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🌐Hooks: Smart Contracts for the XRP Ledger🌐
January 17, 2023
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One of the key features that sets the XRP Ledger (XRPL) apart from other blockchains is its ability to do things natively, such as token issuing, escrows, and decentralized trading.

Other chains require smart contracts to do those same things. All these and more are built into the XRPL, making it efficient and well-documented.

Adding Hooks to the XRPL increases its functionality and expands the range of potential services on offer for retail and enterprise users.

What are Hooks?

Hooks allow the creation of customized logic and automation within the XRPL, making transactions smarter and more convenient.

These small, efficient modules add custom on-ledger functionality, such as creating custom triggers for specific events on the ledger. These triggers can be used to send on-ledger actions or execute other actions in response to the specified event.

Hooks are currently only available on theĀ XRPL Labs public Hooks testnet,Ā as the feature is under development.

There is aĀ Hooks Builder siteĀ where you can develop, test, debug, and deploy your own Hooks on testnet in your browser, using our examples or building your own from scratch.

Why are Hooks a big deal?

Simply put, Hooks add smart contract functionality to the XRPL. They give you the freedom to build and deploy your applications with functionality tailored to your specific needs and requirements. They can be used to implement most business logic and smart contract ideas.

Once a hook is set up on an account, it can allow you to:

  • Block or allow transactions to and from the account.
  • Change and keep track of the hook’s internal state and logic to inform programmatic choices.
  • Send out new transactions on the account’s behalf.

Hooks can be written in C or any other language and then compiled into WebAssembly.

Some examples of specific Hooks

Auto-Savings Hook

Automatically transfer a set amount of XRP into a separate savings account on the ledger. This could be done regularly, such as daily, weekly, or monthly, to help the person save a portion of their XRP and build up their savings.

Carbon-Offset Hook

When sending funds, an extra transaction is sent out for 1% of the amount spent. This transaction is sent to a carbon offset account run by a non-governmental organization (NGO), which will use the money to plant trees.

Firewall Hook

Malicious small transactions containing memos or outgoing payments to confirmed scam accounts are blocked. The hook can retrieve a blocklist from a different hook installed on a different account. This means the user does not need to update their firewall to remain safe. Additionally, the user can impose spending limits to prevent high amounts from being withdrawn.

How do Hooks differ from an Ethereum Virtual Machine (EVM)?

XRPL Hooks and the EVM both allow developers to build and deploy custom logic and automation within their respective platforms. However, some key differences between these two technologies set them apart.

One of the main differences between Hooks and EVM is the platform they are designed to work with. Hooks are specifically designed to work within the XRP Ledger, while EVM smart contracts only work with Ethereum-based blockchains.

Hooks are more efficient because they use WebAssembly (WASM), which is faster and more efficient than the bytecode used by the Ethereum Virtual Machine.

Additionally, XRPL Hooks use guards to ensure that maximum execution time is well-bounded and known ahead of time, which helps to improve efficiency.

Alternatives to Hooks on the XRPL

Ripple and Peersyst announced that an EVM-compatible sidechain is now liveĀ on the company’s devnet.

A sidechain is an independent ledger with its own consensus algorithm and transaction types and rules. It acts as its own blockchain.

The EVM sidechain is an alternative to Hooks that adds a type of smart contract functionality to the ecosystem.

However, sidechains operate on Layer 2, so any smart contracts running on the sidechain are not directly integrated into the XRPL.

In order to use the smart contract functionality of the sidechain, XRP first has to be swapped onto the sidechain, then later swapped back. This means the transaction essentially gets processed twice. Once on the sidechain, then again on the XRPL, meaning Layer 2 smart contracts cannot influence the flow.

Hooks can decide if a transaction is allowed in the first place. Layer 2 can make a retroactive decision, but the initial transaction has already happened.

Hooks are more closely integrated with XRPL, operating directly on Layer 1 of the XRPL, so they are more tightly integrated with the underlying blockchain technology than the EVM-Compatible Sidechain to take advantage of the specific features and capabilities of the XRPL platform.

Hooks are implemented using WebAssembly, designed for high-performance environments such as edge computing.

