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Bitcoin ‘Halving’ Will Deal a $10 Billion Blow to Crypto Miners
April 15, 2024
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For enthusiasts of Bitcoin, a once-every-four-years software update called the “halving” has long been held as one of the keys to propping up its value.

This time around, it’s also set to trigger multibillion-dollar declines in revenue for the very companies that ensure the digital currency’s smooth functioning, right on the heels of a surge in their biggest costs.

Around April 20, the halving will cut the amount of Bitcoin that “miners” can earn each day for validating transactions to 450 from 900 now. Based on Bitcoin’s current price, it could spell revenue losses of around $10 billion a year for the industry as a whole. Marathon Digital Holdings Inc.CleanSpark Inc. and other miners, which compete for a fixed Bitcoin reward by solving mathematical puzzles using superfast computers, have invested in new equipment and sought to buy smaller rivals in an attempt to cushion the drop-off in revenue.

“This is the final push for miners to squeeze out as much revenue as they can before their production takes a big hit,” said Matthew Kimmell, a digital asset analyst at CoinShares. “With revenues across the board decreasing overnight, the strategic response of each miner, and how they adapt, could well determine who comes out ahead and who gets left behind.”

On the horizon is a preordained event that will change the business of Bitcoin forever. It’s called The Halving, and once it occurs the potential balance sheet of every Bitcoin miner is cut in half. Companies are doing everything they can to prepare for it, including moving away from crypto and in some cases into an even newer field: artificial intelligence.

Granted, Bitcoin has reached new highs after previous halvings, helping to mitigate the periodic drop in mining rewards and the increase in the cost of doing business. The event this month is coming after the digital currency has more than quadrupled since November 2022. Yet the margin of success for the industry keeps getting finer. Miners will need to continually spend more money in a never-ending, technological arms race for smaller rewards. And while the energy-intensive validation process has always made mining expensive, companies now face even more competition for power from the burgeoning and deep-pocketed artificial intelligence industry.

The soaring price of Bitcoin has helped offset those power costs and fueled growth in crypto mining. Since the first specialized machines came into play in 2013, the aggregate market cap of 14 U.S.-listed miners has grown to about $20 billion, according to an April 1 report by JPMorgan Chase & Co.

While US-listed miners are the face of the industry, they account for just about 20% of the sector’s computing power, according to crypto researcher TheMinerMag. Private miners make up the rest and could be more vulnerable after the halving as they typically must tap debt financing or venture capital to cover their needs, whereas public companies can raise funds via share sales.

As the hoopla has revved up around the event, some traders are betting that mining stocks will fall. Total short interest, the dollar value of the shares borrowed and sold by bearish traders, stood at about $2 billion as of April 11, according to an estimate from S3 Partners LLC. That short interest accounted for almost 15% of the group’s outstanding shares — three times more than the US average of 4.75%, said Ihor Dusaniwsky, managing director of predictive analytics at S3.

Bearish Bets

The total short interest in 15 crypto-mining stocks is nearly $2 billion

                                             Source: S3 Partners LLC

                                    Note: As of the close April 8, 2024

The update, the fourth since 2012, was preprogrammed by the anonymous Bitcoin creator Satoshi Nakamoto to maintain the hard cap of 21 million tokens to keep it from becoming inflationary as a currency.

The situation differs from four years ago when Bitcoin was trading under $9,000 and most of the mining activity took place in China. Since then, much of that activity has shifted to the US, driving competition for electricity.

“Power in the US is extraordinarily constrained,” said Adam Sullivan, chief executive officer at Austin, Texas-based Core Scientific Inc., one of the largest public Bitcoin mining companies. “Right now, miners are competing against some of the largest tech companies in the world, who are trying to find space for data centers, which are high energy consumers too.”

The nascent AI industry is drawing in massive amounts of capital, which is making it harder for miners to secure favorable electricity rates with utility companies. Amazon.com Inc. is set to spend almost $150 billion on data centers, while Blackstone is building a $25 billion empire of centers. Google Inc. and Microsoft Corp. are also making hefty investments.

Power Grab

“The artificial intelligence crowd is willing to pay three or four times what Bitcoin miners were paying last year” for electricity, said David Foley, co-managing partner at Bitcoin Opportunity Fund, which has made investments in both public and private miners. That is happening across the globe, he said.

The tech giants also have an edge in acquiring power from utilities, given their consistent revenue stream, whereas crypto mining revenue fluctuates with the rise and fall in Bitcoin prices. Utilities consider tech companies as more reliable purchasers given their strong balance sheets, said Taras Kulyk, CEO at crypto-mining services provider SunnyDigital.

With that competition in place, low-cost power contracts could be tougher to renew when existing agreements expire. Large-scale Bitcoin miners tend to lock in energy prices, typically for a few years, said Greg Beard, CEO of public Bitcoin miner Stronghold Digital Mining Inc.

Computer Power

Miners compete for a fixed amount of reward, with winner-take-all for the first to successfully process a block of transactions on the Bitcoin blockchain. That reward will drop to 3.125 Bitcoin at the halving from 6.25 now.

The more computing power a miner has, the more likely it is to earn the reward. But it’s getting harder. Mining difficulty, a measure of computing power to mine Bitcoin, has swelled almost sixfold since the 2020 halving, according to a biweekly update from crypto-mining website btc.com. That is a result of an increasing number of miners and a reward that remains fixed.

Companies have been updating their technology with more efficient machines to generate extra computing power, and public Bitcoin miners have raised billions of dollars to fund the purchases by offering new shares.

That option isn’t available to private mining businesses, which account for about 80% of the industry’s computing power in the US. During the previous bull run in 2021, those companies mostly relied on issuing debt to help cover their costs. Both public and private miners were estimated to have borrowed as much as $4 billion in loans backed by mining equipment around that time. But deals have been harder to come by as a slew of lenders went bankrupt during the crypto market crash in 2022.

“It is tough out there,” said Young Cho, CEO at Blockhouse Digital, an asset management firm that specializes in collateralized lending and yield-generating strategies in the crypto markets. “Miners have been looking for lenders for several months and they have not been able to find any.”

Besides debt financing, some private miners are raising money through venture capital funding rounds, Bitcoin Opportunity Fund’s Foley said.

Those with negative cash flows that don’t have access to borrowing are faced with the decision to finance operations through private equity or the cash preemptively stowed on their balance sheet, said Kimmell at CoinShares.

“Alternatively, if they have low confidence in future mining revenues, they may wind up exiting the market,” he said.

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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.

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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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