Ripple, in collaboration with ProprHome, plans to create a revolutionary path in Portugalās real estate market.Ā
ProprHome creates āCustomer Education-ProprHomeā in a bid to familiarize users with the platform.
Ripple, in partnership with ProprHome, set out to create a revolutionary way to buy, sell and rent real estate in Portugal. The new method will utilize the XRP ledger, an open-source layer 1 blockchain using an NFT utility. Also, it will allow potential buyers to carry out faster, more reliable, and more energy-efficient transactions.
Interestingly, the three entities: Ripple, ProprHome, and XRP Ledger, share similar characteristics and purposes. These platforms are fast, efficient, and transparent. In fact, the primary goal of the partnership is to mitigate the rigorous process of buying, selling, or renting homes in Portugal.Ā
Ripple and ProprHome partner on Portugal real estate revolution
Ripple announced the partnership between the two firms, while ProprHome explained the significant changes in its mode of operation. Prior to the partnership, ProprHome, a blockchain-enabled real estate marketplace, announced its plan to change how people trade and rent homes in Portugal.
Every NFT used on the platform will be minted on the XRP Ledger, a fast and energy-efficient blockchain for asset tokenization. In addition, the XRPās speed and reliability will help facilitate interactions between real estate clients and their agents. Nevertheless, clients will be able to control the offer and acceptance procedure for every transaction.Ā
The CEO of ProprHome, John McCoy, whileĀ commentingĀ on the companyās recent partnership with Ripple, said:
ProprHome and our partner Ripple share the same vision of the tokenization of assets with functional utility. We see the potential of an online real estate market that leverages blockchain technology to improve real estate interactions dramatically. We have trusted in the reliability of XRP Ledger for over ten years to serve as our preferred blockchain for its tokenization and settlement capabilities.
More on the Ripple-ProprHome collaboration
The highly competitive real estate market in Portugal uses customer experience as a deciding factor. ProprHome sets out to provide a well-trusted platform where clients can access suitable professionals. The partnership between ProprHome and Ripple will offer different types of tokens, beginning with utility tokens for digital property certificates (DOC). Only customers who plan to buy or rent a property using the ProprHome platform can use the DOC token. DOC gives customers the right to use a particular property, eliminating the onboarding verification and approval process.Ā
ProprHome plans to have its own native token called Propr (PRP). It is a reputation currency that agents, developers, and owners can earn and exchange for additional exposure. PRP tokens will encourage a positive real estate experience by rewarding users for good practices. ProprHome leverages the XRP ledger to provide transparent and immutable data to all real estate participants
Furthermore, ProprHome created the āCustomer Education-ProprHomeā project to educate and enable customers to make better market decisions. It has also prepared to inform users of the basic blockchain terminologies involved in the platform. ProprHome plans to provide users with an NFT minting guide.
š”ļø Perturb (SN26) plans a decentralized marketplace for AI security testing š”ļø
š”ļø Perturb (SN26) plans a decentralized marketplace for AI security testing š”ļø
Perturbās Whitepaper 3.0 outlines a Bittensor subnet that rewards vulnerability discovery, adversarial testing, model hardening, and commercial AI-robustness services.
š Key points
š¹ Scanning Track receives 80% of emissions: Miners create subtle image modifications that cause AI models to produce incorrect predictions.
š¹ Training Track receives 20%: Miners improve models so they can resist adversarial attacks.
š¹ New tasks arrive every 120 seconds: The network selects images from ImageNet-1k and distributes fresh testing challenges.
š¹ Validators check attack quality: Submissions are evaluated for prediction changes, image quality, perturbation limits, and authenticity.
š¹ Daily evaluations test trained models: Models are tested against clean images and attacks generated during the previous day.
š¹ Two commercial products are planned: Perturb is building an adversarial training dataset and model-robustness ...
š±āļøDid you know that when you meet people, there is a frequency balance between the two electromagnetic fields?
If you vibrate very high, and the person you meet vibrates very low, there is a frequency balance
(as you can see in the video)
The frequency that is very high will descend, and the frequency that is very low will rise to counter and balance the frequency.