Hooks will expand the on-ledger functionality and help XRPL grow

Hooks will bring native smart contract functionality to the XRPL, allowing the development of custom applications tailored to the specific needs and requirements of the account holder, opening up whole new domains of functionality, as the possibilities with Hooks are almost unlimited.

As the XRPL continues to grow, there is no doubt that Hooks will play a significant role in driving further innovation and adoption of the platform by retail and enterprise users.

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ā€‹šŸšØ BREAKING: The Final Clarity Act Bill Text is Official! šŸ‡ŗšŸ‡øšŸ”„

​After more than a year of back-and-forth, the final draft is here—incorporating 126 last-minute amendments requested by Democrats just 24 hours before the vote. 🤯

​Key updates in the final text:

​Strict Ethics Oversight: Expanded restrictions now cover federal officials, judges, and spouses, with Senator Lummis noting Trump opted in voluntarily.
​Banking Safeguards: Treasury gains authority to step in if high-yield stablecoins start draining liquidity from community banks.

​Builder Protections: Civil safe harbor provisions have been strengthened to explicitly cover crypto miners and network validators.

​Market Integrity: Added guardrails target conflicts of interest and affiliate trading while leaving state consumer protection laws intact.

​Does it have enough momentum to secure 60 votes tomorrow? šŸ‘€

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RFK Jr: "The Pandemics are coming from labs. ALL OF THEM... Lyme, COVID, RSV, HIV & Spanish Flu came out of a vaccine lab." ā˜ ļø šŸ’‰

"Gain-of-Function Vaccine research has created the worst plagues in our history."

"We can go down the whole list of diseases... It’s just a disaster. It’s given us no benefits. It’s given us everything from Lyme disease to Covid, and many many other diseases. RSV, which is now one of the biggest killers of children, came out of a vaccine lab."

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"The 'PANDEMICS' are coming from labs... ALL OF THEM."

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šŸš€The industry has gotten incredible at teaching robots

šŸš€The industry has gotten incredible at teaching robots to move, sprint, and imitate body dynamics. But as Michael Parker (@bittensormax) points out in The UMI Thesis, there’s still a massive missing piece in Physical AI: Motion Understanding.

✨ Key Takeaways:

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šŸ”¹Motion is Meaning: A gesture, hesitation, or glance changes completely depending on posture, timing, and surrounding context.

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The future of robotics isn't just about how machines move—it's about how ...

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šŸ”‘ Key points

šŸ”¹ Chutes is live in production and reportedly scaled to more than 1,170 active GPU nodes, including large numbers of Nvidia H200s and Blackwell-class hardware.

šŸ”¹ The platform says it has processed nearly 38 trillion tokens since launch across 53 deployed applications and more than 700,000 registered users.

šŸ”¹ The team reportedly cut unprofitable usage programs, reduced total token volume, and still improved revenue efficiency, with revenue per GPU rising sharply after removing subsidized traffic.

šŸ”¹ Chutes is using post-quantum cryptography, trusted execution environments, and Nvidia confidential ...

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A new clash is emerging between legacy finance and crypto legislation after JPMorgan CEO Jamie Dimon reportedly warned that the CLARITY Act could let crypto firms offer bank-like products without bank-level oversight. The dispute is quickly turning into a larger fight over regulation, competitiveness, and who controls the future architecture of digital finance in the United States.

šŸ”‘ Key points

šŸ”¹ Jamie Dimon reportedly called the CLARITY Act a threat to the financial system, arguing it could allow crypto firms to offer yield-like products while avoiding the capital, reserve, and oversight burdens traditional banks face.

šŸ”¹ Senator Cynthia Lummis pushed back publicly, framing the issue as a global strategic race and warning that if the U.S. does not set digital asset standards, other powers will.

šŸ”¹ The core tension is whether the bill creates legitimate regulatory clarity or simply opens the door to regulatory arbitrage for crypto platforms operating outside the traditional banking...

🚨 JPMorgan’s criticism of the CLARITY Act is fueling a fresh power struggle over who gets to write America’s crypto rules 🚨
šŸ‘‰ Coinbase just launched an AI agent for Crypto Trading

Custom AI assistants that print money in your sleep? šŸ”œ

The future of Crypto x AI is about to go crazy.

