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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December 23, 2024
6 Best Altcoins To Watch 👀 – Theta Network, IOTA, Tezos, Uniswap 🚀 📈
Based on projections, 2025 could mark an extremely bullish era for AI solutions and Bitcoin. An analyst who shared data on the ARC-AGI semi-private v1 score and the BlackRock iShares ETF AUM illustrated how the assets have performed historically while also projecting what will come in 2025.
According to the shared data, 2024 is the breakout year for ARC-AGI, positioning the metric for a vertical surge in the coming months. In light of the positive crypto market wave, this article outlined other affordable tokens, particularly the best altcoins to watch today.
👉 6 Best Altcoins To Watch Today
Theta Token (THETA) is currently valued at $2.23, reflecting a 19.81% rise over the past 24 hours. Lido DAO’s token (LDO) has also performed well, reaching $1.75 after a 13.24% gain within the same period. Following the community’s approval of the IOTA Rebased protocol upgrade, IOTA is expected to undergo major technological and token economy advancements. Meanwhile, Tezos (XTZ) is trading at $1.32, recording a 15.02% increase over the last day.
Wall Street Pepe (WEPE), a recently launched crypto initiative, has secured $32 million during its ongoing presale. Uniswap (UNI) is now priced at $13.46, climbing 13.76% in the past 24 hours. In contrast, Bitcoin has dropped to $96,000 amid heightened market volatility affecting cryptocurrency assets.
THETA is trading well above its 200-day simple moving average at $1.71508, suggesting strong bullish momentum. The token has shown positive performance since its initial sale price, with 63% of the days in the last month being green, indicating consistent growth.
Liquidity is high, evidenced by a market cap-to-volume ratio of 4.16%, which is favorable for traders. However, potential investors should consider the broader market conditions and their risk tolerance before making investment decisions.
2. Lido DAO (LDO)
Over the past month, Lido Finance’s Community Staking Module (CSM) has significantly influenced Ethereum staking by introducing a more inclusive and decentralized approach. The CSM, operational on Ethereum’s mainnet, has been pivotal in lowering the entry barriers for staking, allowing participation with just 1.3 ETH. This development is part of Lido’s broader strategy to enhance Ethereum’s staking ecosystem through its modular Staking Router. It supports new and seasoned stakers by offering features like smooth rewards and cost-efficient staking setups.
The introduction of CSM has democratized access to Ethereum staking. It supports the network’s decentralization efforts by enabling solo stakers to participate more easily. This move is crucial for maintaining the integrity and security of the Ethereum network, as it encourages a wider distribution of node operators.
Lido DAO’s token (LDO) has also seen a positive market response, with its price currently at $1.75 after a 13.24% increase over the last day. The token’s market cap is robust at $1.56 billion, and it’s trading above its 200-day simple moving average, indicating strong market confidence. The high liquidity, as evidenced by a volume of $375.47 million over 24 hours, suggests active trading and investor interest.
3. IOTA (IOTA)
After the community’s approval of the IOTA Rebased protocol upgrade, IOTA is set to experience significant improvements in its technology and token economics. The price of IOTA is currently at $0.3039, with a market capitalization of $1.08 billion. Over the last year, the token has seen an increase of 9%, trading above its 200-day simple moving average, which suggests a bullish trend. However, the neutral price prediction sentiment and ‘Greed’ level on the Fear & Greed Index indicate a cautious optimism among investors.
The Rebased upgrade introduces a Move-based object ledger to enhance transaction speed and network capacity. This is essential for real-world applications that need high throughput and low latency. With these improvements, IOTA aims to compete more effectively in the blockchain industry.
The community overwhelmingly supported the upgrade, with 98.37% in favor. This strong backing suggests a positive outlook for future developments and the adoption of IOTA. For investors, the upgrades could mean increased value and utility of IOTA tokens. For users, particularly those in IoT sectors, the enhanced scalability and security could make IOTA a more appealing platform for application deployment.
4. Tezos (XTZ)
Tezos (XTZ) is trading at $1.32, marking a 15.02% increase in the past 24 hours. Over the past year, XTZ has gained 35%, reflecting steady growth. The token is trading 39.72% above its 200-day simple moving average (SMA) of $0.947823, signaling a strong uptrend. In the last 30 days, Tezos has recorded 16 green days, making up 53% of the period, which supports a neutral price prediction sentiment.
The Fear & Greed Index currently stands at 73 (Greed), indicating optimistic market sentiment. Tezos has also seen an uptick in community activity. For example, the Share4Tez initiative on Objkt.com promotes NFT referrals. At the same time, several community members have celebrated achievements such as sold-out collections and seasonal showcases.
Tezos continues to build momentum, driven by strong technical performance, market sentiment, and active community engagement. Given market conditions, investors should monitor its ongoing developments and the sustainability of the recent price increase.