That said, people steal your energy...
That's why you must be very careful with the people around you, because these fields carry their emotions, their thoughts, their traumas, their thoughts, and these fields transmit all this energy to you.. ( you can feel it )
These fields are the manifestation of their inner state.
People don't just enter your space,
they enter your fieldš«
Their energy, their emotions and their inner state, influence you more than most people realize..!
šØ Elon Musk Drops a Bombshell on the Future of Wealth š„š
Standing alongside Donald Trump inside the White House, Elon Musk delivered an unprecedented vision for the future of work and finance, declaring:
"You won't need to work for any company from now on... I'll make every person on planet Earth enjoy a fantastic income like celebrities!" šµāØ
Rather than advocating for traditional Universal Basic Income (UBI)āwhich often aims merely for survivalāMusk is effectively signaling a radical shift toward post-scarcity capitalism powered by autonomous labor and exponential AI abundance. š¤š
Instead of governments cutting small safety-net checks, this vision redefines economic participation entirely: as automation and AI scale productivity beyond human limits, wealth creation decouples from standard 9-to-5 employment. šš®
The central question shifting across global finance is no longer if labor will be automated, but how this next evolution of capitalism will distribute high-tier abundance to everyone on the planet. šš
šØ 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 šØ
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.
š Key points
š¹ 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.
š¹ The platform says it has processed nearly 38 trillion tokens since launch across 53 deployed applications and more than 700,000 registered users.
š¹ 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.
š¹ Chutes is using post-quantum cryptography, trusted execution environments, and Nvidia confidential ...
šØ 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 šØ
šØ 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 šØ
šØ JPMorgan’s criticism of the CLARITY Act is fueling a fresh power struggle over who gets to write America’s crypto rules šØ
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.
š Key points
š¹ 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.
š¹ 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.
š¹ 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...
š Coinbase just launched an AI agent for Crypto Trading
Custom AI assistants that print money in your sleep? š
The future of Crypto x AI is about to go crazy.
š Hereās what you need to know:
š 'Based Agent' enables creation of custom AI agents
š Users set up personalized agents in < 3 minutes
š Equipped w/ crypto wallet and on-chain functions
š Capable of completing trades, swaps, and staking
š Integrates with Coinbaseās SDK, OpenAI, & Replit
š 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 štxns done by AI agents by 2025
šØ I personally wouldn't bet against Brian Armstrong and Jesse Pollak.
š Coinbase just launched an AI agent for Crypto Trading
š Coinbase just launched an AI agent for Crypto Trading
š® Remote viewers reveal a sobering possible future for money š®
The video explores remote-viewing impressions about the future of money, financial systems, purchasing power, and the possibility that major changes may arrive before the public recognizes what is happening.
š Key points
š¹ Monetary systems may shift quickly: The discussion considers how currency, banking, payments, and financial access could change during periods of economic stress.
š¹ Not everyone may see the transition coming: Major financial changes often develop gradually before becoming obvious to the wider public.
š¹ Digital money is expanding: Central-bank digital currencies, stablecoins, mobile payments, tokenized assets, and blockchain settlement are reshaping how value moves.
š¹ Purchasing power remains a concern: Inflation, debt, currency expansion, and rising living costs can reduce the real value of savings.
š¹ Physical and digital assets are compared: The video explores whether people may increasingly seek protection...
š¢ļø Global diesel shortage could last into 2027 as inventories drain š¢ļø
Global diesel supplies are tightening as wars in Iran and Ukraine disrupt production and exports, while storage levels fall to historically low levels.
š Key points
š¹ U.S. inventories hit a record seasonal low: Diesel stocks fell to 107.9 million barrels by September 11, the lowest for that time of year since records began in 1982.
š¹ Storage tanks are becoming available: North American and Caribbean diesel storage capacity available for lease rose to approximately 13 million barrels because traders have less fuel to store.
š¹ The shortage may last into 2027: Industry participants expect supplies to remain tight through winter and potentially into the first quarter of next year.
