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September 02, 2022
😮Insider Fed Paper Admits the Central Bank Can’t Control Inflation😮

It appears somebody at the Federal Reserve has figured out that the central bank can’t tame inflation, so it’s setting up a scapegoat – Uncle Sam.

A paper co-authored by Leonardo Melosi of the Federal Reserve Bank of Chicago and John Hopkins University economist Francesco Bianchi and published by the Kansas City Federal Reserve argues that central bank monetary policy alone can’t control inflation.

The paper’s abstract asserts, ā€œThis increase in inflation could not have been averted by simply tightening monetary policy.ā€

In a nutshell, Melosi and Bianchi argue that the Fed can’t control inflation alone. US government fiscal policy contributes to inflationary pressure and makes it impossible for the Fed to do its job.

"Trend inflation is fully controlled by the monetary authority only when public debt can be successfully stabilized by credible future fiscal plans. When the fiscal authority is not perceived as fully responsible for covering the existing fiscal imbalances, the private sector expects that inflation will rise to ensure sustainability of national debt. As a result, a large fiscal imbalance combined with a weakening fiscal credibility may lead trend inflation to drift away from the long-run target chosen by the monetary authority.ā€

There are a couple of startling admissions in this single paragraph.

First, the authors acknowledge that the federal government uses inflation as a tool to handle its debt. In other words, it acknowledges that we’re all paying an inflation tax.

Peter Schiff talked about this inflation tax in an interview on Rob Schmitt Tonight.

"Inflation is a tax. It’s the way government finances deficit spending. Government spends money. It doesn’t collect enough taxes, so it has to run deficits. The Federal Reserve monetizes those defiticts – prints money. They call it quantitative easing, but that’s inflation. Government is getting bigger and bigger, and families across America are going to have to bear that burden through higher prices.ā€

Second, the paper concedes that merely tinkering with interest rates won’t slay inflation if the government continues to spend far beyond its means.

And make no mistake, the US government is spending far beyond its means. Although the budget deficit is shrinking as emergency pandemic spending programs wind down, the Biden administration continues to spend about half-a-trillion dollars every single month, piling onto the ever-ballooning deficit.

This paper admits what I’ve been saying for months. Government spending is a big problem for the Federal Reserve. Powell and Company continue to insist they will stay in this inflation fight until the end. But Uncle Sam depends on the Fed buying Treasury bonds in order to facilitate its borrowing addiction. As the central bank buys bonds, it creates artificial demand and holds interest rates down. The government needs low interest rates when it’s borrowing trillions of dollars. Without the Fed’s big fat thumb on the bond market, Treasury prices will continue to sink as supply outstrips demand, and interest rates will rise.

Melosi and Bianchi also tacitly admit that the Fed isn’t going to win this inflation fight and warns we could be heading toward stagflation.

"When fiscal imbalances are large and fiscal credibility wanes, it may become increasingly harder for the monetary authority to stabilize inflation around its desired target. If the monetary authority increases rates in response to high inflation, the economy enters a recession, which increases the debt-to-GDP ratio. If the monetary tightening is not supported by the expectation of appropriate fiscal adjustments, the deterioration of fiscal imbalances leads to even higher inflationary pressure. As a result, a vicious circle of rising nominal interest rates, rising inflation, economic stagnation, and increasing debt would arise.ā€

This is exactly what is happening.

Melosi and Bianchi call this a ā€œpathological situation.ā€

"Monetary tightening would actually spur higher inflation and would spark a pernicious fiscal stagflation, with the inflation rate drifting away from the monetary authority’s target and with GDP growth slowing down considerably.ā€

Well hello there, Fed! Welcome to reality.

The Federal Reserve has raised rates to 2.5%. Despite mainstream assertions to the contrary, it appears the economy has already dipped into a recession. Private sector economic activity has dropped to the lowest levels since early in the COVID lockdowns, the housing market is tanking, and the economy has charted two straight months of negative GDP growth.

During his Jackson Hole speech, Jerome Powell said the Fed will ā€œuse our tools forcefullyā€ to get inflation under control and even conceded that it will cause some economic pain. But the numbers undercut Powell’s confident assertions. The Fed would have to raise rates to a level that would obliterate this bubble economy in order to cool inflation.

I think the central bankers know this. This paper, co-authored by a Fed official, makes that pretty clear. I think the central bankers are setting the stage to finger point and pass the buck when this whole inflation-fighting scheme blows up in their faces.

The paper states, that the central bank can control inflation ā€œonly when public debt can be successfully stabilized by credible future fiscal plans.ā€

Do you think that is going to happen?

I don’t either.

In fact, the only workable plan is for the Federal Reserve to monetize more debt by buying more Treasuries with more money created out of thin air. This is one reason I’ve been saying for months that the Fed won’t win this inflation fight.

