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.  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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August 14, 2022
The ‘writing is on the wall’ for ‘Chimerica’ on U.S. stock exchanges as $318 billion of Chinese equity flees Wall Street
For months, federal regulators have increased pressure on Beijing and Chinese companies that trade on U.S. stock exchanges to comply with American listing rules.
But on Friday, five of China’s biggest U.S.-listed, state-owned giants, valued at a collective $318 billion, announced they would exit Wall Street instead, marking an acceleration in the U.S.-China financial decoupling.
State insurer China Life Insurance, energy behemoths PetroChina and China Petroleum & Chemical Corporation, alongside Aluminum Corporation of China, and Sinopec Shanghai Petrochemical, all said Friday that they will delist from the New York Stock Exchange (NYSE), as Washington and Beijing continue to jostle over letting American inspectors audit Chinese companies. The fight could lead to hundreds of China-based companies being booted from U.S. stock exchanges.
Just in case, Chinese businesses are preparing to be kicked off of Wall Street. “The state-owned firms are seeing that the writing is on the wall for them,” Liqian Ren, director of modern alpha at investment firm WisdomTree Asset Management, told Fortune, and indicates that a bigger shift might be underway for other public China-based companies as well.
Business decisions
The U.S. and China are at loggerheads over a decades-long dispute over allowing American inspectors to audit U.S.-listed Chinese firms. The U.S.’s audit watchdog wants full access to Chinese companies’ auditors and audit papers, but China has refused, citing national security concerns. The U.S. could delist over 260 Chinese companies worth a combined $1.3 trillion by 2024 if Washington and Beijing can’t reach an agreement.
China’s securities regulator said in a Friday statement that “listings and delistings are… common in capital markets.” It added that the five state firms followed U.S. rules while listed on American stock exchanges, and that their delisting decisions were only “made out of business considerations.”
Other U.S.-listed Chinese firms could follow in the footsteps of the five state-owned enterprises (SOEs). The two remaining Chinese SOEs listed on U.S. stock exchanges—two state-linked airlines—will “definitely be considering” delisting from New York, Ren says. China’s state-run firms all hold information that Beijing deems sensitive or crucial to national security that it doesn’t want American inspectors to access, meaning that it wouldn’t come as a surprise if the remaining state firms choose to delist soon, Brendan Brendan Ahern, chief investment officer at KraneShares, a China-focused investment fund, told Fortune.
Yet this hedge isn’t limited to state firms. Other Chinese firms want to retain their U.S. listings. But they’ll ultimately “review the situation and make a strategic choice,” Ren says. For most big firms, they’ll feel that a U.S. listing is risky and opens them to being caught in the crossfire between Chinese and American regulators, especially in the face of deteriorating Sino-U.S. ties, she says.
And non-state linked companies have been moving to reduce those risks. On July 29, the U.S. Securities and Exchange Commission (SEC) added Chinese tech behemoth Alibaba—which raised $25 billion in 2014 in the U.S.’s biggest-ever IPO—to its delisting watchlist. Alibaba announced that it is changing its Hong Kong listing from a secondary to primary status, which allows it an exit route in case of delisting—and one that lets it tap mainland China investors.
Stifled progress
In recent months, the SEC has continued to add Chinese companies to its now-long list of firms that face expulsion from American stock exchanges. SEC chair Gary Gensler has reiterated that the U.S. will accept nothing less than full compliance from China.
Beijing reportedly wants to strike a deal with Washington that would separate U.S.-listed Chinese firms based on the type of data they hold. China is seeking a compromise to let most non-state owned firms open their books to American inspectors, but restrict reviews of state firms and tech companies that hold sensitive information, Adam Montanaro, investment director of global emerging markets equities at investment firm abrdn, told Fortune earlier this year.
While “China does have incentives to improve their relations with the U.S., [their ties] have been seriously damaged in the last few years. The trust is very low, especially with the recent Taiwan flareup,” Ren says. At the same time, U.S. regulators have been very clear that they want full access and compliance. There’s not going to be a two-tier system of access” that Beijing desires, she says.
Ahern however, argues that the five state firms’ delistings are a positive sign that Washington and Beijing might be closer to reaching a delisting consensus. Once Chinese SOEs are all delisted from Wall Street, the “remaining non-state companies have long-stated that they have nothing to hide” from U.S. inspectors, Ahern says.
Still, the SEC’s delisting watchlist has only grown larger—and the challenges for U.S.-listed Chinese firms more difficult. The SEC has now flagged 159 firms, including Alibaba’s e-commerce rival JD.com, social and blogging giant Weibo, KFC parent Yum China, and biotechnology firm BeiGene, to be expelled from Wall Street if they don’t comply. Washington “clearly won’t give an inch. There is no compromise to be had. The Chinese side [must] do all the conceding,” China-focused research firm Trivium wrote in an April note.