š¹ U.S. diesel prices topped $6 per gallon: Higher fuel costs are affecting farmers, truckers, waste-management companies, manufacturers, and consumers.
š¹ Europe is also under pressure: Diesel stocks in the Amsterdam-Rotterdam-Antwerp hub were ...
š Beam (SN105) expands AI-agent data transfers to Box š
Beam has added Box support, allowing AI agents to move files between Box and other cloud-storage systems without requiring businesses to build custom integrations for every platform.
š Key points
š¹ Box is now supported: AI agents can upload files to Box and retrieve them through Beam.
š¹ Cross-cloud movement expands: Beam already supports S3-compatible infrastructure and can now connect with Boxās enterprise content-management platform.
š¹ Agents can manage files: Workflows may include retrieving documents, transferring files, organizing information, and moving data between services.
š¹ Enterprise storage is the target: Box is widely used by businesses for file storage, collaboration, document management, and secure sharing.
š¹ Beam acts as the data-movement layer: SN105 coordinates transfers across cloud storage platforms and other endpoints.
š¹ Custom integration work can be reduced: Businesses may not need to build separate ...
Revolut Leak Shows the Cost of Constant ID Collection
Revolutās 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 āunauthorized third partyā reportedly includes names, dates of birth, occupations, addresses, phone numbers, account numbers, transaction histories (including Bitcoin), and even copies of government-issued IDs and onboarding verification selfies.
Revolut claims that derived biometric face data was not.
The company said that the data was handed over in response to an email that came from a real government agencyās 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 messageās origin and integrity, but do not verify the legitimacy of the legal request itself.
Revolut said that it complied with the request āunder the reasonable belief that it was an authentic government agency requestā ā 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 ālimitedā number of its customers were affected by the data leak, and that the companyās 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 customersā identities, and sometimes even financial transactions, for a long time, and this data is then available to be disclosed to third parties ā 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. Revolutās 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 ā for legal reasons.
This means that even if you close your account, your identity documents donāt disappear.
And while the incident with Revolut happened in the financial sector, itās 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 ā 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.
Itās 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 didnāt 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.
This Is The Income A Family Needs To Live Comfortably In Every US State
Hereās the short version of what it takes for a family of four to live comfortably in 2026 by state:
In Massachusetts, youād 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. Thatās a full $142,000 less than what youād need in Massachusetts.
Soā¦ how much does a family of four need in your state?
This map shows the pre-tax income a household with two working adults and two kids needs to live comfortably in every U.S. state.
The numbers come fromĀ SmartAssetĀ (as of February 2026). Theyāre based on the familiar 50/30/20 budget: 50% for necessities, 30% for discretionary spending, and 20% for savings or other goals. These arenāt bare-minimum survival numbersātheyāre what it takes to live pretty well while still putting money aside.
And asĀ Visual CapitalistĀ notes,Ā Massachusetts sits at the very top of that list.Ā Massachusetts tops the ranking, with a family of four needing $329,555 per year to meet the 50/30/20 benchmark.
Hawaii follows at $313,165, while California ranks third at $302,682.
Rank State Income needed for family of four (2026)
1 - Massachusetts - $329,555
2 - Hawaii - $313,165
3 - California - $302,682
4 - Connecticut - $298,189
5 - New Jersey - $295,110
6 - New York - $291,533
7 - Colorado - $283,213
8 - Washington - $281,798
9 - Oregon - $280,966
10 - Vermont - $280,384
11 - Alaska - $272,064
12 - New Hampshire - $267,904
13 - Rhode Island - $264,659
14 - Minnesota - $263,078
15 - Maryland - $257,837
16 - Maine - $250,931
17 - Montana - $249,434
18 - Pennsylvania - $247,936
19 - Illinois - $244,109
20 - Virginia - $242,944
21 - Nevada - $242,278
22 - Indiana - $241,696
23 - Wisconsin - $238,451
24 - Arizona - $236,870
25 - Utah - $235,789
26 - Delaware - $228,134
27 - Ohio - $226,221
28 - Idaho - $226,054
29 - Florida - $223,392
30 - New Mexico - $223,142
31 - Nebraska - $223,059
32 - Missouri - $217,734
33 - Georgia - $214,573
34 - Michigan - $214,323
35 - South Carolina - $212,909
36 - North Carolina - $212,410
37 - Wyoming - $212,410
38 - Oklahoma - $211,910
39 - North Dakota - $210,496
40 - Kansas - $207,917
41 - Iowa - $204,422
42 - Texas - $203,424
43 - West Virginia - $202,592
44 - South Dakota - $201,760
45 - Alabama - $198,931
46 - Louisiana - $197,933
47 - Tennessee - $197,267
48 - Arkansas - $195,437
49 - Kentucky - $194,854
50 - Mississippi - $187,533
Connecticut, New Jersey, and New York aren't far behind, bringing the number of states with comfortable-income thresholds above $290,000 to six.