5. Wall Street Pepe ($WEPE)
Wall Street Pepe (WEPE), a new cryptocurrency project, has raised $32 million in its ongoing presale. The project aims to provide retail investors with market insights, staking opportunities, and community-driven trading rewards. Since launching on December 3, WEPE tokens have been available at 0.000365 per token. Buyers can purchase the tokens directly from the project’s website using cryptocurrency or card payments.
The project has allocated 20% of its 200 billion token supply to early presale participants. It also offers early staking opportunities. Investors can stake their tokens before the official launch, earning rewards distributed over three years.
According to the project, 3,044 WEPE tokens will be issued per Ethereum block. However, the presale has no set hard cap or end date. The roadmap indicates an exchange listing is planned shortly after the presale ends. Tokens will also become claimable at that point.
Coinsult has audited the smart contract and found no major vulnerabilities. The project continues to share updates through platforms like X (formerly Twitter) and Telegram, drawing attention from the wider crypto community. Wall Street Pepe’s combination of entertainment and utility could appeal to retail investors seeking engagement and practical tools.
6. Uniswap (UNI)
Uniswap (UNI) trades at $13.46, reflecting a 13.76% gain in the last 24 hours. Over the past year, UNI’s price has increased by 115%, outperforming 72% of the top 100 cryptocurrencies. The token trades 41.53% above its 200-day simple moving average (SMA) of $9.56, indicating a bullish trend. Notably, 19 of the last 30 days (63%) have been marked by positive price movements.
Uniswap has high liquidity relative to its market cap, making it a stable option for traders. Recent integration on the Saga Chainlet introduces gasless trading, enhancing the DeFi experience and contributing to Uniswap’s adoption and usability. The Fear & Greed Index reads 73 (Greed), signaling a favorable market sentiment.
Looking ahead, Uniswap is predicted to close 2024 within the $14.23–$17.44 range, with an average price of $15.97. This would represent a 19.36% price increase from current levels, offering a potential return on investment (ROI) of 30.34%. By 2025, UNI’s price is forecasted to trade between $15.55 and $85.90, with an average of $50.53.
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Bittensor $TAO as a frontrunner 🎯
Speaking with @jaltucher on The TAO Pod six months ago, he explained why he sees Bittensor $TAO as a frontrunner for that value capture.
Still worth hearing today.👇
00:03:32
00:01:02
🚨 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.
🌐 Bittensor is becoming a network state for intelligence 🌐
Bittensor is evolving beyond a token network into a global economy where miners, validators, researchers, founders, and subnet communities coordinate to produce AI, compute, data, storage, security, and other digital resources.
🔑 Key points
🔹 A fictional future illustrates the model: In the essay’s 2028 scenario, Mateo earns TAO by competing in AI-optimization subnets from Argentina while collaborating with researchers across the world.
🔹 Work is open by default: Contributors submit models, code, research, and improvements directly into an open network rather than keeping their work behind corporate or government walls.
🔹 Subnets function as factories: Each subnet produces a specialized service or commodity, including compute, trained models, inference, storage, cybersecurity, robotics, and scientific data.
🔹 Miners form a global labor market: Independent operators and teams compete to provide the best outputs at the lowest effective ...
Still Think The Government Has Your Best Interests In Mind? 🤔
⚡ John Hutchison: Antigravity, Crystal Energy & The Suppressed Experiments 🌀
In this presentation, Hutchison details his pioneering experiments with zero-point energy, high-frequency electromagnetic fields, self-generating crystalline power cells, and the physical manifestations of the Hutchison Effect.
🔑 Key Highlights & Breakdown
⚡ The Interdimensional Keyway [01:22] — Hutchison explains how combining conventional electrostatics, high-frequency RF fields, and Tesla wave generators creates a unique spatial resonance. This acts as a "keyway" into quantum zero-point energy fields and gravitational wave distortions.
🛸 Translational Levitation & Acoustic Resonance [03:51] — By subjecting ferroelectric barium titanate cylinders to self-resonance across multiple frequencies, heavy items (including a 7-lb cylinder) become buoyant and glide across surfaces without direct mechanical thrust [06:02].
💎 Crystalline Zero-Point Power Cells [11:19] — By heating, compressing, and ...
🔥 Manual burns are becoming a real economic force across Bittensor 🔥
Bittensor subnet owners are increasingly using manual token burns to reduce alpha supply, strengthen token economics, and connect real revenue or treasury activity to subnet markets.
🔑 Key points
🔹 Manual burns remove alpha from circulation: Subnet teams can purchase and permanently destroy their own tokens.
🔹 Revenue can fund the process: Some subnets use commercial income, platform fees, or treasury resources to support buybacks and burns.
🔹 Supply reduction creates scarcity: Fewer circulating tokens can increase the relative value of remaining alpha if demand remains stable or grows.
🔹 Burns provide visible economic signals: A public burn can show that a subnet is actively managing its token economy rather than relying only on emissions.
🔹 Buybacks and burns are different: A buyback acquires tokens, while a burn permanently removes them from circulation.
🔹 TAO can flow into subnet economies: When a subnet uses TAO ...
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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