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IMF: Facing a Darkening Economic Outlook: How the G20 Can Respond

By Kristalina Georgieva

As G20 ministers and central bank governors gather in Bali this week, they face a global economic outlook that has darkened significantly.

When the G20 last met in April, the IMF had just cut its global growth forecast to 3.6 percent for this year and next—and we warned this could get worse given potential downside risks. Since then, several of those risks have materialized—and the multiple crises facing the world have intensified.

The human tragedy of the war in Ukraine has worsened. So, too, has its economic impact especially through commodity price shocks that are slowing growth and exacerbating a cost-of-living crisis that affects hundreds of millions of people—and especially poor people who cannot afford to feed their families. And it’s only getting worse.

Inflation is higher than expected and has broadened beyond food and energy prices. This has prompted major central banks to announce further monetary tightening—which is necessary but will weigh on the recovery.

Continuing pandemic-related disruptions—especially in China—and renewed bottlenecks in global supply chains have hampered economic activity.

As a result, recent indicators imply a weak second quarter—and we will be projecting a further downgrade to global growth for both 2022 and 2023 in our World Economic Outlook Update later this month.

Indeed, the outlook remains extremely uncertain. Think of how further disruption in the natural gas supply to Europe could plunge many economies into recession and trigger a global energy crisis. This is just one of the factors that could worsen an already difficult situation.

It is going to be a tough 2022—and possibly an even tougher 2023, with increased risk of recession.

That is why we need decisive action and strong international cooperation, led by the G20. Our new report to the G20 outlines policies that countries can use to navigate this sea of troubles. Let me highlight three priorities.
First, countries must do everything in their power to bring down high inflation.

Why? Because persistently high inflation could sink the recovery and further damage living standards, particularly for the vulnerable. Inflation has already reached multi-decade highs in many countries, with both headline and core inflation continuing to rise.

This has triggered a monetary tightening cycle that is increasingly synchronized: 75 central banks—or about three-quarters of the central banks we track—have raised interest rates since July 2021. And, on average, they have done so 3.8 times. For emerging and developing economies, where policy rates were lifted sooner, the average total rate increase has been 3 percentage points—almost double the 1.7 percentage points for advanced economies.

Most central banks will need to continue to tighten monetary policy decisively. This is especially urgent where inflation expectations are starting to de-anchor. Without action, these countries could face a destructive wage-price spiral that would require more forceful monetary tightening, with even more harm to growth and employment.

Acting now will hurt less than acting later.

Equally important is clear communication of these policy actions. This is about preserving policy credibility as downside risks abound. For example, continued inflation surprises would require a sharper monetary tightening beyond what the market has priced in, potentially causing further volatility and sell-offs in risk assets and sovereign bond markets. This, in turn, could prompt further capital outflows from emerging and developing economies.
The appreciation of the US dollar has already coincided with portfolio outflows from emerging markets: they experienced a fourth consecutive month of outflows in June, the longest such run in seven years. This is putting additional pressure on vulnerable countries.

Where external shocks are so disruptive they cannot be absorbed by flexible exchange rates alone, policymakers should be ready to act. For example: through foreign exchange interventions or capital flow management measures in a crisis scenario—to help anchor expectations. In addition, they should pre-emptively reduce reliance on foreign currency borrowing where debt levels are high. It was to help countries respond in such circumstances that we recently updated the IMF’s institutional view on this issue.

The Fund is stepping up to serve our members in other ways as well. This includes providing advice on managing reserve assets and technical assistance to strengthen central bank communications.

The goal must be to get everyone safely to the other side of this tightening cycle.

Second, fiscal policy must help—and not hinder—central bank efforts to bring down inflation.

Countries facing elevated debt levels will also need to tighten their fiscal policy. This will help reduce the burden of increasingly expensive borrowing and—at the same time—complement monetary efforts to tame inflation.
In countries where recovery from the pandemic is more advanced, shifting away from extraordinary fiscal support will help tamp down demand and thus reduce price pressures.

