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Fantoms SpiritSwap V2 is LIVE — UI & protocol upgrades

Users can now enjoy V2 via the following link: beta.spiritswap.finance

SpiritSwap has come a long way since its inception on the Fantom network one year ago. This past year has been full of highs and lows but at the end of the day the Spirit team has loved sharing every minute of this journey with you all! To celebrate our continued ingenuity and drive to consistently add value to the Fantom ecosystem, SpiritSwap is pleased to present V2 and subsequent protocol upgrades.

This project in itself has been a monumental effort by our development team, all coordinated by our core team members in their respective fields. This product is a result from months of blood, sweat, tears and a severe lack of sleep. To start, SpiritSwap would like to thank everyone involved in the development of this major overhaul.

This article explains our reasons for the V2 upgrade, what the upgrade entails, the key differences between V1 & V2, along with the architectural upgrades to the AMM infrastructure and the underlying updates to some of the contracts.

The work doesn’t stop here. Upon deploying V2, the team will be getting straight to work on V2.1 upgrades, which consist of functionality upgrades that would have taken too long to implement in the V2 rollout, balance is key.

V2 TLDR 1 minute ;
>New AMMs in the mix

>Protocol Fees: Giving back to the protocols, whenever a protocol lists with us, SpiritSwap rebates protocols` 25% of the fees their pools generate

>Implementation of a master router. This means we can add new AMMs (like balancer weighted and linear or concentrated AMMs) without having to upgrade our UI or contracts.

>Fee reduction from 0.3% to 0.18% for Classic AMM (customizable fees down to 0.01%)

>Stable AMM introduced at 0.04% fees (customizable fees down to 0.01%)

>More fees for inSPIRIT holders from 0.05% — 0.135% (Includes both base fee and vote fee)

>Non-dilutive tokenomics for inSPIRIT holders through ve(3,3) model

>Making the inSPIRIT model more sustainable: Using a mix of solidly voting models

>Introduction of Permissionless Spirit farms

> In-built bribe UI

> Gauge proxy divided into 3 isolated gauge proxies for greater balance of emissions

V2.1 TLDR;
>Introduction of weighted pools

>Introduction of linear pools — better capital efficiency by feeding to lending network

>Introduction of Permissionless Ecosystem farms

> Upgrades to bribes (% based bribes, limit bribes)

V2 will be released in two stages. The first being a public beta, which is live as of today. This gives the public the ability to switch between V1 and V2 at their leisure. The current plan is for V2 beta to be live for 2 weeks, allowing the team to receive feedback and bug reports from the community. Over this time, the development team will dedicate 95 % of development resources to remedy any reported bugs from the community. Upon this round of community testing being complete, the team will redeploy our URL to face our V2 product thus making V2 our official application moving forward.

V2 TLDR 5 minutes :
Huge overhaul of fee structure with the aim to pass as much value back to inSPIRIT holders and protocols who support SpiritSwap.
Notably our vAMM fee has been reduced from 0.3% — 0.18%. This provides a positive feedback loop between aggregator traffic, volume and fees. The introduction of the new Vote Fee further rewards inSPIRIT holders who vote on gauges that have the ecosystem’s best interest at heart. The introduction of the Protocol Fee further incentivizes protocols to add liquidity with SpiritSwap, establishing a pool of deep liquidity for more optimal trade pricing.

Bridge swap upgrade:
SpiritSwap’s bridge aggregator will pave the way for a myriad of other chains to be added to the bridge. As a part of this upgrade, people will now be able to simultaneously swap while they bridge. For example, users can now send BNB from Binance Smart Chain to Fantom Opera, but in the same process, convert this BNB to FTM with one click.

We have 2 options — cheaper fees or faster transactions.

Bribe UI:
Isolated gauge proxies:
What was a “singular gauge proxy” for boosted farms, has now been segregated into 3 isolated gauge proxies for greater control over emissions on pairs that are crucial to the SpiritSwap ecosystem.

Running snapshots and facilitating airdrops for bribes is cumbersome and laborious. It’s not a good use of developer time. As such, the bribe process has been simplified for both developers and the community. Developers of projects who have gauges can now offer a bribe and set this up directly within our inSPIRIT UI. Subsequently, inSPIRIT holders who vote on farms with active bribes can also collect their voting fees directly within the inSPIRIT page, along with their inSPIRIT weekly rewards.