šŸ‘‰ Here’s what you need to know:

šŸ’  'Based Agent' enables creation of custom AI agents
šŸ’  Users set up personalized agents in < 3 minutes
šŸ’  Equipped w/ crypto wallet and on-chain functions
šŸ’  Capable of completing trades, swaps, and staking
šŸ’  Integrates with Coinbase’s SDK, OpenAI, & Replit

šŸ‘‰ What this means for the future of Crypto:

1. Open Access: Democratized access to advanced trading
2. Automated Txns: Complex trades + streamlined on-chain activity
3. AI Dominance: Est ~80% of crypto šŸ‘‰txns done by AI agents by 2025

🚨 I personally wouldn't bet against Brian Armstrong and Jesse Pollak.

šŸ‘‰ Coinbase just launched an AI agent for Crypto Trading

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šŸ”¹ Family coverage must expand: The current language covers officials and spouses. Democrats want it extended to children and other family members involved in crypto ventures.

šŸ”¹ Ethics rules should be permanent: The current provisions sunset on January 20, 2029. Democrats want the restrictions to continue beyond the current presidential term.

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TaoStats provides a simplified way to acquire Bittensor subnet tokens by connecting a wallet, selecting a subnet, and swapping TAO for the corresponding alpha token.

šŸ”‘ Key points

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šŸ”¹ Choose a subnet: TaoStats displays available subnet information, including alpha prices, market capitalization, liquidity, and emissions.

šŸ”¹ Review the market first: Users should check liquidity, trading volume, price movement, circulating supply, and recent emissions before swapping.

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šŸ”‘ Key points

šŸ”¹ Six decades of open work: The problem had remained unresolved for approximately 66 years.

šŸ”¹ AI-assisted discovery: Conjecture uses computational systems to explore mathematical structures, test cases, and search for potential solutions.

šŸ”¹ Distributed contributors: Miners can compete to generate candidate constructions, proofs, counterexamples, or reductions.

šŸ”¹ Verification is essential: A proposed result must be checked through formal reasoning or independently reproducible computation.

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September 13, 2026
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Revolut Leak Shows the Cost of Constant ID Collection
Revolut’s mistake is the news, but the bigger problem is the growing number of companies being encouraged or required to keep copies of our most sensitive identity documents.

Online bank Revolut has revealed that it gave out sensitive personal and financial information of an undisclosed number of its customers in response to a fake government request.

The information that was handed over to an ā€œunauthorized third partyā€ reportedly includes names, dates of birth, occupations, addresses, phone numbers, account numbers, transaction histories (including Bitcoin), and even copies of government-issued IDs and onboarding verification selfies.

Revolut claims that derived biometric face data was not.

The company said that the data was handed over in response to an email that came from a real government agency’s domain, but was not actually sent or authorized by that agency.

The email passed several authentication checks (SPF, DKIM, and DMARC) that are designed to establish the authenticity of a message’s origin and integrity, but do not verify the legitimacy of the legal request itself.

Revolut said that it complied with the request ā€œunder the reasonable belief that it was an authentic government agency requestā€ – and only later found out that it was not.

Revolut said it later realized its mistake, blocked the email address, and reported the incident to the relevant authorities.

Revolut said that only a ā€œlimitedā€ number of its customers were affected by the data leak, and that the company’s systems were not hacked, nor was any money stolen.

The story broke on September 11 when Revolut customers started receiving an email notice about a data leak, and the news was picked up by media outlets the following day.

Revolut notice explaining customer identity and financial data was shared after an unauthorized government email request.

The reason this is a recurring problem is that companies are keeping highly sensitive information about their customers’ identities, and sometimes even financial transactions, for a long time, and this data is then available to be disclosed to third parties – either in response to valid legal requests, or, as in the case of Revolut, fake ones.

One reason for this is know your customer (KYC) and anti-money laundering (AML) rules. Revolut’s current UK customer privacy notice spells it out: the company generally keeps personal data of UK customers for no more than seven years after the relationship ends, and sometimes longer – for legal reasons.

This means that even if you close your account, your identity documents don’t disappear.