But that is only part of the story. Some people will need more support, not less.

This requires targeted and temporary measures to support vulnerable households facing renewed shocks, especially from high energy or food prices. Here, direct cash transfers have proven to be effective, rather than distortionary subsidies or price controls that typically fail to reduce the cost of living in a durable way.

Over the medium-term, structural reforms are also crucial to bolster growth: think of labor market policies that help people join the workforce, especially women.

New measures must be budget-neutral—funded through new revenues or expenditure reductions elsewhere, without incurring fresh debt and to avoid working against monetary policy. This new era of record indebtedness and higher interest rates makes all this doubly important.

Reducing debt is an urgent necessity—especially in emerging and developing economies with liabilities denominated in foreign exchange (FX) that are more vulnerable to tightening global financial conditions and where borrowing costs are surging.

Already, sovereign FX bond yields have reached more than 10 percent in around a third of emerging economies—close to the highs last seen after the global financial crisis. Emerging economies with a greater reliance on domestic borrowing, such as in Asia, have been more insulated. But a broadening of inflation pressures and the attendant need to tighten domestic monetary policy faster could change the calculation.

The situation is increasingly grave for economies in or near debt distress, including 30 percent of emerging market countries and 60 percent of low-income nations.

Again, the Fund is here for its members—offering tailored analysis and advice, and a more agile lending framework to support countries in times of crisis. That includes emergency financing, increased access limits, new liquidity and credit lines, and last year’s historic SDR allocation of $650 billion.

Beyond these efforts, decisive action by all involved is urgently needed to improve and implement the G20’s Common Framework for debt treatment. Large lenders—both sovereign and private—need to step up and play their part. Time is not on our side. It is critical that creditor committees for Chad, Ethiopia, and Zambia deliver as much progress as possible at their meetings this month.

Third, we need a fresh impetus for global cooperation—led by the G20.
To avoid potential crises and boost growth and productivity, more coordinated international action is urgently needed. The key is to build on recent progress in areas ranging from taxation and trade to pandemic preparedness and climate change. The G20’s new $1.1 billion fund for pandemic prevention and preparedness shows what is possible, as do recent successes at the World Trade Organization.

Most urgent of all is action to alleviate the cost-of-living crisis, which is pushing an additional 71 million people into extreme poverty in the world’s poorest countries, according to the United Nations Development Programme . As concerns over food and energy supplies increase, risks of social instability are rising.

To avoid further hunger, malnutrition and migration, the world’s wealthier countries should provide urgent support for those in need, including with new bilateral and multilateral financing, especially through the World Food Programme.

As an immediate step, countries must reverse recently imposed restrictions on food exports. Why? Because such restrictions are both harmful and ineffective in stabilizing domestic prices. Further measures are also needed to strengthen supply chains and to help vulnerable countries adapt food production to cope with climate change.

Here, too, the IMF is helping. We are working closely with our international partners, including through a new multilateral food security initiative . Our new Resilience and Sustainability Trust will provide $45 billion in concessional financing for vulnerable countries—aimed at addressing longer-term challenges such as climate change and future pandemics. And we are ready to do more.

The particularly difficult conditions in many African countries at this moment is important to consider. In my meeting with Ministers of Finance and Central Bank Governors from the continent this week, many highlighted how the effects of this, entirely exogenous, shock was pushing their economies to the brink. The effect of higher food prices is being felt acutely as food accounts for a higher share of income. Inflation, fiscal, debt and balance of payments pressures are all intensifying. Most are now completely shut out from global financial markets; and unlike other regions don’t have large domestic markets to turn to. Against this backdrop, they are calling on the international community to come up with bold measures to support their people. This is a call we need to heed.

