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šŸ’„NYDFS Releases Draft Regulation on Assessing Operating Costs for Digital Asset OversightšŸ’„
December 03, 2022
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Subject to a 10-day pre-proposal comment period, followed by a 60-day comment period upon publication in the state register, the New York State Department of Financial Services has published a draft regulation outlining the proposed methodologies to assess licensed virtual currency businesses for supervision and examination costs.

If it comes into effect, the proposed regulation will create a provision in the state budget FY23 for DFS to collect supervisory costs from virtual currency businesses, helping them acquire top talent for the virtual currency regulatory team. A proficient regulatory team would eventually ensure that the DFS stays adequately capable of protecting customer interests and the safety and soundness of the industry ecosystem.

Regulating virtual asset companies to ensure that they adhere to the industry-wide best practices is nothing new in the state of New York. After all, the regulatory framework, comprising efforts toward licensing, supervision, and enforcement, has been in place since 2015. It was the year when the state adopted 23NYCCR Part 200, which mandated obtaining licenses before engaging in virtual currency businesses under the authority given to the DFS by the FSL or Financial Services Law.

However, the genesis of New York’s digital asset regulation efforts involves a lot more. Before delving deeper into the current regulation proposed by the DFS, let’s look at how the virtual assets regulation framework kept evolving in the state.

Virtual Currency Regulation in the State of New York: The Genesis

BitLicense is probably the most discussed and debated among the efforts undertaken by the State so far in the realm of virtual currencies and their regulation.

BitLicense

What came as flagship crypto and virtual currency regulation in the state was but a licensing regime at its core. First issued in 2015, BitLicense implied a business license issued by the NYDFS for companies engaged in virtual currency activity.

There is no denying that the licensing regime was received by the industry and its diverse components with a significant amount of anxiety. Industry stakeholders contended that the regulations were discouraging and disincentivizing and required much more compliance than what the standard financial establishments had to adhere to.

Pushbacks that the regulation drew from emerging businesses drove the authorities to make some changes in the framework to make it more accommodative and inclusive. The regulators allowed the new licensees to collaborate with the existing BitLicense holders so that the latter could receive specific guidance to overcome the hurdles in obtaining the license.

However, there was no compulsion for the prevailing players to guide the new license applicant. On top of that, there was no reduction in the fees that a new applicant, an emerging virtual currency business, might have to pay together towards obtaining the licenses, paying the application and legal fees, etc.

While BitLicense remained a bone of contention and a reason for many virtual asset companies to relocate to a new crypto-friendly jurisdiction, more reasons for new businesses to worry continued to pop up. And the latest one among them was the 2-year moratorium imposed on new proof-of-work mining.

2-Year Moratorium on New PoW Mining

As recently as in the third week of November 2022, New York Governor Kathy Hochul signed a bill introducing a two-yearĀ moratorium on new PoW mining. It included new and renewed air permits for fossil fuel power plants used for PoW mining, considered energy-intensive or sometimes an energy-inefficient form of crypto mining.

The moratorium came into effect despite a series of objections raised by the New York Crypto Industry stakeholders. Although the moratorium kept existing operations like Greenidge Generation and other hydroelectricity-powered processes out of its purview, many industry lobbyists and organizations termed it as nothing less than a bad policy.

For instance, the New York State Lead of the crypto-lobbying Blockchain Association termed the moratorium an existential threat while referring to the BitLicense regime as another obstacle. However, the bill proponents cited the negative impact moreĀ PoW miningĀ could have had on the environment and asked for a detailed study on its implications while the ban on new permits for fossil-fuel-powered PoW mining operations would be in effect.

In such a scenario, riddled with the complexities that these regulations and licensing regimes introduced, the New York State virtual currency businesses come face to face with another regulatory scheme, the Virtual Currency Assessment Regulation.

Virtual Currency Assessment Regulation

The New York State Department of Financial Services is undoubtedly ambitious about the proposed regulation. Admittedly, it believes that the ā€œassessment authority will allow the Department to continue building the team which is leading the nation with a suite of regulatory tools.ā€

The regulation applies to entities that obtained licenses under the 23NYCCR Part 200. The billing would occur five times a year, including four quarters and one final assessment billing. In the following segments, we will look at the proposals in greater detail.

