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How do Digital RMB smart contracts work? First supply chain finance use cases
September 25, 2023
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ICBC China’s biggest bank and e-commerce giant JD.com have worked together to develop a supply chain finance solution based on digital RMB smart contracts. To date, the emphasis has been on consumer CBDC smart contracts, so this is one of the first business applications. 

This raises an interesting question: how does the broader smart contract ecosystem work, given they trigger central bank digital currency (CBDC) payments? And a much bigger question: What does this mean for the future of banking?

JD.com supply chain finance & digital RMB

Earlier this month, JD.com was involved in the first supply chain finance credit that was entirely automated using digital RMB. CBDC aside, supply chain finance solutions often involve a large company working with its bank to supply credit to its suppliers. 

In this case, large companies pay the funds directly and instantly to the suppliers using CBDC, avoiding bank settlement delays. Combining a CBDC and smart contracts, JD.com highlighted how it’s possible to work directly with multiple financiers without using a third party provider. Later we’ll explore the implications of this.

Meanwhile, smart contracts are pieces of programming code. Given the digital yuan is used only for the payment leg, the majority of the code is around business applications. For example, if someone orders a food delivery and pays upfront with the CBDC, it will lock the currency as a prepayment. But much of the code will involve logging the food order, calculating the amount due, and recording the customer accepting the delivery. Only then is the money released to the restaurant.

How digital yuan smart contracts work

Smart contracts are on a separate system from the CBDC but are used to add payment conditionality and programmability. 

In the same way that banks distribute the centralized CBDC in China, they are also used to access smart contracts. 

The smart contract platform is surprisingly open. It is a little like an open source version of Apple iOS apps. 

Organizations can work with and through the big banks to develop smart contracts based on central bank rules and standards. Then the banks submit the smart contracts to the central platform for review. That’s not dissimilar to submitting iPhone apps to the Apple appstore. 

The review isn’t just technical but also looks at the legality of the smart contract. Presumably that might involve the smart contract platform liaising with other regulators. Once the code is approved, it becomes an open source template so others can re-use it.

While approval is centralized, we’re not 100% clear whether the smart contract would run on the bank’s infrastructure or the central banks’. The platform adheres to the principle of “centralized management and two-tier operation structure,” which might imply that smart contracts are executed on the infrastructure of the big state banks.

Given the banks already implement a layer of security around CBDC transactions, there’s some logic in them hosting the smart contracts.

A year ago, Mu Changchun, the head of the central bank’s Digital Currency Research Institute, outlined the framework for smart contracts. He mentioned that code development needs to be both secure and convenient. And it should take advantage of the expertise of different agencies and institutions. 

He also emphasized the importance of interoperability. This includes interoperability of smart contract systems and external systems, particularly for identity and compliance.

Meanwhile, to use the smart contract, businesses interact via an API.

Is digital RMB programmable money?

The central banks of the EU and England have rejected the idea of programmable money. That means that units of money can only be used to buy specific types of goods or services. In contrast, programmable payments define the business logic for payments.

At its core, we don’t believe the digital RMB is programmable money. However, in conjunction with smart contracts, it looks similar.

ICBC revealed that most of China’s digital RMB ‘red envelope’ giveaways are based on programmable smart contracts. In some cases, the goal was to promote the adoption of the CBDC, but others related to COVID. Often recipients could only spend the red envelope CBDC at certain merchants, and the smart contracts would impose that restriction. Also the red envelopes had expiry dates, so smart contracts reclaim unused currency at the end of the validity period.

Analysis: how CBDC smart contracts impact commercial bank money

In the UK, Barclays recently wrote a paper about the functional consistency of money and the potential digital pound. One of the takeaways was that bank deposit tokens and CBDC might want to share the same (centralized) programmability layer. That helps with full interoperability.

But the key point Barclays was making is that to preserve the singleness of money, different types of money need to have the same functionality. That ranges from the ability to withdraw cash at an ATM to programmability.