Colorado and Vermont Make the Top 10
As expected, many of the highest income thresholds are concentrated in the Northeast and along the West Coast.
However, Colorado has the seventh-highest threshold in the country at $283,213, ranking above Washington and Oregon.
Vermont rounds out the top 10 at $280,384, despite having theĀ second-smallest populationĀ of any U.S. state. Meanwhile, nearby states like New Hampshire, Maine, and Rhode Island all fall outside the top 10.
Just Six States Come in Below $200,000
Despite theĀ wide range in living costsĀ across the country, only six states have a comfortable-income threshold below $200,000 for a family of four.
Mississippi ranks lowest at $187,533, followed by Kentucky.Ā The states of Arkansas, Tennessee, Louisiana, and Alabama also fall below the $200,000 mark.
The gap between Massachusetts and Mississippi exceeds $142,000 per year, meaning the Massachusetts benchmark is about 76% higher.
š¤Can Decentralized AI Stop Big Tech from Owning the Future of Robotics?š¤
The race to build the future of robotics is no longer just about robots. It's about who controls the intelligence behind them.
Ā
Over the last three years, a small group of companies has emerged as the backbone of the AI revolution. Microsoft provides cloud infrastructure. NVIDIA supplies the chips. Google, OpenAI, Anthropic, Meta, and others develop the models. Together, they control much of the compute, data, and software stack powering modern AI.
Ā
Now that AI is moving into the physical world, many are asking a bigger question:
Ā
Will these same companies end up controlling robotics too?
Ā
It's a valid concern.
Ā
The latest generation of robots relies on enormous amounts of compute, simulation, training data, and foundation models. Many robotics startups today are built on infrastructure provided by large technology companies. NVIDIA's Omniverse is becoming a key simulation environment for robot training. Microsoft Azure is powering the training of robotics foundation models. Physical AI startups increasingly depend on hyperscale cloud infrastructure to train and deploy intelligent systems. Recent partnerships across the industry show just how central Big Tech has become to robotics development.
But while Big Tech is building the highways, another movement is trying to ensure it doesn't own every destination.
Ā
That movement is decentralized AI.
Ā
Why Decentralized AI Exists
Ā
The idea behind decentralized AI is simple. Instead of a handful of companies owning the models, compute infrastructure, data pipelines, and intelligence networks, these resources are distributed across thousands of participants.
Ā
This means anyone can contribute compute, contribute models, validate outputs and can participate.
The most visible example today is the decentralized AI network known as Bittensor (@bittensor). The network has evolved into a large ecosystem of specialized AI markets called subnets, where participants compete to provide useful machine intelligence and are rewarded based on performance. Rather than relying on a single company, intelligence is generated and validated by a distributed network of miners and validators.
Ā
Think of it as an attempt to build an open marketplace for AI instead of a world where intelligence is rented from a few centralized providers.
Ā
Why This Matters for Robotics
Ā
Robotics has a unique problem. Unlike chatbots, robots operate in the physical world. They need to perceive environments, make decisions, move safely and they need to learn continuously.
Ā
The challenge is that collecting and training on real-world robotic data is incredibly expensive. That's one reason large companies have such an advantage. They can afford the compute, simulation environments, and data infrastructure needed to train robotics models at scale.
Ā
This is where decentralized systems become interesting.