And while the incident with Revolut happened in the financial sector, it’s by no means the only one that requires customers to hand over sensitive identity information. Discord, a popular chat service, said in an October 9, 2025 security update that government ID photos of approximately 70,000 users may have been exposed after a third-party customer service provider got hacked.

This was not a financial service, nor the same type of attack. But the result was similar – because the underlying business process was the same: requiring and storing sensitive identity documents. In the case of Discord, these were used to review age-related appeals.

It’s hard to do anything about a copy of your old passport, or a photo of your face, or a record of your past transactions. These can be used to identify and profile you, and can be used to carry out targeted fraud. And this can happen even if the initial disclosure didn’t result in financial loss.

The more companies are forced to collect and store such information, and the more of it they have, the more opportunities there are for this data to be leaked, either by the company itself or a third party it works with. That's what makes governments' push for more ID checks just to access ordinary parts of life so reckless.

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This Is The Income A Family Needs To Live Comfortably In Every US State

Here’s the short version of what it takes for a family of four to live comfortably in 2026 by state:

In Massachusetts, you’d need nearly $330,000 a year - the highest figure in the entire country. Only three states clear the $300,000 mark: Massachusetts, Hawaii, and California. At the other end of the spectrum, Mississippi is the most affordable at about $188,000. That’s a full $142,000 less than what you’d need in Massachusetts.

So… how much does a family of four need in your state?

This map shows the pre-tax income a household with two working adults and two kids needs to live comfortably in every U.S. state.

The numbers come fromĀ SmartAssetĀ (as of February 2026). They’re based on the familiar 50/30/20 budget: 50% for necessities, 30% for discretionary spending, and 20% for savings or other goals. These aren’t bare-minimum survival numbers—they’re what it takes to live pretty well while still putting money aside.

And asĀ Visual CapitalistĀ notes,Ā Massachusetts sits at the very top of that list.Ā Massachusetts tops the ranking, with a family of four needing $329,555 per year to meet the 50/30/20 benchmark.

Hawaii follows at $313,165, while California ranks third at $302,682.

Rank State Income needed for family of four (2026)

  • 1 - Massachusetts - $329,555
  • 2 - Hawaii - $313,165
  • 3 - California - $302,682
  • 4 - Connecticut - $298,189
  • 5 - New Jersey - $295,110
  • 6 - New York - $291,533
  • 7 - Colorado - $283,213
  • 8 - Washington - $281,798
  • 9 - Oregon - $280,966
  • 10 - Vermont - $280,384
  • 11 - Alaska - $272,064
  • 12 - New Hampshire - $267,904
  • 13 - Rhode Island - $264,659
  • 14 - Minnesota - $263,078
  • 15 - Maryland - $257,837
  • 16 - Maine - $250,931
  • 17 - Montana - $249,434
  • 18 - Pennsylvania - $247,936
  • 19 - Illinois - $244,109
  • 20 - Virginia - $242,944
  • 21 - Nevada - $242,278
  • 22 - Indiana - $241,696
  • 23 - Wisconsin - $238,451
  • 24 - Arizona - $236,870
  • 25 - Utah - $235,789
  • 26 - Delaware - $228,134
  • 27 - Ohio - $226,221
  • 28 - Idaho - $226,054
  • 29 - Florida - $223,392
  • 30 - New Mexico - $223,142
  • 31 - Nebraska - $223,059
  • 32 - Missouri - $217,734
  • 33 - Georgia - $214,573
  • 34 - Michigan - $214,323
  • 35 - South Carolina - $212,909
  • 36 - North Carolina - $212,410
  • 37 - Wyoming - $212,410
  • 38 - Oklahoma - $211,910
  • 39 - North Dakota - $210,496
  • 40 - Kansas - $207,917
  • 41 - Iowa - $204,422
  • 42 - Texas - $203,424
  • 43 - West Virginia - $202,592
  • 44 - South Dakota - $201,760
  • 45 - Alabama - $198,931
  • 46 - Louisiana - $197,933
  • 47 - Tennessee - $197,267
  • 48 - Arkansas - $195,437
  • 49 - Kentucky - $194,854
  • 50 - Mississippi - $187,533

Connecticut, New Jersey, and New York aren't far behind, bringing the number of states with comfortable-income thresholds above $290,000 to six.