Isolated gauge proxies:

What was a “singular gauge proxy” for boosted farms, has now been segregated into 3 isolated gauge proxies for greater control over emissions on pairs that are crucial to the SpiritSwap ecosystem.

Real Yield — Anti dilution for inSPIRIT holders:
This aims to further stimulate the adoption of inSPIRIT for new and existing participants in our ecosystem. The Real Yield model sees emissions redirected to ensure loyal inSPIRIT holders are never diluted by farmers.

In depth overview 20 minutes
UI and codebase upgrades.
Soully has undergone some cosmetic surgery, SOME being an understatement. As you will notice, the entire layout of the SpiritSwap application has changed for a more simplified, crisp, clean and professional look. On top of this, we have rebuilt the ENTIRE code base from scratch, which is why V2 has been such a long drawn process.

In layman’s terms, by building this code ourselves (rather than relying on forked code) we understand the mechanics of this code much better, thus are able to execute a rapid turnaround time on fixing bugs and expediting deployment of new features. Needless to say the functionality of our DEX will now be much quicker than V1.

Offering a user interface that embodies the playful nature of Soully, while highlighting the key elements users expect from a DEX, is where inspiration came from. We wanted to keep things as minimalistic as possible, meanwhile offering the layers of detail that more seasoned DeFi users have come to expect from an aspiring tier 1 DEX.

The layout of the application was given careful consideration, specifically focusing on the flow of interaction. As users will notice, their journey within the application begins where all DeFi users would expect, their portfolio. Our home page now doubles as a portfolio page, which gives a detailed overview of all user positions including single held assets, LP positions, farm, winSPIRIT, lending and borrowing, as well as eventual ApeMode positions. This will offer all users a more enhanced overview of their positions on SpiritSwap and all key components / features that are offered as a protocol.

The new landing page will feature an overview of ALL key components that SpiritSwap brings to market. Included in these key components is user education, as a lot of users are new to defi. Ensuring users who arrive at our landing page have immediate access to information they need to make informed decisions is of immense importance. As such, when new users initially arrive at the landing page before entering the application, they are offered a myriad of information that details each individual feature via the ability to click on pop up infographic cards explaining the intricacy of each feature.

Basic AMM features like Swap, Bridge, Liquidity and Farms, still retain their standard functionality but with a new look and feel to the design. The focus was to keep as much of this functionality as familiar as possible for our existing users.

However you will notice that there are some new feature additions to farms and liquidity, which aligns with some of our new AMM architecture. These will be covered in a separate paragraph related to AMM upgrades.

The inSPIRIT page has also undergone a huge facelift, now offering far greater user experience. Users can now toggle between locking more SPIRIT or increasing their delegation period to eliminate any confusion. The process of locking inSPIRIT has now also been broken down into a simple 3 step process, replicating a walkthrough type approach for users participating in our inSPIRIT model. This makes the process seamless, easy to understand and eliminates any confusion for those who are new to the ecosystem or struggle to comprehend the process.

The farm voting panel has also been updated to offer improved UX via farm voting rebalance exclusion. Currently users must exclude farms they don’t want to vote for, otherwise vote percentages will automatically be rebalanced accordingly. This has led to a cumbersome and frustrating experience for V1 users and has been something we have strived to improve since the initial inSPIRIT deployment.

My farms toggle function: This allows users to automatically flip a switch that only displays their active farms in the voting panel. This improves UX as users no longer need to scroll through endless farms picking out the ones that are pertinent to their investment strategies, but rather streamline this approach by only displaying their active positions. This also helps users easily identify the most lucrative farms to vote for in order to capture the largest amount of voting fees.

AMM upgrades.
SpiritV2 will launch with two AMMs. A variable AMM (vAMM) for variable liquidity pairs (vLP) and a stable AMM (sAMM) for stable liquidity pairs (sLP). This AMM is a modified version of Solidly with an upgrade to the fee structure.