In China’s case, to what extent can banks integrate their own payments with the digital RMB smart contract platform? Or is that functionality restricted to the CBDC?

For years, ICBC has already used smart contracts with bank payments. And it recently integrated its existing blockchain with the digital RMB smart contract platform. 

However, smart contracts could still put commercial bank money at a disadvantage. That’s because someone can’t necessarily use RMB smart contracts for a payment from any commercial bank. If they could, that might level the playing field between big and small banks.

Analysis: Does CBDC commoditize banking services?

A second point relates to open source. From a societal perspective, open source is enormously beneficial because innovation is accelerated as people build on each other’s innovations. 

In China, with two dominant financial players Tencent/WeChat Pay and Ant/Alipay, an explosion of code sharing could start to level the playing field. On the other hand, when many services become commoditized, it can benefit those with brands and scale.

How will banks in the West respond to a concept like this? There’s no question that many activities are replicated across every bank with no competitive advantage. For these functions, open source makes sense. However, most have existing legacy systems which they might be slow to upgrade. So the primary beneficiaries might be new entrants. 

And if higher value activities became open source and automated, it could impact competitive advantage.

Finally, the supply chain example appears to demonstrate the potential for a CBDC to disintermediate banks – not just for payments but for other functionality. Often a single bank is the primary conduit for supply chain finance, but in the digital RMB, there are competing financiers. That said, many trade finance platforms already enable multiple lenders to compete on a single platform. Here, it is those platforms that become disintermediated.

A path to narrow banking?

Zooming out to a distant future, one possibility is banks competing for lending opportunities on centralized smart contract platforms – not just for trade finance but for all lending. This looks similar to the vision of narrow banking proponents who see lending as the commercial bank’s primary (sole) role.

It has all sorts of implications for commercial banks and existing platforms for trade finance or other banking services.

Most of all, it raises major questions about the breadth of the role of the central bank.

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​🚨 BREAKING: The Final Clarity Act Bill Text is Official! 🇺🇸🔥

​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? 👀

00:00:09
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September 13, 2026
RFK Jr: "The Pandemics are coming from labs. ALL OF THEM... Lyme, COVID, RSV, HIV & Spanish Flu came out of a vaccine lab." ☠️ 💉

"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."

"There’s strong evidence that even Spanish flu came from vaccine research."

"There’s plenty of evidence that HIV also came from a vaccine gain-of-function lab program. "

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

00:04:00
🚨 Chutes is being framed as a Hyperliquid-style breakout for decentralized AI inference, with live revenue, verified GPU infrastructure, and a direct challenge to centralized cloud AI 🚨

Chutes is gaining attention as a decentralized AI inference platform that claims to combine real usage, cryptographic verification, confidential computing, and open-source infrastructure into a working production system. The thesis is simple: instead of trusting Big Tech clouds with AI workloads, users get a distributed compute layer built around verification and privacy.

🔑 Key points

🔹 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.

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🚨 Chutes is being framed as a Hyperliquid-style breakout for decentralized AI inference, with live revenue, verified GPU infrastructure, and a direct challenge to centralized cloud AI 🚨
🚨 JPMorgan’s criticism of the CLARITY Act is fueling a fresh power struggle over who gets to write America’s crypto rules 🚨

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.

🔑 Key points

🔹 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.

🔹 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.

🔹 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 🚨
👉 Coinbase just launched an AI agent for Crypto Trading

Custom AI assistants that print money in your sleep? 🔜

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

👉 Here’s what you need to know:

💠 'Based Agent' enables creation of custom AI agents
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👉 What this means for the future of Crypto:

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

👉 Coinbase just launched an AI agent for Crypto Trading
🌎 Schumann Resonance Today 9/15 🌎

Right now the Schumann resonance fundamental sits at 7.83 Hz, with geomagnetic activity unsettled (Kp 3.0).