In one sense, I think the Fed is setting the stage for its own failure. It’s already making excuses. And it’s a little pathetic. The central bank put quantitative easing on steroids during the pandemic, injecting nearly $5 trillion into the economy. That is the very definition of inflation. If you want to know who to blame for this inflation mess, the Fed stands at the front of the line.

That said, this paper isn’t completely disingenuous. As I’ve already explained, the federal government plays a role in the inflation game as well. As the saying goes, it takes two to tango. Federal government spending is out of control, and the spending spree necessitates inflation. (It’s not just Biden’s fault — the Trump administration was running massive deficits prior to the pandemic.)

So, even if Melosi and Bianchi are trying to point the finger in another direction, they aren’t wrong when they write, ā€œ[Stagflation] is caused by the progressive deterioration of the fiscal authority’s credibility to stabilize its large debt and the realization that the reputation of the monetary authority is incompatible with the expected behavior of the fiscal authority.ā€

In plain English, the central bank can’t stop inflation when the federal government needs inflation to survive.

This paper won’t get much attention. In fact, it comes with a disclaimer — ā€œThe views in this paper are solely those of the authors and should not be interpreted as reflecting the views of the Federal Reserve Bank of Chicago or any person associated with the Federal Reserve System.ā€

Regardless, they’ve swerved into the truth and we’d do well to pay attention.

JH_Paper_Bianchi.pdf
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September 15, 2026
🚨 BREAKING CRYPTO NEWS 🚨

According to CNBC, SEC Chair Paul Atkins is set to announce NEW crypto rules this Friday! āš”ļøšŸ‡ŗšŸ‡ø

Here is what’s on the horizon for the digital asset space:

šŸ”¹ Project Crypto Unleashed: The SEC is moving forward with a dedicated framework for crypto assets, transfer agent updates, and adviser custody guidelines.

šŸ”¹ Regulatory Clarity: After years of uncertainty, official rules of the road are finally arriving for token issuers, exchanges, and institutional investors.

šŸ”¹ Moving Independent of Congress: Whether or not legislative bills like the CLARITY Act pass, federal regulators are taking direct action to build a modern market architecture.

This could mark a massive turning point for innovation and compliance in the U.S. crypto industry! šŸš€šŸ“Š

Will this ignite the next market rally? Drop your predictions below! šŸ‘‡šŸ”„

#Crypto #SEC #PaulAtkins #CryptoNews #Bitcoin #Ethereum #Web3 #Regulation

00:00:53
September 15, 2026
šŸ™‰Sign → perceive → understandšŸ™‰

Proof, not a promise.

Real ASL video.
Real recorded landmarks.
Real model output.

We took what we’ve been building inside UMI and put it into the first bitsign iOS product concept.

Sign → perceive → understand.

This is recorded playback, not live translation yet.

The next milestone is making this happen live.

bitsign.ai

00:00:14
September 14, 2026
ā€‹šŸšØ BREAKING: The Final Clarity Act Bill Text is Official! šŸ‡ŗšŸ‡øšŸ”„

​After more than a year of back-and-forth, the final draft is here—incorporating 126 last-minute amendments requested by Democrats just 24 hours before the vote. 🤯

​Key updates in the final text:

​Strict Ethics Oversight: Expanded restrictions now cover federal officials, judges, and spouses, with Senator Lummis noting Trump opted in voluntarily.
​Banking Safeguards: Treasury gains authority to step in if high-yield stablecoins start draining liquidity from community banks.

​Builder Protections: Civil safe harbor provisions have been strengthened to explicitly cover crypto miners and network validators.

​Market Integrity: Added guardrails target conflicts of interest and affiliate trading while leaving state consumer protection laws intact.

​Does it have enough momentum to secure 60 votes tomorrow? šŸ‘€

00:00:09
🚨 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.

šŸ”‘ Key points

šŸ”¹ 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.

šŸ”¹ The platform says it has processed nearly 38 trillion tokens since launch across 53 deployed applications and more than 700,000 registered users.

šŸ”¹ 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.

šŸ”¹ 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 🚨
🚨 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.

šŸ”‘ Key points

šŸ”¹ 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.

šŸ”¹ 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.

šŸ”¹ 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...

🚨 JPMorgan’s criticism of the CLARITY Act is fueling a fresh power struggle over who gets to write America’s crypto rules 🚨
šŸ‘‰ Coinbase just launched an AI agent for Crypto Trading

Custom AI assistants that print money in your sleep? šŸ”œ

The future of Crypto x AI is about to go crazy.

šŸ‘‰ Here’s what you need to know:

šŸ’  'Based Agent' enables creation of custom AI agents
šŸ’  Users set up personalized agents in < 3 minutes
šŸ’  Equipped w/ crypto wallet and on-chain functions
šŸ’  Capable of completing trades, swaps, and staking
šŸ’  Integrates with Coinbase’s SDK, OpenAI, & Replit

šŸ‘‰ 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 šŸ‘‰txns done by AI agents by 2025

🚨 I personally wouldn't bet against Brian Armstrong and Jesse Pollak.