As the G20 meets to navigate the current sea of troubles, we can all take inspiration from a Balinese phrase that captures the spirit that is needed more than ever— menyama braya, “everyone is a brother or sister.”

https://blogs.imf.org/2022/07/13/facing-a-darkening-economic-outlook-how-the-g20-can-respond/?utm_medium=email&utm_source=govdelivery

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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! ⚡️🇺🇸

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

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

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

🔹 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! 🚀📊

Will this ignite the next market rally? Drop your predictions below! 👇🔥

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

00:00:53
September 15, 2026
🙉Sign → perceive → understand🙉

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
​🚨 BREAKING: The Final Clarity Act Bill Text is Official! 🇺🇸🔥

​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? 👀

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.

🔑 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 🚨
🚨 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...

🚨 JPMorgan’s criticism of the CLARITY Act is fueling a fresh power struggle over who gets to write America’s crypto rules 🚨
👉 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

🤖 How Bittensor SN61 RedTeam is building an autonomous cybersecurity immune system 🛡️

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:

  • 🛠️ Reverse-engineers miner techniques
  • 🔍 Identifies the underlying exploit
  • 🧬 Generates new attack variants
  • 🛡️ 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. 🚀

🔥 Key topics covered in this episode:

  • 📱 Device Fingerprinting & Proxy Detection: Catching sophisticated VPNs and residential proxy networks.

  • 🤖 ...

🏦 Three Fortune 500 banks reportedly enter RedTeam’s cybersecurity pipeline 🏦

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.

🔑 Key points

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

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

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

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

🔹 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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🤖 Nepher Robotics (SN49) unifies robot validation for enterprise deployments 🤖

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

🔑 Key points

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

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

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

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

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

🔹 ...

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 “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.

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 from SmartAsset (as of February 2026). They’re based on the familiar 50/30/20 budget: 50% for necessities, 30% for discretionary spending, and 20% for savings or other goals. These aren’t bare-minimum survival numbers—they’re what it takes to live pretty well while still putting money aside.

And as Visual Capitalist notesMassachusetts sits at the very top of that list. Massachusetts tops the ranking, with a family of four needing $329,555 per year to meet the 50/30/20 benchmark.

Hawaii follows at $313,165, while California ranks third at $302,682.

Rank State Income needed for family of four (2026)

  • 1 - Massachusetts - $329,555
  • 2 - Hawaii - $313,165
  • 3 - California - $302,682
  • 4 - Connecticut - $298,189
  • 5 - New Jersey - $295,110
  • 6 - New York - $291,533
  • 7 - Colorado - $283,213
  • 8 - Washington - $281,798
  • 9 - Oregon - $280,966
  • 10 - Vermont - $280,384
  • 11 - Alaska - $272,064
  • 12 - New Hampshire - $267,904
  • 13 - Rhode Island - $264,659
  • 14 - Minnesota - $263,078
  • 15 - Maryland - $257,837
  • 16 - Maine - $250,931
  • 17 - Montana - $249,434
  • 18 - Pennsylvania - $247,936
  • 19 - Illinois - $244,109
  • 20 - Virginia - $242,944
  • 21 - Nevada - $242,278
  • 22 - Indiana - $241,696
  • 23 - Wisconsin - $238,451
  • 24 - Arizona - $236,870
  • 25 - Utah - $235,789
  • 26 - Delaware - $228,134
  • 27 - Ohio - $226,221
  • 28 - Idaho - $226,054
  • 29 - Florida - $223,392
  • 30 - New Mexico - $223,142
  • 31 - Nebraska - $223,059
  • 32 - Missouri - $217,734
  • 33 - Georgia - $214,573
  • 34 - Michigan - $214,323
  • 35 - South Carolina - $212,909
  • 36 - North Carolina - $212,410
  • 37 - Wyoming - $212,410
  • 38 - Oklahoma - $211,910
  • 39 - North Dakota - $210,496
  • 40 - Kansas - $207,917
  • 41 - Iowa - $204,422
  • 42 - Texas - $203,424
  • 43 - West Virginia - $202,592
  • 44 - South Dakota - $201,760
  • 45 - Alabama - $198,931
  • 46 - Louisiana - $197,933
  • 47 - Tennessee - $197,267
  • 48 - Arkansas - $195,437
  • 49 - Kentucky - $194,854
  • 50 - Mississippi - $187,533

Connecticut, New Jersey, and New York aren't far behind, bringing the number of states with comfortable-income thresholds above $290,000 to six.