Colorado and Vermont Make the Top 10

As expected, many of the highest income thresholds are concentrated in the Northeast and along the West Coast.

However, Colorado has the seventh-highest threshold in the country at $283,213, ranking above Washington and Oregon.

Vermont rounds out the top 10 at $280,384, despite having theĀ second-smallest populationĀ of any U.S. state. Meanwhile, nearby states like New Hampshire, Maine, and Rhode Island all fall outside the top 10.

Just Six States Come in Below $200,000

Despite theĀ wide range in living costsĀ across the country, only six states have a comfortable-income threshold below $200,000 for a family of four.

Mississippi ranks lowest at $187,533, followed by Kentucky.Ā The states of Arkansas, Tennessee, Louisiana, and Alabama also fall below the $200,000 mark.

The gap between Massachusetts and Mississippi exceeds $142,000 per year, meaning the Massachusetts benchmark is about 76% higher.

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šŸ¤–Can Decentralized AI Stop Big Tech from Owning the Future of Robotics?šŸ¤–
The race to build the future of robotics is no longer just about robots. It's about who controls the intelligence behind them.
Ā 
Over the last three years, a small group of companies has emerged as the backbone of the AI revolution. Microsoft provides cloud infrastructure. NVIDIA supplies the chips. Google, OpenAI, Anthropic, Meta, and others develop the models. Together, they control much of the compute, data, and software stack powering modern AI.
Ā 
Now that AI is moving into the physical world, many are asking a bigger question:
Ā 
Will these same companies end up controlling robotics too?
Ā 
It's a valid concern.
Ā 
The latest generation of robots relies on enormous amounts of compute, simulation, training data, and foundation models. Many robotics startups today are built on infrastructure provided by large technology companies. NVIDIA's Omniverse is becoming a key simulation environment for robot training. Microsoft Azure is powering the training of robotics foundation models. Physical AI startups increasingly depend on hyperscale cloud infrastructure to train and deploy intelligent systems. Recent partnerships across the industry show just how central Big Tech has become to robotics development.
But while Big Tech is building the highways, another movement is trying to ensure it doesn't own every destination.
Ā 
That movement is decentralized AI.
Ā 
Why Decentralized AI Exists
Ā 
The idea behind decentralized AI is simple. Instead of a handful of companies owning the models, compute infrastructure, data pipelines, and intelligence networks, these resources are distributed across thousands of participants.
Ā 
This means anyone can contribute compute, contribute models, validate outputs and can participate.
The most visible example today is the decentralized AI network known as Bittensor (@bittensor). The network has evolved into a large ecosystem of specialized AI markets called subnets, where participants compete to provide useful machine intelligence and are rewarded based on performance. Rather than relying on a single company, intelligence is generated and validated by a distributed network of miners and validators.
Ā 
Think of it as an attempt to build an open marketplace for AI instead of a world where intelligence is rented from a few centralized providers.
Ā 
Why This Matters for Robotics
Ā 
Robotics has a unique problem. Unlike chatbots, robots operate in the physical world. They need to perceive environments, make decisions, move safely and they need to learn continuously.
Ā 
The challenge is that collecting and training on real-world robotic data is incredibly expensive. That's one reason large companies have such an advantage. They can afford the compute, simulation environments, and data infrastructure needed to train robotics models at scale.
Ā 
This is where decentralized systems become interesting.
Ā 
Instead of one company collecting all the data and training all the models, decentralized networks could allow thousands of contributors to participate in building robotic intelligence.
Ā 
Imagine a future where:
  • Warehouse robots contribute operational data.
  • Delivery robots contribute navigation data.
  • Factory robots contribute manipulation data.
  • Developers contribute models.
  • Validators evaluate performance.
The resulting intelligence becomes a shared network rather than a proprietary asset.
Ā 
That vision is beginning to emerge.
Ā 
Bittensor's Move Toward Physical AI
Ā 
While many people associate Bittensor (@bittensor) with language models and AI services, parts of the ecosystem are increasingly exploring embodied intelligence and robotics.
Ā 
