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FANTOM: Governance Vote 4: Unlocking The New Frontier for Validators and Stakeholders
June 28, 2024
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  • Migrate Rewards: Limit inflation by migrating Opera block rewards to Sonic.
  • Accessing Staked Value: Simplify Sonic’s staking mechanisms to unlock hundreds of millions in LST (Liquid Staking Token) liquidity. Engaging with reputable native and external LST providers like BeethovenX, FRAX, and others.
  • Supply and Burn: Enhance network security and value accrual through limiting inflation and innovative burn implementations.
  • Increase ecosystem Rewards: Boost GasM rewards up to 90% returned to an exclusive number of applications.
  • Vault Change: Migrate the current Ecosystem Vault rewards to the community ran SCC (Sonic Community Council)

For additional details on the upgrade from $FTM to $S as well as information on the Sonic network and technology, read this forum post 2.

Increasing Validator Value

This proposal seeks the Fantom community’s support to accelerate validator and stakeholder’s transition from the Fantom Opera chain to the new Sonic network.

First, this proposal will outline an Opera-to-Sonic migration plan for validator block rewards. This plan seeks to tap into a potentially ~$750m+ LST ecosystem, boosting overall adoption and DeFi activity. With the inclusion of this TVL and additional DeFi composability benefits, Sonic is primed to capitalize on the strong ~48% staked supply which has existed on Opera since inception. Previously, due to Opera’s constrictive staking terms and un-delegation periods, LSTs only occupy less than 4% of the total staked “supply” in comparison to 40% on fellow PoS networks like Ethereum. By decreasing the minimum and max lock-up period from one year to 14 days (while maintaining a competitive reward rate), the network can capitalize on the benefits of liquid staking while continuing to secure the network efficiently. Additionally, we’re seeking to modify our transaction fee structure to increase burn rate and dApp rewards. Lastly we are seeking to update Ecosystem vault permissions to enable further funding to the SCC to further ecosystem support from third-parties.

An active Liquid Staking Tokens (LST) market for Sonic validators provides the following benefits:

  • Increased TVL and capital inflows to Sonic’s DeFi ecosystem
  • Lower opportunity costs for staking, accessing the capital for alternative strategies (More yield opportunities for validators and stakers)
  • Encouraging more Sonic stakeholders and aligning incentives for its growth
  • Increased volume for network
  • More available pairs for DeFi ecosystem
  • DeFi composability and integration of LST’s into DApps such as lending, borrowing, liquidity pairs, CDPs and more.

Migrating Fantom Block Rewards

Block rewards for Opera validators are currently set to last for the next 1,344 days. This proposal introduces the reduction of Opera block rewards, as the majority of validators and stakers migrate to $S. We intend to migrate those funds as rewards for Sonic validators, while the Fantom Foundation maintains Opera validators for an indefinite period of time.

Inflation Network Block Rewards

We intend to migrate those funds as rewards for Sonic validators, while the Fantom Foundation maintains Opera validators for an indefinite period of time.

As outlined below, Sonic’s Annual Percentage Yield (APR) target is 3.5% per year. To ensure this is achievable without inflation in Sonic’s first four years, the network will migrate the remaining $FTM block rewards from Opera to Sonic as yield for Validators and Stakers in the $S token. As a result, the APR on Opera for Validators and Stakers will diminish entirely upon Sonic’s genesis.

Opera’s remaining FTM block rewards will target a rate range of 0%. Further, new tokens will not need to be minted until year four of the Sonic network deployment for validator security (see chart), retaining value for all $FTM and $S holders and ensuring Sonic will not require new inflationary block rewards at genesis.

Validator/Staker Max-Stake and Yield Targets

Currently, there is a variable up to one-year locking requirement for validators and stakers to achieve the maximum yield on Opera. While this mechanism is beneficial in sustaining network security, it impedes capital efficiency of the staked tokens and their potential to benefit the network’s DeFi landscape.

Further, this variable lock-in period creates unnecessary complexity for validators and the LSTs built around them via excessive waiting times and long un-delegation processes.

Annual % Yield Return

This proposal seeks to reduce the minimum and maximum lock-up period for optimal rewards from Opera’s current one week to one year with a seven day un-delegation model to a simplified hard minimum period of 14 days period without a variable APR scale, and a seven day un-delegation period.