Colorado and Vermont Make the Top 10

As expected, many of the highest income thresholds are concentrated in the Northeast and along the West Coast.

However, Colorado has the seventh-highest threshold in the country at $283,213, ranking above Washington and Oregon.

Vermont rounds out the top 10 at $280,384, despite having the second-smallest population of any U.S. state. Meanwhile, nearby states like New Hampshire, Maine, and Rhode Island all fall outside the top 10.

Just Six States Come in Below $200,000

Despite the wide range in living costs across the country, only six states have a comfortable-income threshold below $200,000 for a family of four.

Mississippi ranks lowest at $187,533, followed by Kentucky. The states of Arkansas, Tennessee, Louisiana, and Alabama also fall below the $200,000 mark.

The gap between Massachusetts and Mississippi exceeds $142,000 per year, meaning the Massachusetts benchmark is about 76% higher.

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🤖Can Decentralized AI Stop Big Tech from Owning the Future of Robotics?🤖
The race to build the future of robotics is no longer just about robots. It's about who controls the intelligence behind them.
 
Over the last three years, a small group of companies has emerged as the backbone of the AI revolution. Microsoft provides cloud infrastructure. NVIDIA supplies the chips. Google, OpenAI, Anthropic, Meta, and others develop the models. Together, they control much of the compute, data, and software stack powering modern AI.
 
Now that AI is moving into the physical world, many are asking a bigger question:
 
Will these same companies end up controlling robotics too?
 
It's a valid concern.
 
The latest generation of robots relies on enormous amounts of compute, simulation, training data, and foundation models. Many robotics startups today are built on infrastructure provided by large technology companies. NVIDIA's Omniverse is becoming a key simulation environment for robot training. Microsoft Azure is powering the training of robotics foundation models. Physical AI startups increasingly depend on hyperscale cloud infrastructure to train and deploy intelligent systems. Recent partnerships across the industry show just how central Big Tech has become to robotics development.
But while Big Tech is building the highways, another movement is trying to ensure it doesn't own every destination.
 
That movement is decentralized AI.
 
Why Decentralized AI Exists
 
The idea behind decentralized AI is simple. Instead of a handful of companies owning the models, compute infrastructure, data pipelines, and intelligence networks, these resources are distributed across thousands of participants.
 
This means anyone can contribute compute, contribute models, validate outputs and can participate.
The most visible example today is the decentralized AI network known as Bittensor (@bittensor). The network has evolved into a large ecosystem of specialized AI markets called subnets, where participants compete to provide useful machine intelligence and are rewarded based on performance. Rather than relying on a single company, intelligence is generated and validated by a distributed network of miners and validators.
 
Think of it as an attempt to build an open marketplace for AI instead of a world where intelligence is rented from a few centralized providers.
 
Why This Matters for Robotics
 
Robotics has a unique problem. Unlike chatbots, robots operate in the physical world. They need to perceive environments, make decisions, move safely and they need to learn continuously.
 
The challenge is that collecting and training on real-world robotic data is incredibly expensive. That's one reason large companies have such an advantage. They can afford the compute, simulation environments, and data infrastructure needed to train robotics models at scale.
 
This is where decentralized systems become interesting.
 
Instead of one company collecting all the data and training all the models, decentralized networks could allow thousands of contributors to participate in building robotic intelligence.
 
