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Why the SEC Crackdown is Good for Staking
March 18, 2023
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Key Takeaways

  • Kraken shutting down its Staking Program and being charged by the SEC for offering and selling unregistered staking-as-a-service securities could set a precedent for other crypto platforms operating in the same manner
  • SEC’s charges against Kraken weren’t a strike against staking but rather against business practices of platforms offering modified staking products, which are considered securities
  • Expanding Qualified Custodial requirements to include crypto drastically reduces the number of crypto platforms that can legally operate, further centralizing power amongst select crypto platforms that become Qualified Custodians
  • Custodial requirements add additional layers of safety for crypto investors as it requires custodial platforms to segregate funds, provide yearly disclosures and public audits, and ensure customer funds are accessible in case of bankruptcy
  • Custodial requirements are likely to reduce the number of custodial crypto platforms operating and adversely push retail and institutions on-chain via non-custodial solutions or running validators, ultimately improving decentralization

Introduction

The SEC has recently implemented a multitude of initiatives regarding staking and stablecoins. It claims its actions shield consumers while enforcing regulatory requirements. Regulatory bodies, including the SEC, hope their new initiatives prevent future crypto frauds. However, many in the crypto sphere worry that regulatory intervention will cause harmful adverse effects. Namely, regulatory red tape will centralize power amongst governments and financial institutions – directly contradicting the decentralized nature of blockchain technology.

SEC’s view and planned actions on staking will have a paramount impact on the industry outlook. Fortunately, Gary Gensler has recognized staking as a legitimate practice to achieve blockchain consensus. However, there are dissenting opinions on crypto platforms’ handling of staking programs, not staking itself. Although Kraken was the first to be charged, other platforms with similar products and operations are likely at risk of being charged.

ETH staking flows initially reacted negatively to SEC’s charges against Kraken but quickly recovered and surged to a weekly high when the Qualified Custodian rule was proposed to include crypto.

Let’s dig into what happened and what it means for staking. In our view, the recent developments are positive for the staking industry.

Kraken Shuts Down its Staking Program

Why did the SEC order Kraken’s Staking Program to be shut down?

The SEC deemed Kraken’s Staking Program as an illegal offering of unregistered securities due to Kraken’s ability to give customers an advantage and higher returns than independent staking.

Several factors about Kraken’s Staking Program led to SEC’s conclusions, including

  • Staking on Kraken was passive for participants; no action required
  • Kraken set staking yields, determined by opaque criteria. Instead, in legitimate staking, software determines yields.
  • A partial portion of customers’ crypto was held as reserve, not staked, to ensure withdrawals.
  • Kraken sent regular investment payouts, whereas legitimate staking does not follow a set schedule.
  • No staking minimums

Can Kraken challenge SEC’s conclusions?

Kraken paid a $30M fine to settle SEC charges, ceasing its Staking Program rather than choosing to fight it in court.

Was the SEC after staking or after Kraken’s business practices?

The SEC complaint did not allege that staking is an offer or sale of securities. Instead, it claimed that Kraken’s Staking Program practices altered the nature of staking and touted features such as easy-to-use platforms, investment returns and payouts.

Staking directly on-chain is unaffected by the SEC’s charges, yet this event could set a precedent for potential action against similarly configured custodial crypto platforms. On-chain staking vs custodial staking is an important distinction that the media seems to skip over.

Staking isn’t a security because:

  • Token owners remain in full ownership of their assets when staking, and can unstake them following the underlying protocol.
  • Stakers are not connected by a common enterprise but by decentralized blockchain networks, hence failing to meet the “common enterprise” element of the Howey test.
  • It’s argued staking services don’t meet the “reasonable expectation of profits” element of the Howey test, which examines whether an asset is purchased for investment returns or personal use. Staking rewards are payments for validating transactions on the blockchain network, not investment returns.
  • Staking services don’t involve rewards based on the “efforts of others” under the Howey test. Service providers are not entrepreneurs, managers, or key contributors to determining customer rewards or the number of rewards received. Instead, the blockchain protocol governs which validator nodes receive rewards and how many, regardless of service providers.

What does this mean for staking providers in the future?

Regulatory scrutiny on centralized staking operations may vary based on the degree of centralization. Recent events have likely increased such scrutiny, though decentralized staking remains unaffected and may see higher demand for a non-custodial approach.