One example is Kinitro, a subnet focused on incentivizing the training and evaluation of embodied AI systems. The goal is to create competitive environments where developers build robotic intelligence and are rewarded based on performance.
Ā 
The broader Bittensor ecosystem has also expanded into compute marketplaces, distributed inference systems, bandwidth infrastructure, and AI coordination layers that could eventually support robotics workloads. Several subnets now focus on decentralized compute, confidential inference, data transfer, and model training, critical components for future robotic systems.
Ā 
In other words, the pieces are starting to appear.
Ā 
Not a decentralized robot network yet.
Ā 
But the infrastructure that could support one.
Ā 
Beyond Bittensor: The Rise of Physical AI Networks
Ā 
Bittensor isn't alone.
Ā 
Across the industry, researchers and builders are experimenting with decentralized approaches to physical AI.
Ā 
New research published in 2026 introduced the concept of DAO-enabled decentralized physical AI, or DePAI. The idea combines robotics, decentralized infrastructure, AI models, governance systems, and human oversight into a single framework. Instead of centralized control, robots and physical infrastructure could be coordinated through transparent rules and distributed ownership models.
Ā 
At the same time, developers are exploring decentralized operating systems for robots that allow machines to communicate directly with each other and with distributed compute resources. These architectures are designed to make robotic systems more resilient and less dependent on a single cloud provider.
Ā 
The goal is not simply decentralization for its own sake.
Ā 
The goal is resilience.
Ā 
If one server fails, the system continues.
Ā 
If one company disappears, the network survives.
Ā 
If one participant leaves, innovation continues.
Ā 
But Here's the Reality
Ā 
Decentralized AI faces the same challenge every decentralized technology faces.
Ā 
Big Tech has resources. A lot of resources.
Ā 
Training advanced robotics models requires enormous compute budgets, sophisticated simulation environments, access to specialized hardware, and vast amounts of real-world data.
Ā 
That's why many robotics startups still partner with major cloud providers and AI companies. It's often the fastest path to deployment.
Ā 
And there are legitimate concerns about whether decentralized networks can maintain quality, reliability, and security at the scale required for industrial robotics. Even researchers studying decentralized AI systems have highlighted risks around concentration, incentives, governance, and network security.
Ā 
The challenge isn't just decentralizing intelligence.
Ā 
It's decentralizing intelligence while maintaining performance.
Ā 
That's much harder.
Ā 
The Most Likely Outcome
Ā 
The future probably won't be fully centralized. And it probably won't be fully decentralized either. Instead, we're likely heading toward a hybrid model.
Ā 
Large technology companies will continue providing chips, cloud infrastructure, simulation platforms, and foundational research.
Ā 
At the same time, decentralized AI networks will emerge as alternative coordination layers where intelligence, data, and economic value can be shared more openly.
Ā 
The companies building robots may use NVIDIA hardware.
Ā 
Train on Azure.
Ā 
Run foundation models from OpenAI.
Ā 
But they may also participate in decentralized data networks, decentralized compute markets, and decentralized intelligence protocols.
Ā 
The future of robotics could end up looking less like a monopoly and more like an ecosystem.
Ā 
The Bigger Question
Ā 
The real question isn't whether decentralized AI can eliminate Big Tech.
Ā 
It can't.
Ā 
At least not anytime soon.
Ā 
The real question is whether decentralized AI can prevent a future where a handful of companies control every robot, every model, every dataset, and every decision made by the machines operating around us.
Ā 
As robots become workers, assistants, delivery drivers, factory operators, and even economic agents, that question becomes increasingly important.
Ā 
Because the battle for the future of robotics is no longer about hardware.
Ā 
It's about who owns the intelligence.
Ā 
And that battle is just getting started.
Ā 
Ā 

šŸ™To support my work, Helping to keep the signal high and the noise low:

šŸ‘‰ Cashapp: $thedinarian

šŸ‘‰ Buy me a coffee: https://buymeacoffee.com/thedinarian

šŸ‘‰ PayPal: Scan the QR code below šŸ“² or Click Here:Ā 

šŸ‘‡ Crypto Donations šŸ‘‡

XRP: r9pid4yrQgs6XSFWhMZ8NkxW3gkydWNyQX
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google store google store app tv store app tv store amazon store amazon store roku store roku store
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