There is an unprecedented situation emerging in London, where the relentless hemorrhaging of one of the world’s largest stockpiles of silver is now well and truly under way.
For the last 9 months, this stockpile of silver, held in the LBMA vaults in London, has been consistently falling each and every month, and has now reached an all time low (since vault holdings records began in July 2016).
These vaults comprise the precious metals storage facilities in and around London run by the bullion banks JP Morgan, HSBC and ICBC Standard Bank, as well as the London vaults of three security operators, namely Brinks, Malca-Amit and Loomis. Since the system of vaults is administered and coordinated by the London Bullion Market Association (LBMA), these vaults are collectively known as the ‘LBMA vaults’.
That article covered the vault data up to the end of June 2022, where the London silver holdings had reached the dubious milestone of having dropped below the 1 billion ounce level, specifically falling to 997.4 million ozs (31,022 tonnes).
London sub-Billion Market Association (LBMA)
Since then, however, the situation has only worsened. Latest data for July and August show that the downward trend is still very much intact. During July 2022, London silver inventories fell by another 4.66% month-on-month, with the vaults seeing an outflow of 46.5 million ozs of silver (1447 tonnes). This brought total LBMA London silver holdings down to 950.9 million ozs (29,576 tonnes), and a new all time low since records began. (Note the lowest previous low had been 951.4 million ozs at the end of July 2016).
Now that August 2022 vault data has been released (LBMA release vault data by the 5th business day of a new month), we can see that August saw no reprieve, because in August the London silver holdings fell by another 3.62% month-on-month, with the vaults seeing an outflow of 34.4 million ozs of silver (1070 tonnes). This brings the LBMA silver vault inventories down to 916.5 million ozs (28,506 tonnes).
In other words, during these two months of July and August 2022, the LBMA vaults have lost another 2517 tonnes of silver.
With consistent silver outflows over the last 9 months to the end of August 2022, the LBMA silver vaults have now lost a whopping 254.5 million ozs (7915 tonnes) of silver since the end of November 2021. In other words, from a situation where the LBMA silver inventories had been 36,421 tonnes at the end of November 2021, they are now 21.7% lower at 28,506 tonnes.
To put all of this into context, the Silver Institute estimates that world annual silver mining production will only be 843.2 million ozs this year. That’s 26,262 tonnes. So the LBMA vaults, with 28,506 tonnes as of the end of August 2022, now hold just less than one year’s mine supply of silver.
In addition, except for a blip during November 2021 in which LBMA silver inventories rose by 311 tonnes, the LBMA silver vaults have actually seen outflows for 13 of the last 14 months. This is because silver inventories in London also fell in each of the months of July, August, September and October 2021. Putting all of this together means that since the end of June 2021, the LBMA vaults in London have lost 8200 tonnes of silver (263.3 million ozs), and the vaults now hold silver representing just over one year’s mine production.
While LBMA silver inventories did rise during the first six months of 2021, the net outflow from January 2021 to the end of August 2022 is still 5102 tonnes. And people say there is no silver squeeze?
But that is actually only half the story, because as readers of these pages will know, a majority of the silver within the LBMA vaults is held by Exchange Traded Funds (ETFs) and is already accounted for, and is therefore not (unless it is sold out of ETFs) available to the market. Additionally, this silver in ETFs is not, as the LBMA disingenuously claims, available to “underpin the physical OTC market."
Backing this ETF silver out of the headline figure is thus even more revealing. According to the calculations of GoldCharts’R’Us, as of the end of August there were 18,110 tonnes of silver held by silver-backed ETFs which store their silver in London. This means that of the 28,506 tonnes of silver that the LBMA claims to be held in its London vaults, 63.5% of this is held in ETFs, and only 10,396 tonnes (36.4%) is not held by ETFs. This 10,396 tonnes also represents only about 40% of annual silver mining supply.
Back at the end of June 2022 when the LBMA data claims that there were 31,023 tonnes of silver in the London vaults, the combined silver-backed ETFs which store their silver in London accounted for 19,422 tonnes (62.6%) of this total, leaving a remainder of 11,601 tonnes of silver (37.4%) not held in ETFs. Fast forward to the end of August, and you can see that ETFs now comprise a greater percentage (63.5%) of all the silver in the London vaults. This is because, while there have been outflows of ETF held silver over these two months, there have been even greater outflows of non-ETF held silver.