By reducing this locking period and providing more liquidity to validators and stakers, we target a 3.5% return when ~50% of the network is staked and realize a 1.75% inflation rate per annum. The graph above outlines this target yield for each percentage of the network staked. The minimum and maximum lock-up period and target rate will both change at the start of the Sonic network.

As mentioned above, this rate will be sustained for the first four years by migrating the remaining $FTM block rewards for the Sonic Network in the form of $S. At the end of this time period, new tokens will be minted from the network to ensure this target rate (and the security of the network) is properly and consistently maintained.This may be modified by a new governance proposal that passes before this four year period ends.

Burn and Gas Monetization (GasM)

The proposed 3.5% target block reward rate ensures the Sonic network can continue to support its applications. By locking in this reward rate for validators, the network can increase its token burn and provide higher fees for builders as outlined below:

  • Non-GasM Participants: 50% of the transaction fee will be burned, and the remaining will be tipped to validators.
  • GasM Participants: Up to 90% of the reward will be allocated to an exclusive number of dApps’, with the remaining amount sent to validators as a fee.

GasM is a novel method of rewarding builders on Fantom for the demand they drive to the network. Sonic’s scalability allows the network to offer up-to 90% “cash back” on gas used for an exclusive number of dApps.

The number GasM applications will require an approval of at least 55% approval and 10% quorum through any voting mechanism available on chain (e.g. fwallet governance, snapshot).

Potential Gas Fee Allocations

 OperaSonic (Non-GasM Tx)Sonic (GasM Tx)
Burn5%50%0%
Fee to validators70%45%10%
Vault > S.C.C10%5%0%
Gas Monetization15%0%90%
Total100%100%100%

Burn and GasM: An Example

  • Scenario:
    • 50% of transactions from GasM participants, 50% burned/validators.
    • Average cost of 1 cent per transaction.
  • Network Capability: Sonic network can handle 100M+ transactions per day.
  • Forecast: With increased spending on business development and marketing, we anticipate a significant impact on transactions.
  • Projection:
    • The network is capable of high throughput and scaling to 100M+ transactions per day. Just achieving 10 million transactions per day alone would result in:
      • ~$0.1 million inflow per day
      • ~$36.5 million inflow per year
      • ~$9.125 million burned per year
      • ~$10.095 million paid as bonuses to validators
      • ~$16.425 million paid to Sonic developers and builders
    • This projection utilizes less than 1/10 of the network’s capability

Sonic Labs Ecosystem Vault v2

The Fantom Ecosystem Vault 2 was initially launched to fuel the community ecosystem by sharing a percentage of total gas fees used with select Dapps in the community. You can learn more about this initiative here 1.

To extend this program to the Sonic network, we will revise the program to allocate quarterly disbursements from the Ecosystem Vault to the Sonic Community Council (SCC), 1 an independently operated collective of ecosystem members who actively contribute to elevating the Sonic community via user-based programs, assisting with developer onboarding, and dApp support. The amount will be decided at the discretion of the Sonic Foundation and reflect the SCC’s previous quarter performance.

What happens to Opera Validators?

This proposal requests validators grant the Foundation the authority to create and activate a “Migration Validator/Staker Unlock” on the day of the Sonic launch, enabling all validators to lock up at that time on Opera to access the Sonic network immediately. After discussions with many large validators, we are confident a significant majority of the network will migrate to start validating on the inception of the Sonic network.

While we anticipate an overwhelming majority (> 90%) of $FTM tokens will convert to $S, the Opera network will continue to operate as a decentralized network if the Foundation does not hold a majority of the validating power.

Next Steps

Upon passing, this governance vote will finalize the tokenomic migration plan with a concise Sonic white paper in the works, including information regarding all previous governance votes.

Outline of Governance Proposal

  • Reducing the max and min lock-up period for validators and stakers from one year to 14 days.
  • Migrate the remaining $FTM from the remaining validator block rewards from Opera to Sonic upon its mainnet launch.
  • Target a 3.5% yield for validators and stakers when 50% of the network is staked through inflation (Inflation from rewards starting 4 years post-Sonic launch)
  • Increase potential GasM distribution to as much as 90% with the remaining burned
  • Increase burn for non-GasM transactions to 50% with the remaining tipped to validators
  • Right to create the “Migration Validator/Staker Unlock” as described above.

Voting

Do you agree with the outlined proposal covering gas mechanics, inflation rate, burn, lock-up period, and migration of block rewards?

  • Yes
  • No
  • I want different options

👉 VOTE NOW

 

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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.

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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.

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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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