Our AMM architecture is preceded with a master router for swaps on SpiritV2. This means we can add new AMMs (like balancer weighted/linear pools or new types of AMMs) without having to upgrade our UI or contracts. They can just be added in the master router.

In this new AMM format, swap fees now accumulate outside of LP tokens in an LP Fee contract. This is unlike our old (UniV2) AMM in which fees are compounded directly into the LP tokens themselves. In this architecture each LP Pair contract has an associated LP Fee contract to handle this logic. Breaking out the accumulated swap fees from the LPs themselves allows us to implement our LP voting logic into the gauge system (more on that later).

The sAMM will allow for the ability to set different fees than the vAMM which Solidly didn't allow for. We see this as an opportunity to fix a broken system, which is why the SpiritSwap AMM’s offers variable fee functionality. The thought process here is that by utilizing the (X²+Y²)(XY)/2=K formula, we achieve a higher concentration of liquidity resulting in tighter spreads and lower impermanent loss. This means we can offer a far better execution on swaps (fees/slippage).

Further to this, SpiritSwap also achieves the ability to offer peg support, meaning SpiritSwap can now offer more effective pricing on stable trades, but also the ability to offer a more targeted solution to tokens that require peg maintenance. With this integration, winSPIRIT pairs will achieve more effective peg maintenance. This will now entice winSPIRIT pairs to stay where they belong and retain profitability on these pairs being traded, meaning inSPIRIT holders won’t miss out on the fees captured by any trading of inSPIRIT pairs that are currently based on other AMM’s.

By offering a more competitive pricing delivery on certain stable pairs, SpiritSwap will subsequently be more competitive in the aggregator space, meaning fees we were missing out on via DEX aggregation, will be a thing of the past.

Better pricing = more fees captured by proxy of DEX aggregation.

Further to this AMM architecture upgrade, SpiritSwap intends to add another layer of architecture to the mix in V2.1 that will allow for more enhanced trading functionality, offering the ability for us to bootstrap enhanced trader UI onto our front end. For now that update will remain as a surprise for a later day.

Fee structure:
The fee structure for SpiritSwap has also undergone some upgrades. The upgraded AMM has variable fees that can be updated by governance and can go as low as 0.01%. This will help us remain competitive with fees and we won’t have to redeploy even if our competitors lower their fees. Unlike Solidly, the vAMM and sAMM can have different fees, this makes sense because stable swaps should have lower fees than variable swaps because they incur less IL.

Moving forward, SpiritSwap will be reducing fees from 0.3% to 0.18% for our classic vAMM while establishing the ability to have an even more competitive fee for our new sAMM at a respectable 0.01%.

The reason for this stems from the realization that it’s better to capture a smaller slice of a bigger pie rather than trying to take the entire pie for ourselves. This update will see a more optimal pricing on trades, meaning that we capture a larger amount of aggregator traffic (fees that are currently being missed out on).

The distribution of fees has also undergone a change. The current model sees fees allocated as follows:

5 / 6 of fees are currently given back to LP’s

1 / 6 of fees are currently used to buy back SPIRIT at market rate and distribute to inSPIRIT holders during our weekly reward distribution.
vAMM & sAMM fee restructure:

Moving forward, Fees accumulate outside of LP token (unlike uniV2 which compounds fees directly into LP). Fees will be allocated as follows:

25 % will go to our base fee:
The base fee is exactly the same as the current inSPIRIT distribution. These are the SPIRIT rewards that all inSPIRIT holders collect at the end of each distribution epoch. It is pertinent to note that with the reduction in fee we are hopeful our routers will collect a higher volume of trade traffic from aggregators. Due to increased volume by virtue of a reduced fee, this increase in volume is expected to capture a higher distribution for inSPIRIT holders each week.

25% of fees will go to the new Protocol Fee model:

The protocol reward fee model is a rebate to protocols who list LP’s with us, for example Liquid Driver.

Out of all fees collected on Liquid Drivers liquidity pools, 25% of these will be given back to the protocol who lists with us (in this example Liquid Driver).