These calculations were done on 9 September using silver ETF bar lists dated 8 September. This ETF silver is held in the London vaults of JP Morgan, HSBC, Brinks, Malca Amit, and Loomis.
Together these 13 ETFs currently hold 17,759.7 tonnes of silver in the LBMA London vaults.
The LBMA London vaults figures also include silver held by clients of BullionVault and GoldMoney. BullionVault clients hold 491.2 tonnes of silver in the LBMA vaults in London (same as at the end of June, while GoldMoney clients hold 186.8 tonnes in the LBMA vaults (one tonne less than in June). Adding these two figures to the ETF total means that as of 8 September 2022, there were 18,437.6 tonnes of silver held by silver-backed ETFs and private client investors in the LBMA London vaults, which to reiterate, has nothing to do with “London’s ability to underpin the physical OTC market”.
This means that of the 28,506.28 tonnes of silver as of the end of August 2022, only 10,068.7 tonnes of silver is not held in ETFs. And another caveat as usual: of the London silver not held in ETFs, some of this too represents allocated silver holdings of the wealth management sector, such as physical silver held by investment institutions, family offices and High Net Worth individuals.
So as more and more silver drains out of the LBMA London vaults due to continued strong global demand, the free float (the amount of silver that is available to ‘underpin’ trading), is diminishing.
COMEX Silver also in Crisis
Over on COMEX in New York, the silver situation is also precarious, with ‘Registered’ silver inventories in the COMEX approved warehouses practically in freefall, and at a four and a half low. See the following chart. Latest figures for 9 September show that registered inventories (those that are warranted and available to back COMEX silver futures contract delivery) are now only 46 million ozs (1430 tonnes). This is insanely low. For example, more silver left the LBMA vaults during July 2022 (1447 tonnes) than there is currently in COMEX registered silver stockpiles.
Regarding the COMEX category of ‘Eligible’ silver (which merely represents silver stored in the COMEX approved vaults which could be traded if it was put under warrant, but which realistically may have nothing to do with COMEX trading), the amount of silver in the COMEX eligible category hasn’t really fluctuated much so far in 2022 and has ebbed and flowed by about 30 million ozs (930 tonnes) within the 250-280 million ozs range. See the following chart.
With so much silver exiting the London vaults, the silver holdings on COMEX cannot explain this, since the silver leaving London is not showing up in New York. So where is the silver that is leaving London going to?
A Resurgence in Indian Silver Demand
Apart from 2022’s strong global investment and industrial demand for silver which is detailed by the Silver Institute here, there is now huge new physical demand entering at the margin, a case in point being India. Indian silver imports are now seeing some of their strongest monthly figures in recent years. See chart below which includes silver imports into India up to the end of July 2022.
Reports out of India also say that July has been a record month, according to the following interview with Metals Focus India.
Conclusion
The existence of ETF silver in London is key to the ability of the LBMA bullion banks to control the market and the silver price.
LBMA bullion banks / ETF Authorised Participants appear to use London silver ETFs as a top up fund for physical silver, scaring the market by bringing the paper silver price lower and flushing out / triggering institutions and retail to sell ETF units, at which point the bullion banks pick up and convert these units, thereby obtaining extra metal that’s needed to meet physical demand. In fact, as physical silver demand rises, bullion banks will try to get the price lower so as to have access to the silver that is held by the ETFs.
But the bullion banks know that in the West, a higher silver price brings in more ETF buyers, which in turn leads to more of the silver that is in the LBMA vaults being ‘spoken for’ by the ETFs. Which is why the bullion banks have a vested interest in keeping a lid on the silver price, because they don’t want a situation (such as early 2021) where ETF investor demand gobbles up a greater and greater proportion of LBMA silver holdings, as then this silver cannot be used to supply other industrial and investor demand (i.e. global demand outside London). See BullionStar article “LBMA acknowledges “Buying Frenzy” in Silver Market and silver shortage Fears” from April 2021.
This circus trick, where the bullion banks have to keep all the plates spinning at the same time, only works when they can control the various sources of demand and borrow silver from the ETFs. Which they do via controlling the silver price.
But as demand for physical silver continues to accelerate globally and silver continues to flow out of London at an astounding rate (which are factors which the bullion banks seem to have lost control of), is this crunch time again for the LBMA?