Imagine a future where:
  • Warehouse robots contribute operational data.
  • Delivery robots contribute navigation data.
  • Factory robots contribute manipulation data.
  • Developers contribute models.
  • Validators evaluate performance.
The resulting intelligence becomes a shared network rather than a proprietary asset.
 
That vision is beginning to emerge.
 
Bittensor's Move Toward Physical AI
 
While many people associate Bittensor (@bittensor) with language models and AI services, parts of the ecosystem are increasingly exploring embodied intelligence and robotics.
 
One example is Kinitro, a subnet focused on incentivizing the training and evaluation of embodied AI systems. The goal is to create competitive environments where developers build robotic intelligence and are rewarded based on performance.
 
The broader Bittensor ecosystem has also expanded into compute marketplaces, distributed inference systems, bandwidth infrastructure, and AI coordination layers that could eventually support robotics workloads. Several subnets now focus on decentralized compute, confidential inference, data transfer, and model training, critical components for future robotic systems.
 
In other words, the pieces are starting to appear.
 
Not a decentralized robot network yet.
 
But the infrastructure that could support one.
 
Beyond Bittensor: The Rise of Physical AI Networks
 
Bittensor isn't alone.
 
Across the industry, researchers and builders are experimenting with decentralized approaches to physical AI.
 
New research published in 2026 introduced the concept of DAO-enabled decentralized physical AI, or DePAI. The idea combines robotics, decentralized infrastructure, AI models, governance systems, and human oversight into a single framework. Instead of centralized control, robots and physical infrastructure could be coordinated through transparent rules and distributed ownership models.
 
At the same time, developers are exploring decentralized operating systems for robots that allow machines to communicate directly with each other and with distributed compute resources. These architectures are designed to make robotic systems more resilient and less dependent on a single cloud provider.
 
The goal is not simply decentralization for its own sake.
 
The goal is resilience.
 
If one server fails, the system continues.
 
If one company disappears, the network survives.
 
If one participant leaves, innovation continues.
 
But Here's the Reality
 
Decentralized AI faces the same challenge every decentralized technology faces.
 
Big Tech has resources. A lot of resources.
 
Training advanced robotics models requires enormous compute budgets, sophisticated simulation environments, access to specialized hardware, and vast amounts of real-world data.
 
That's why many robotics startups still partner with major cloud providers and AI companies. It's often the fastest path to deployment.
 
And there are legitimate concerns about whether decentralized networks can maintain quality, reliability, and security at the scale required for industrial robotics. Even researchers studying decentralized AI systems have highlighted risks around concentration, incentives, governance, and network security.
 
The challenge isn't just decentralizing intelligence.
 
It's decentralizing intelligence while maintaining performance.
 
That's much harder.
 
The Most Likely Outcome
 
The future probably won't be fully centralized. And it probably won't be fully decentralized either. Instead, we're likely heading toward a hybrid model.
 
Large technology companies will continue providing chips, cloud infrastructure, simulation platforms, and foundational research.
 
At the same time, decentralized AI networks will emerge as alternative coordination layers where intelligence, data, and economic value can be shared more openly.
 
The companies building robots may use NVIDIA hardware.
 
Train on Azure.
 
Run foundation models from OpenAI.
 
But they may also participate in decentralized data networks, decentralized compute markets, and decentralized intelligence protocols.
 
The future of robotics could end up looking less like a monopoly and more like an ecosystem.
 
The Bigger Question
 
The real question isn't whether decentralized AI can eliminate Big Tech.
 
It can't.
 
At least not anytime soon.
 
The real question is whether decentralized AI can prevent a future where a handful of companies control every robot, every model, every dataset, and every decision made by the machines operating around us.
 
As robots become workers, assistants, delivery drivers, factory operators, and even economic agents, that question becomes increasingly important.
 
Because the battle for the future of robotics is no longer about hardware.
 
It's about who owns the intelligence.
 
And that battle is just getting started.
 
 

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