Read more at: https://spiritswap.medium.com/spiritswap-v2-is-live-ui-protocol-upgrades-bec064ebba61

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⚠️ The UN Has Just Made This Mandatory Worldwide ⚠️
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🚀 Bittensor subnets are shipping real AI products—not just selling a narrative 🚀

While the market debates whether TAO is a genuine AI play, its subnets are producing models, deploying physical systems, offering private inference, and building recurring security products.

🔑 Key points

🔹 Gittensor (SN74) released a Qwen 3.8 27B checkpoint that runs on a single RTX 5090 and reportedly surpassed 500,000 downloads on Hugging Face.

🔹 Score (SN44) expanded its fuel-station rollout beyond Avia into Shell and Eni locations, creating a path toward direct commercial contracts.

🔹 Good Morning (SN28) made OpenAI’s GPT-6 Astra available through Bittensor with private, verifiable access at an reported 8.3% discount.

🔹 OpenRoboto (SN80) switched its community post-training base to Robbyant’s LingBot VLA 2.0 and brought an xArm 6 online to test simulation models on physical hardware.

🔹 Bitsec (SN60) launched Sentios, offering continuous smart-contract auditing instead of relying on one-time security reports.

🔹 Trishool (SN23) was accepted into OpenAI’s Trusted Access for ...

00:20:29
September 05, 2026
AI integrity when it matters most. 🚀

In high-stakes fields like aviation ✈️ and healthcare 🏥, standard Computer Vision has a critical flaw: logs can be edited. ⚠️

When safety and human lives are on the line, "just trust the logs" isn't enough.
@InferenceLabs is solving this trust gap with Sertn 🛡️

By leveraging Proof of Inference via zkML, Sertn creates verifiable, tamper-proof proof that a model executed correctly. 🔐⚡

No silent edits. No forged data. Just cryptographically guaranteed AI integrity when it matters most. 🚀

#SertnAI #ComputerVision #VerifiableAI #AI #Bittensor #ZKML #Dsperse #SN2 #tao

Sertn.ai

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🚨 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

🚀 The v1 Whitepaper from @DeSciClaims (Subnet 111) has officially dropped! 📄✨

​While Claims is currently live in v0, this newly released whitepaper details the blueprint for the transition to v1, including:

​🏗️ Architecture: The framework for turning scientific literature into structured, machine-readable claim-evidence graphs.

​🛡️ Verification Model: Grounding AI outputs directly in exact paper source spans to eliminate hallucinations.

​💡 Incentive Design: Rewarding top miners for high-accuracy extractions while ensuring robust adversarial validation.

​By structuring 300M+ scientific papers into verified claim graphs, DeSciClaims is pushing scientific AI accuracy from ~72% up to 94%! 📊🧠

Read it here:
Https://claims111.ai/whitepaper

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🌍 Stellar leads in tokenized non-U.S. government debt as sovereign assets move onchain 🌍

Stellar says it now holds more tokenized non-U.S. government debt than any other blockchain, with approximately $490 million in sovereign instruments as of August 20, 2026.

🔑 Key points

🔹 Specific category leadership: Stellar leads in non-U.S. sovereign debt, while Ethereum remains ahead in tokenized U.S. Treasuries and total real-world asset value.

🔹 RWA growth accelerated: Stellar’s tokenized real-world assets reportedly grew from roughly $500 million in early 2025 to more than $3 billion by June 2026.

🔹 Stellar represents about 9% of distributed RWA value: The network ranks among the top four blockchains for tokenized real-world assets.

🔹 Mexican and Brazilian debt are included: Etherfuse has brought Mexican CETES and Brazilian Tesouro bonds onchain.

🔹 Euro-denominated T-bills are growing: Spiko’s euro T-bill fund reportedly expanded from approximately $520 million to $970 million, with much of the...

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XDC Network (XDC) is now available for trading and custody to clients of Bitcoin Suisse AG, effective immediately.

XDC Network is an enterprise-focused Layer 1 blockchain designed to support trade finance and the tokenization of real-world assets. It bridges blockchain technology and traditional finance, facilitating applications such as asset tokenization, digital invoices and receivables, and cross-border settlements.

As an EVM-compatible network, XDC offers features tailored to enterprise use, combining the transparency of public blockchain infrastructure with the privacy required for institutional applications.
With the addition of XDC, Bitcoin Suisse continues to expand the range of digital assets available to our clients, supporting innovation across emerging blockchain ecosystems.