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Tokenization is moving from issuance to utility 🔧
Stellar gives institutions the controls they need to issue assets onchain and the infrastructure to put them to work across a growing financial ecosystem.
Hear more from @DenelleDixon on @DefiantNews👇
#RWAFI
00:01:23
🚨 JUST IN — CONST AT EXPLOIT SUMMIT— 🖕The Cabal
@Const of Bittensor ($TAO) just delivered an absolute mic-drop speech on decentralized intelligence and true freedom! 🔥
Key takeaways from the stage:
1️⃣ Mind Outside of the State: 🌐
"Bitcoin was money outside of the state. Bittensor said, let’s build artificial intelligence that’s not controllable by China and the United States."
2️⃣ Fighting Centralized Control: 🛡️
The goal is to build an independent, sovereign intelligence outside the cabal to safeguard against potential impending totalitarianism.
3️⃣ A Message to Regulators:
"And the fact that we exist is a massive middle finger to anybody trying to regulate AI and slow this down."
4️⃣ Harnessing the Swarm: 🤖
Bittensor embraces hyper-intelligent bot swarms to optimize tech, creating open systems where anyone can contribute and have a say.
5️⃣ Empowering Everyone: 🌍
From a core team to 25 validators, to $dTAO holders, and ultimately—everyone on Earth!
🚀 Rule #1: Don't become the cabal. Decentralize ...
00:01:47
🚨 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.
🔹 The platform says it has processed nearly 38 trillion tokens since launch across 53 deployed applications and more than 700,000 registered users.
🔹 The team reportedly cut unprofitable usage programs, reduced total token volume, and still improved revenue efficiency, with revenue per GPU rising sharply after removing subsidized traffic.
🔹 Chutes is using post-quantum cryptography, trusted execution environments, and Nvidia confidential ...
🚨 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...
👉 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
💠 Users set up personalized agents in < 3 minutes
💠 Equipped w/ crypto wallet and on-chain functions
💠 Capable of completing trades, swaps, and staking
💠 Integrates with Coinbase’s SDK, OpenAI, & Replit
👉 What this means for the future of Crypto:
1. Open Access: Democratized access to advanced trading
2. Automated Txns: Complex trades + streamlined on-chain activity
3. AI Dominance: Est ~80% of crypto 👉txns done by AI agents by 2025
🚨 I personally wouldn't bet against Brian Armstrong and Jesse Pollak.
🛸 UFO disclosure may be more about artificial intelligence than extraterrestrials 🧠
Ashton argues that the UFO disclosure conversation could ultimately be connected to artificial intelligence, advanced technology, and the possibility that humanity is encountering forms of intelligence that do not fit conventional categories.
🔑 Key points
🔹 Disclosure involves intelligence: The central question may not simply be where unidentified objects come from, but what kind of intelligence controls or created them.
🔹 Advanced technology could resemble AI: Autonomous systems, non-human intelligence, and highly advanced machines may be difficult to distinguish from one another.
🔹 Reverse engineering is part of the theory: If recovered or observed technology exists, artificial intelligence could be essential for analyzing systems that are far beyond current human understanding.
🔹 AI may accelerate disclosure: Advanced models can process massive amounts of testimony, sensor data, government documents, ...
🧭 TAO.BOT Basket Explorer is live
With Root Basket Trading now active on Bittensor, validator strategy is becoming much more important.
The new Basket Explorer makes that activity visible in one place.
Users can now:
-
compare basket weights across Root validators
-
see validator exposure to each subnet through a heatmap
-
filter by validator, subnet, and minimum weight
-
track every basket swap on-chain
-
see the TAO value and allocation changes behind each trade
-
monitor aggregate basket NAV, swap activity, and volume
As validators begin actively managing subnet exposure, understanding where they allocate — and how those allocations change over time — becomes another important part of evaluating validator performance.
The goal is to make TAO.BOT the easiest place to analyze that layer of Bittensor.
Explore validator baskets → https://tao.bot/root
☁️ Hippius (SN75) presents decentralized cloud infrastructure on Bittensor ☁️
Hippius is building a decentralized cloud platform that combines encrypted storage, distributed compute, bandwidth, and privacy-focused infrastructure for AI developers, businesses, and everyday users.
🔑 Key points
🔹 Decentralized storage: Files can be distributed across independent providers instead of relying on one centralized cloud company.
🔹 Encrypted file management: Data can be protected before it is uploaded, giving users greater control over access and privacy.
🔹 Cloud-compatible tools: Hippius is designed to support familiar storage workflows and S3-compatible integrations.
🔹 Compute is part of the expansion: The platform is moving beyond storage into GPU access, confidential computing, and AI workloads.
🔹 Bandwidth can be distributed: The network can help move data between storage providers, cloud platforms, and AI systems.
🔹 AI infrastructure is a major use case: Models, datasets, checkpoints, ...
Revolut Leak Shows the Cost of Constant ID Collection
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 notes, Massachusetts 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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