šŸ‘‰ Coinbase just launched an AI agent for Crypto Trading

šŸ¤– How Bittensor SN61 RedTeam is building an autonomous cybersecurity immune system šŸ›”ļø

Cybersecurity has always been a constant cat-and-mouse game—until now. By incentivizing miners to discover novel ways to break bot detection, device fingerprinting, and geolocation systems, RedTeam transforms attacker ingenuity into fuel for an adaptive defense network.

Every exploit submitted becomes an input into an autonomous "immune system" that:

  • šŸ› ļø Reverse-engineers miner techniques
  • šŸ” Identifies the underlying exploit
  • 🧬 Generates new attack variants
  • šŸ›”ļø Develop realtime detection mechanism

In this deep dive, Oscar and Javokhir unpack how RedTeam evolved from manually breaking competing security products into a commercial cybersecurity platform now protecting over 125 million daily active users across its customer base. šŸš€

šŸ”„ Key topics covered in this episode:

  • šŸ“± Device Fingerprinting & Proxy Detection: Catching sophisticated VPNs and residential proxy networks.

  • šŸ¤– ...

šŸ¦ Three Fortune 500 banks reportedly enter RedTeam’s cybersecurity pipeline šŸ¦

RedTeam (SN61) says three Fortune 500 banks are now in its commercial pipeline, signaling growing interest in its AI-driven approach to adversarial security testing.

šŸ”‘ Key points

šŸ”¹ Three major banks are evaluating RedTeam: The institutions are reportedly considering SN61 for fraud detection, bot defense, device intelligence, and security testing.

šŸ”¹ Pipeline is not revenue: Being in a sales pipeline does not mean the banks have signed contracts or deployed the product.

šŸ”¹ RedTeam attacks detection systems: Its network of security researchers and miners searches for ways to bypass fraud and identity protections.

šŸ”¹ AI agents expand testing: Automated systems can generate and test attack variations faster than traditional manual security teams.

šŸ”¹ Financial institutions are high-value targets: Banks face constant threats involving bots, account takeover, synthetic identities, credential theft, and payment fraud.

...

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šŸ¤– Nepher Robotics (SN49) unifies robot validation for enterprise deployments šŸ¤–

Nepher Robotics is building a unified validation platform designed to help enterprises test, compare, and deploy robotic systems across different hardware and operating environments.

šŸ”‘ Key points

šŸ”¹ One validation layer: Enterprises can evaluate robots through a common platform instead of maintaining separate testing systems for each hardware vendor.

šŸ”¹ Hardware abstraction is central: SN49 aims to separate robot intelligence and evaluation from the specific machine running the workload.

šŸ”¹ Real-world performance matters: Robots can be tested across navigation, manipulation, perception, safety, and task-completion scenarios.

šŸ”¹ Simulation and physical testing can connect: Models may be evaluated in virtual environments before being validated on real robotic hardware.

šŸ”¹ Standardized benchmarks improve comparison: A common framework helps enterprises compare different models, robots, and deployment strategies.

šŸ”¹ ...

September 13, 2026
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Revolut Leak Shows the Cost of Constant ID Collection
Revolut’s mistake is the news, but the bigger problem is the growing number of companies being encouraged or required to keep copies of our most sensitive identity documents.

Online bank Revolut has revealed that it gave out sensitive personal and financial information of an undisclosed number of its customers in response to a fake government request.

The information that was handed over to an ā€œunauthorized 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 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 ā€œunder the reasonable belief that it was an authentic government agency requestā€ – 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 ā€œlimitedā€ number of its customers were affected by the data leak, and that the company’s systems were not hacked, nor was any money stolen.

The story broke on September 11 when Revolut customers started receiving an email notice about a data leak, and the news was picked up by media outlets the following day.

Revolut notice explaining customer identity and financial data was shared after an unauthorized government email request.

The reason this is a recurring problem is that companies are keeping highly sensitive information about their customers’ identities, and sometimes even financial transactions, for a long time, and this data is then available to be disclosed to third parties – either in response to valid legal requests, or, as in the case of Revolut, fake ones.

One reason for this is know your customer (KYC) and anti-money laundering (AML) rules. Revolut’s current UK customer privacy notice spells it out: the company generally keeps personal data of UK customers for no more than seven years after the relationship ends, and sometimes longer – for legal reasons.

This means that even if you close your account, your identity documents don’t disappear.

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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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 fromĀ SmartAssetĀ (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 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.

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šŸ¤–Can Decentralized AI Stop Big Tech from Owning the Future of Robotics?šŸ¤–
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.
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As robots become workers, assistants, delivery drivers, factory operators, and even economic agents, that question becomes increasingly important.
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Because the battle for the future of robotics is no longer about hardware.
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It's about who owns the intelligence.
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And that battle is just getting started.
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