This social media post is for information purposes only, limited to our followers in Switzerland, and does not constitute an opinion, legal or investment advice or any other statement that creates any ...

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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.

Source

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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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Navigating the world of blockchain 🧭
Navigating the world of blockchain can feel like learning a completely foreign language. Between technical jargon and fast-moving Web3 terminology, getting started can be overwhelming.

Whether you are exploring digital assets, building on-chain, or simply trying to understand decentralized technology, here is your foundational glossary of essential blockchain terms every beginner should know.

🏛️ 1. Core Architecture: The Base Layer

  • Blockchain: A distributed, immutable digital ledger that records transactions across a peer-to-peer network of computers. Once data is written to a block and added to the chain, it cannot be altered without altering all subsequent blocks.
  • Block: A collection of verified transactions grouped together. Once filled, the block is cryptographically linked to the previous one, forming a chronological "chain."
  • Node: An individual computer connected to a blockchain network that helps validate transactions, store ledger data, and maintain network consensus.
  • Consensus Mechanism: The set of rules and algorithms that network nodes use to agree on the validity of transactions.

    • Proof of Work (PoW): Requires miners to solve complex mathematical puzzles using computational power (e.g., Bitcoin).
    • Proof of Stake (PoS): Requires validators to lock up ("stake") native tokens as collateral to participate in block validation (e.g., Ethereum).

🔑 2. Ownership & Security: Wallets and Keys

  • Public Key (Address): An alphanumeric string that acts like your bank account number or email address. It is safe to share publicly so others can send you digital assets.
  • Private Key: A secret cryptographic passphrase or key that grants full access and control over your wallet assets. Never share your private key or seed phrase with anyone.
  • Seed Phrase (Recovery Phrase): A sequence of 12 to 24 random words generated when you set up a wallet. It acts as the master backup key to restore your wallet and access your funds on any device.
  • Hot Wallet vs. Cold Wallet:

    • Hot Wallet: A software-based crypto wallet connected to the internet (e.g., browser extensions, mobile apps), making it convenient for frequent transactions but higher risk.
    • Cold Wallet: An offline hardware device (e.g., Ledger, Coldcard) designed to isolate private keys from internet-connected threats.

⚙️ 3. Execution & Functionality: Smart Contracts and Apps

  • Smart Contract: Self-executing code stored on a blockchain that automatically enforces agreement terms once predetermined conditions are met—eliminating the need for intermediaries.
  • dApp (Decentralized Application): Applications built on top of a blockchain network that run via smart contracts rather than centralized cloud servers.
  • Gas Fees: Network transaction fees paid to validators or miners to cover the computational energy required to process actions on a blockchain.
  • Layer 1 vs. Layer 2:

    • Layer 1 (L1): The underlying primary blockchain network (e.g., Bitcoin, Ethereum, Solana) that handles base security and finality.
    • Layer 2 (L2): Secondary frameworks or companion networks built on top of an L1 to increase transaction speeds and lower gas fees (e.g., Arbitrum, Optimism, Base).

💰 4. Financial & Market Concepts

  • Tokenomics: The economic design, supply dynamics, utility, and distribution model of a cryptocurrency or token project.
  • DeFi (Decentralized Finance): Financial services—such as lending, borrowing, trading, and earning interest—built on smart contracts without traditional banks or financial intermediaries.
  • Liquidity: The ease with which an asset can be bought or sold in a market without significantly impacting its price.
  • DYOR (Do Your Own Research): A foundational golden rule in the Web3 space reminding users to independently verify technical code, whitepapers, and team backgrounds before making any capital commitments.

💡 Quick Cheat Sheet

"Not your keys, not your coins."

If you do not hold the private keys or seed phrase to your digital wallet, you do not truly own the assets inside it—a centralized entity or exchange does. Always prioritize security first as you explore the space.

🙏To support my work, Helping to keep the signal high and the noise low:

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👇 Crypto Donations 👇

XRP: r9pid4yrQgs6XSFWhMZ8NkxW3gkydWNyQX
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