The Basis of Billing

As proposed in the bill, there will be four quarterly assessments, each involving nearly 25 percent of the projected annual amount. The projection will indicate the tentative budget to cover the total operating cost as applicable at the time of billing.

The fifth billing – or the final assessment billing – would be a true-up to match the actual operating costs for the entire year. It would be pertinent to mention that the New York State fiscal year starts on April 1st and ends on March 31st.

Any entity that has received its license for a part of the quarter would be assessed for the full quarter, with amounts to be paid within a month from the billing date.

Total Operating Cost

Since this is the amount businesses would have to pay for the year, it is crucial to know what it comprises. The cost would have two components: the supervisory and the regulatory component.

The supervisory component implies the sum of the Transmission Volume Basis Assessment for an individual licensee, where the Transmission Volume Basis means the allocation instrument used to distribute 50% of the Supervisory Hours among licensees.

It is calculated based on the total number of virtual currency transmissions by each licensee in New York for the previous calendar year. The categories that the licensees would fall into could be Small, Medium, or Large, depending on the 5%, 15%, and 30% allocation of supervisory hours.

The regulatory component reflects the cost of license examinations. The hourly rates play a decisive role in determining license examination costs. Hourly rate, as defined in the proposed regulatory bill, would imply the average hourly salary and fringe benefit costs of the examiners and the staff assigned for the supervision of the Licensees.

Additionally, the rate would include a multiplier, which the superintendent would determine. Essentially, the multiplier would reflect a part of the other operating overhead expenses of the department.

It is to note here that Licensee, as proposed in the bill, would mean an individual, partnership, corporation, association, joint stock association, trust, or any other entity that has its license under the provisions of 23 NYCCR Part 200.

Penalizing Actions

Penalties, in the form of late fees and interest, would apply to all licensees. The penalizing authorities would include the FSL, the State Finance Law, and other relevant laws that might be applicable on a case-to-case basis.

These authorities are legally qualified and empowered to follow up on the nonpayment of penalties with appropriate enforcement actions. Such enforcement actions might include the suspension, revocation, expiration, or termination of licenses as deemed fit to the case.

Provisional Exemptions

Persons involved in the virtual currency business as a limited-purpose trust company or banking organization would not be assessed under 23NYCRR Part 200. For such entities, 23NYCRR Part 101 would continue to apply. However, if a person holds both, billing would be done separately for the limited purpose trust charter and the license.

Virtual Currency Assessment Regulation: A Boost or a Roadblock?

As the DFS believes, the effectuation of the proposed bill would help it strengthen the industry in the long run by ensuring a trustworthy, credible, and efficient virtual currency ecosystem.

The department would ensure best practices more rigorously as the costs associated with the department’s oversight of each person’s virtual currency would be properly taken care of. However, as many industry stakeholders believe, these bills might take a toll on the emerging businesses’ bottom lines, resulting in a growth impediment for the industry.

Many have already started seeing the proposal as a continuation of the apparent roadblocks that BitLicense and the 2-year moratorium on PoW mining pose to the industry. To what extent do these assumptions stand valid – only time should tell.

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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.

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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.

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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.

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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
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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
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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:
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  • 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.
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If one server fails, the system continues.
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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.
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The companies building robots may use NVIDIA hardware.
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Train on Azure.
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Run foundation models from OpenAI.
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But they may also participate in decentralized data networks, decentralized compute markets, and decentralized intelligence protocols.
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The future of robotics could end up looking less like a monopoly and more like an ecosystem.
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The Bigger Question
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The real question isn't whether decentralized AI can eliminate Big Tech.
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It can't.
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At least not anytime soon.
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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.
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As robots become workers, assistants, delivery drivers, factory operators, and even economic agents, that question becomes increasingly important.
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Because the battle for the future of robotics is no longer about hardware.
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It's about who owns the intelligence.
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And that battle is just getting started.
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