Quiet Field, Clear Signal
A Kp of 3.00 and slow solar wind keep Earth's electromagnetic environment unusually settled today — a window worth using.

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⚖️ CLARITY Act ethics fight centers on Trump-linked crypto concerns ahead of September 15 vote ⚖️

Senate Democrats have demanded major changes to the CLARITY Act’s crypto-ethics provisions before supporting Tuesday’s cloture vote. Republicans say the latest text includes 126 Democratic-requested changes, but seven Democratic votes are still needed.

🔑 Key points

🔹 State AG enforcement: Democrats want state attorneys general to prosecute violations alongside the DOJ if federal officials refuse to act.

🔹 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.

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

🔹 Existing holdings must be divested: Democrats oppose allowing officials to place significant crypto interests in a blind trust instead of selling ...

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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 “unauthorized third party” 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 “under the reasonable belief that it was an authentic government agency request” – 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 “limited” 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 from SmartAsset (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 as Visual Capitalist notesMassachusetts sits at the very top of that list. 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 the second-smallest population 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 the wide range in living costs 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. 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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🤖Can Decentralized AI Stop Big Tech from Owning the Future of Robotics?🤖
The race to build the future of robotics is no longer just about robots. It's about who controls the intelligence behind them.
 
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.
 
Now that AI is moving into the physical world, many are asking a bigger question:
 
Will these same companies end up controlling robotics too?
 
It's a valid concern.
 
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.
 
That movement is decentralized AI.
 
Why Decentralized AI Exists
 
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.
 
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.
 
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.
 
Why This Matters for Robotics
 
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.
 
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.
 
This is where decentralized systems become interesting.
 
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.
 
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.
 
That vision is beginning to emerge.
 
Bittensor's Move Toward Physical AI
 
While many people associate Bittensor (@bittensor) with language models and AI services, parts of the ecosystem are increasingly exploring embodied intelligence and robotics.
 
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.
 
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.
 
In other words, the pieces are starting to appear.
 
Not a decentralized robot network yet.
 
But the infrastructure that could support one.
 
Beyond Bittensor: The Rise of Physical AI Networks
 
Bittensor isn't alone.
 
Across the industry, researchers and builders are experimenting with decentralized approaches to physical AI.
 
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.
 
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.
 
The goal is not simply decentralization for its own sake.
 
The goal is resilience.
 
If one server fails, the system continues.
 
If one company disappears, the network survives.
 
If one participant leaves, innovation continues.
 
But Here's the Reality
 
Decentralized AI faces the same challenge every decentralized technology faces.
 
Big Tech has resources. A lot of resources.
 
Training advanced robotics models requires enormous compute budgets, sophisticated simulation environments, access to specialized hardware, and vast amounts of real-world data.
 
That's why many robotics startups still partner with major cloud providers and AI companies. It's often the fastest path to deployment.
 
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.
 
The challenge isn't just decentralizing intelligence.
 
It's decentralizing intelligence while maintaining performance.
 
That's much harder.
 
The Most Likely Outcome
 
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.
 
Large technology companies will continue providing chips, cloud infrastructure, simulation platforms, and foundational research.
 
At the same time, decentralized AI networks will emerge as alternative coordination layers where intelligence, data, and economic value can be shared more openly.
 
The companies building robots may use NVIDIA hardware.
 
Train on Azure.
 
Run foundation models from OpenAI.
 
But they may also participate in decentralized data networks, decentralized compute markets, and decentralized intelligence protocols.
 
The future of robotics could end up looking less like a monopoly and more like an ecosystem.
 
The Bigger Question
 
The real question isn't whether decentralized AI can eliminate Big Tech.
 
It can't.
 
At least not anytime soon.
 
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.
 
As robots become workers, assistants, delivery drivers, factory operators, and even economic agents, that question becomes increasingly important.
 
Because the battle for the future of robotics is no longer about hardware.
 
It's about who owns the intelligence.
 
And that battle is just getting started.
 
 

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