also limits speed. In crypto, market demand can appear quickly, and traders often want access before governance processes finish.
Permissionless listings can change that dynamic.
If users or developers can create perpetual markets without full governance intervention, dYdX becomes more flexible. It can react faster to new assets, narratives, and trading demand.
That matters for derivatives.
Perpetual futures are one of crypto’s most active trading products. Traders want access to majors, altcoins, new tokens, ecosystem assets, and sometimes niche markets. The broader the market coverage, the more useful a derivatives venue can become.
But speed brings risk.
Not every asset is suitable for a perpetual market. Thin liquidity, poor oracle data, manipulation risk, and extreme volatility can create problems. Permissionless systems need safeguards.
Smart Contracts Add A New Layer
The smart contract capability introduced in v5.1 is another important piece.
dYdX Chain is built as an appchain with a specific emphasis on derivatives trading. Adding broader smart contract support can make the chain more programmable and adaptable.
That may allow developers to create new trading tools, listing systems, risk modules, or market infrastructure around the core exchange.
For dYdX, this helps the chain move beyond a tightly controlled market structure and toward a more open ecosystem.
That is a difficult balance. The platform needs enough openness to attract builders and markets, but enough control to keep trading safe and reliable.
v5.1 appears designed to move that balance toward more flexibility.
Liquidity Is Still The Hard Part
Permissionless listings are only valuable if traders use the markets.
A new perpetual market needs market makers, liquidity, oracle coverage, funding rate mechanics, risk limits, and demand from traders. Without those pieces, a listing may exist but remain inactive.
That is why volume should not be assumed.
The upgrade gives dYdX the ability to support more markets. It does not guarantee those markets will be liquid or profitable.
The strongest outcome would be a system where high-quality markets can appear faster while weak or risky markets are contained by safeguards. That would improve the exchange’s competitiveness without exposing users to unnecessary risk.
Execution will matter more than the announcement.
dYdX Is Competing In A Brutal Market
Crypto derivatives is one of the most competitive sectors in the industry.
Centralized exchanges still dominate much of the volume. Decentralized perpetual venues compete on transparency, custody, incentives, leverage, listings, execution quality, and fees.
dYdX has one of the strongest brands in decentralized derivatives, but it still needs to keep evolving.
The v5.1 upgrade helps because it attacks one of the key limitations of more governed market systems: speed. If new markets can be created with less friction, dYdX may be able to respond more quickly to trader demand.
But the broader challenge remains.
The chain needs liquidity and users. It needs market makers to support new listings. It needs risk systems that can handle volatile assets. It needs developers to build around the new smart contract functionality.
v5.1 gives dYdX more tools. Now the ecosystem needs to prove those tools can produce better markets.
For traders, the upgrade is worth watching because it could change how quickly new perpetual markets appear on dYdX Chain.
For the wider DeFi market, it shows appchains continuing to evolve from single-purpose systems into more programmable trading ecosystems.
Pyth Network has launched a USDY/USD price feed designed to support Ondo Finance’s yield-bearing USDY asset across Aptos and Sui DeFi ecosystems.
The feed gives developers and protocols real-time pricing data for USDY, which is important if the asset is used in lending markets, collateral systems, trading products, or other on-chain financial applications.
That makes the update a small but meaningful piece of real-world asset infrastructure.
USDY is not just another token in this context. It represents a yield-bearing note structure, and DeFi protocols need reliable pricing before they can safely integrate assets like that.
TL;DR
Pyth has launched a USDY/USD price feed.
The feed supports Ondo’s USDY across Aptos and Sui DeFi ecosystems.
Reliable oracle data is essential before yield-bearing RWAs can be used in lending, collateral, or trading products.
Why A USDY Feed Matters
Real-world assets are only useful on-chain if applications can price them reliably.
A tokenized Treasury product, yield-bearing note, or RWA-backed asset may have strong demand, but DeFi protocols still need accurate market data. Without it, lending markets can misprice collateral, liquidations can fail, and traders may face unnecessary risk.
That is where oracle networks come in.
Pyth provides price feeds that applications can use to read asset values on-chain. A USDY/USD feed gives Aptos and Sui developers a more direct way to integrate USDY into financial products.
This does not automatically mean large DeFi growth. It simply removes one important infrastructure barrier.
Before an asset can become useful collateral or a trading pair, protocols need to know what it is worth.
Aptos And Sui Are Building RWA Support
Aptos and Sui are both newer high-performance Layer 1 networks that are competing for developers, DeFi activity, and institutional use cases.
Adding support for RWA pricing helps both ecosystems broaden their financial infrastructure.
For Sui, the update fits into a wider push around DeFi, payments, and enterprise-friendly features. For Aptos, it adds another building block for applications that want to use tokenized yield assets.
The important part is that RWAs need more than token issuance.
An issuer can launch a tokenized asset, but ecosystems still need wallets, exchanges, lending markets, oracles, compliance tooling, custody infrastructure, and liquidity. Price feeds are one part of that stack.
Pyth’s USDY feed therefore makes the asset easier for developers to work with.
Ondo’s USDY Needs Reliable Market Plumbing
Ondo Finance has been one of the more visible names in tokenized real-world assets.
USDY is designed as a yield-bearing product, which makes it different from a simple stablecoin. That difference can be useful, but it also creates extra complexity for DeFi integrations.
Protocols need to understand how the asset behaves, how it is priced, and how quickly values update. A clean oracle feed can help reduce some of that uncertainty.
For lending markets, the feed is especially important.
If USDY is used as collateral, pricing needs to be reliable enough to support risk parameters and liquidation systems. If it is used in trading, users need confidence that markets are referencing accurate data.
That does not remove all RWA risk.
Investors still need to understand the asset structure, issuer risk, liquidity, redemption mechanics, and legal framework. But without price data, most DeFi integrations cannot even begin.
RWA Infrastructure Is Getting More Granular
The tokenized asset story is often discussed in large terms: trillions of dollars in real-world assets coming on-chain, tokenized Treasuries, institutional adoption, and new financial rails.
In practice, adoption happens through smaller infrastructure steps.
A new price feed. A new collateral market. A wallet integration. A custody update. A new chain deployment. A risk framework.
Pyth’s USDY/USD feed belongs in that category.
It may not be a flashy consumer story, but it helps make tokenized yield assets more usable on Aptos and Sui. That is how RWA markets develop: one integration layer at a time.
The next thing to watch is whether DeFi protocols on those networks actually adopt the feed and build products around USDY.
If they do, the feed could help deepen RWA liquidity across both ecosystems.
If they do not, it remains useful infrastructure waiting for application demand.
Either way, the launch shows that oracle networks are becoming central to the RWA expansion story. Tokenized assets need trusted data, and Pyth is positioning itself as one of the providers helping newer chains support that market.
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