Ā
Instead of one company collecting all the data and training all the models, decentralized networks could allow thousands of contributors to participate in building robotic intelligence.
Ā
Imagine a future where:
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.
Ā
That vision is beginning to emerge.
Ā
Bittensor's Move Toward Physical AI
Ā
While many people associate Bittensor (@bittensor) with language models and AI services, parts of the ecosystem are increasingly exploring embodied intelligence and robotics.
Ā
One example is Kinitro, a subnet focused on incentivizing the training and evaluation of embodied AI systems. The goal is to create competitive environments where developers build robotic intelligence and are rewarded based on performance.
Ā
The broader Bittensor ecosystem has also expanded into compute marketplaces, distributed inference systems, bandwidth infrastructure, and AI coordination layers that could eventually support robotics workloads. Several subnets now focus on decentralized compute, confidential inference, data transfer, and model training, critical components for future robotic systems.
Ā
In other words, the pieces are starting to appear.
Ā
Not a decentralized robot network yet.
Ā
But the infrastructure that could support one.
Ā
Beyond Bittensor: The Rise of Physical AI Networks
Ā
Bittensor isn't alone.
Ā
Across the industry, researchers and builders are experimenting with decentralized approaches to physical AI.
Ā
New research published in 2026 introduced the concept of DAO-enabled decentralized physical AI, or DePAI. The idea combines robotics, decentralized infrastructure, AI models, governance systems, and human oversight into a single framework. Instead of centralized control, robots and physical infrastructure could be coordinated through transparent rules and distributed ownership models.
Ā
At the same time, developers are exploring decentralized operating systems for robots that allow machines to communicate directly with each other and with distributed compute resources. These architectures are designed to make robotic systems more resilient and less dependent on a single cloud provider.
Ā
The goal is not simply decentralization for its own sake.
Ā
The goal is resilience.
Ā
If one server fails, the system continues.
Ā
If one company disappears, the network survives.
Ā
If one participant leaves, innovation continues.
Ā
But Here's the Reality
Ā
Decentralized AI faces the same challenge every decentralized technology faces.
Ā
Big Tech has resources. A lot of resources.
Ā
Training advanced robotics models requires enormous compute budgets, sophisticated simulation environments, access to specialized hardware, and vast amounts of real-world data.
Ā
That's why many robotics startups still partner with major cloud providers and AI companies. It's often the fastest path to deployment.
Ā
And there are legitimate concerns about whether decentralized networks can maintain quality, reliability, and security at the scale required for industrial robotics. Even researchers studying decentralized AI systems have highlighted risks around concentration, incentives, governance, and network security.
Ā
The challenge isn't just decentralizing intelligence.
Ā
It's decentralizing intelligence while maintaining performance.
Ā
That's much harder.
Ā
The Most Likely Outcome
Ā
The future probably won't be fully centralized. And it probably won't be fully decentralized either. Instead, we're likely heading toward a hybrid model.
Ā
Large technology companies will continue providing chips, cloud infrastructure, simulation platforms, and foundational research.
Ā
At the same time, decentralized AI networks will emerge as alternative coordination layers where intelligence, data, and economic value can be shared more openly.
Ā
The companies building robots may use NVIDIA hardware.
Ā
Train on Azure.
Ā
Run foundation models from OpenAI.
Ā
But they may also participate in decentralized data networks, decentralized compute markets, and decentralized intelligence protocols.
Ā
The future of robotics could end up looking less like a monopoly and more like an ecosystem.
Ā
The Bigger Question
Ā
The real question isn't whether decentralized AI can eliminate Big Tech.
Ā
It can't.
Ā
At least not anytime soon.
Ā
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.
Ā
As robots become workers, assistants, delivery drivers, factory operators, and even economic agents, that question becomes increasingly important.
Ā
Because the battle for the future of robotics is no longer about hardware.
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Welcome to the Dinarian on Locals, where we discuss everything blockchain and digital asset related. We are here to learn from one another as this is a new and ever evolving space. Please post and share what you like, but be respectful to others as they are here to learn as well.
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