Only time will tell, but with physical silver demand firing on all cylinders and massive amounts of silver leaving the LBMA London vaults, the bullion bank tactics of rinse and repeat in creating a ‘paper’ silver price unconnected to physical demand and supply is becoming more and more exposed.
🚨 BIG NEWS: Speaking to a packed room of over 1,000 attendees at ETH Zurich, Edward Snowden called for Sam Altman to face IMPRISONMENT to establish legal liability for harms caused by OpenAI's models—drawing massive, thunderous applause! 👏💥
Time to cut through the corporate "safetyism" PR distraction 🎭 and demand true accountability. Lock him up! 🔒🏛️
🚨 BREAKING: BlackRock lays off 600 employees, hitting the ESG division hardest. 📉💼
The global collapse of ESG is accelerating:
💸 $5 Trillion Lost: Global ESG investments have plummeted by $5 trillion in just 2 years as investors pull back.
⚖️ The Mechanism of Control: ESG has been used by massive institutional asset managers like BlackRock and Vanguard as a leverage system to force corporate alignment with social and political agendas.
🗣️ In Their Own Words: Watch BlackRock CEO Larry Fink (seated alongside the CEO of AmEx) explicitly explain how ESG metrics are deployed to "force behaviors" across the corporate landscape.
The narrative is crumbling, and the markets are responding in real time 🛑📉
🚨 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 ...
🚨 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 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 🚨
🚨 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.
👉 Coinbase just launched an AI agent for Crypto Trading
👉 Coinbase just launched an AI agent for Crypto Trading
This is one of the single best breakdowns of the $TAO institutional thesis you will read this year. 🧠
The smart money isn't speculating on whitepapers—they are positioning for the core engine of decentralized machine intelligence. ⚡️
Key Takeaways from @2xnmore:
1️⃣ Institutional Conviction: From Barry Silbert personally taking the CEO seat at Yuma to Grayscale’s spot ETF filing, TradFi heavyweights are quietly building the institutional plumbing for long-term $TAO allocation. 🏦
2️⃣ Real-World Execution: Subnets like Chutes (9.1T+ tokens processed), Score (PwC France enterprise alliance), and RESI aren't promises—they are live revenue-generating businesses running on decentralized compute. 📊
3️⃣ Supply Squeeze & Capital Migration: We are living through the post-halving supply crunch while less than 20% of staked $TAO sits directly in subnets. Once subnets cross key market cap milestones, capital migration from root stakers will trigger a massive ...
🌌 Gravity may not be a force—it may be the shape of spacetime 🌌
Einstein’s general theory of relativity describes gravity not as an invisible pull, but as the curvature of spacetime created by mass and energy.
🔑 Key points
🔹 Earth curves spacetime: Massive objects change the geometry around them.
🔹 Objects follow curved paths: What we experience as falling is an object moving along the natural path created by curved spacetime.
🔹 Gravity affects time: Clocks run more slowly in stronger gravitational fields.
🔹 Light also bends: Even though photons have no rest mass, their paths follow the curvature of spacetime.
🔹 Gravity is geometric: In Einstein’s model, objects are not necessarily being “pulled” through space—they are following spacetime’s structure.
🔹 Newton still works locally: Newtonian gravity remains highly accurate for ordinary situations, while relativity explains extreme conditions more precisely.
📣 Brandtensor aims to make Bittensor’s best ideas impossible to ignore 📣
Brandtensor is positioning itself as a branding and growth partner for Bittensor subnet teams, helping them turn complex AI technology into clear messaging, stronger distribution, and real-world demand.
🔑 Key points
🔹 Bittensor has an adoption gap: More than 120 subnets are building services across inference, training, compute, data, prediction, cybersecurity, and other AI markets.
🔹 Technical progress is not enough: Potential users also need to understand what a subnet does, who it serves, and why its product matters.
🔹 Brandtensor focuses on communication: Services include positioning, audience-specific messaging, educational content, use-case development, launch planning, and distribution strategy.
🔹 The wider AI market is the target: Brandtensor aims to connect subnets with developers, enterprises, researchers, and businesses outside the Bittensor ecosystem.
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.
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.
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 asVisual Capitalistnotes, 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.
🤖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.
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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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