What does this mean for decentralization in the future?

The staking industry’s recent developments reinforce the resilience of decentralized operations, a positive sign for decentralization and the need to reach a decentralized future. On the other hand, Custodial crypto platforms may experience more centralization among less players as the SEC continues its crackdown and suggests extending the Qualified Custodian rule to digital assets.

Expanding the Qualified Custodian Requirements to Include Digital Assets

What are the new proposed rules for Qualified Custodian requirements?

Gary Gensler proposes to enhance the role of Qualified Custodians. The proposal affects registered investment advisers who custody assets (now including digital assets) on behalf of their investors. Ultimately, custodial requirements aim to remove the ability of an investment adviser to pay the proceeds that new investors invested to old investors (aka Ponzi schemes) and guarantee customers access to funds during bankruptcy proceedings. The rule requires advisers and Qualified Custodians to segregate all client assets, including crypto, and forbid advisers from relying on non-Qualified Custodial crypto platforms. By expanding the custody rule to crypto assets, investors working with advisers would receive the same safeguards as any other asset. According to Gary Gensler, most crypto platforms today aren’t Qualified Custodians and would need to overhaul operations. In addition, the new proposals require yearly disclosures, audits, and discretionary trading on investors’ behalf and apply to foreign financial institutions.

Why are crypto platforms likely to face scrutiny in the short term if the proposed custodial requirements are passed?

Today, some crypto trading and lending platforms assert custody over investors’ crypto assets, but that does not necessarily imply they are Qualified Custodians. Instead of appropriately segregating investors’ assets, such platforms have intermingled funds across investors. As a result, if these platforms go bankrupt, as has occurred, investors’ assets frequently become the property of the failed company, leaving investors in a queue at the bankruptcy court. Few crypto platforms can claim they are eligible to be Qualified Custodians.

How would the expanded custodial requirements affect the competitive landscape of crypto platforms and decentralization?

The SEC’s proposed rule would require SEC-registered investment advisers to use only “Qualified Custodians,” which may pose a challenge for advisers utilizing crypto platforms that don’t meet Qualified Custodian operating and disclosure standards. The proposed rule may result in the concentration of assets with a small number of registered custodians in the US, creating a new centralization force in the industry. SEC Commissioner Mark Uyeda also pointed out that trading crypto assets on platforms that are not qualified custodians would violate the proposed rule.

The proposed rules have several implications for the competitive landscape of crypto. First, only a handful of custodians would pass the Qualified Custodian requirements. Second, any new participants would need to seek approval from the SEC for Qualified Custodian status, which is no easy feat. Thirdly, this gives the SEC significant authority and oversight amongst crypto platforms and imposes a centralized governing body. Although not fully in line with the decentralization ethos of blockchains, such a proposal does assure users’ digital assets are safe. If these proposals were in place previously, FTX and Celsius, for example, would not have existed. As an unintended consequence of the new proposal, users will be pushed towards non-custodial, on-chain solutions, ultimately serving crypto for the better and improving decentralization. In addition, over a more extended time period, we believe institutions will opt to run validators to maximize staking rewards and avoid reliance on custodial platforms. Reducing the number of platforms that can legally provide staking through custody-based platforms will further accelerate institutional investors to run validators.

Conclusions

Ultimately, we believe the Kraken crackdown and Qualified Custodian expansion is good for crypto. It sets a standard for custodial platforms and spurs more interest in non-custodial staking. The expanded Custodian definition creates safety nets as users know their funds won’t be misused, stolen, or frozen in case of bankruptcy. Although this limits the number of platforms offering services in the short term, more clarity for participants will pave the way to legitimize digital assets in the eyes of the SEC.

The crypto space is a complex network of stakeholders; every step shifts the teeter-totter of power, favoring different stakeholders at different times. Ultimately, these steps are crucial for crypto’s widespread adoption and transition towards balance and increasing decentralization in the long term.

This is not financial or legal advice.

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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.

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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.

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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.

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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
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  • 5 - New Jersey - $295,110
  • 6 - New York - $291,533
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  • 8 - Washington - $281,798
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  • 12 - New Hampshire - $267,904
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  • 15 - Maryland - $257,837
  • 16 - Maine - $250,931
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  • 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
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  • 31 - Nebraska - $223,059
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  • 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

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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.

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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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