tokenomics

暗号におけるファンダメンタル分析の意味を学びましょう。投資前に暗号プロジェクトをステップバイステップで評価し、初心者の失敗を避ける方法を発見してください。
多くの初心者は、コインを理解せずに購入するため、暗号でお金を失います。
彼らは流行に従います。
彼らはインフルエンサーに従います。
彼らは感情に従います。
しかし、賢い投資家は何か異なることをします。投資する前にプロジェクトを研究します。
この記事では、あなたが自分のお金を投入する前にどのコインでも適切に分析できるように、暗号におけるファンダメンタル分析を学びます。

​Investing in the future of AI often feels abstract, but the Fabric Foundation is bringing concrete utility to the table with $ROBO . As the native asset of the Fabric network, its roles are clearly defined to ensure long-term ecosystem health and growth:
​1️⃣ Network Fees: Every interaction, from identity verification to mission settlement, is powered by $ROBO.
2️⃣ Machine Identity: Robots need a way to prove who they are and what they’ve done on-chain—$ROBO makes this verifiable and secure.
3️⃣ Governance: Token holders help shape the future of the @Fabric Foundation protocol, ensuring human-machine alignment remains the top priority.

​With a fixed supply and a focus on "Proof of Robotic Work," Robo is designed to capture the economic value of every machine operating within its network. If you’re tracking the intersection of blockchain and physical AI, this is the project to watch! 📈⚡
​#ROBO #Tokenomics #blockchain #Binance #Write2Earn @Fabric Foundation $ROBO

私はまだ、初めてエアドロップを受け取ったときのことを覚えています。何も期待せずにウォレットを開けると、そこには前日には存在しなかった残高がありました。それは静かに感じました。支払っていないにもかかわらず、得たものでした。その小さな驚きが、私をどんなホワイトペーパーよりも深く暗号の世界に引き込んだのです。
エアドロップは、一見シンプルです。プロジェクトが無料のトークンを一群のウォレットアドレスに配布します。時には過去の使用に基づいています。時には特定の資産を保持していることに基づいています。時にはランダムです。この言葉自体は軍事物流から借用されていますが、暗号の世界では何か柔らかいもの、つまり贈り物を示します。

Token Allocation
Hey @Fabric Foundation , a 30% community share for $ROBO is incredibly generous! 👏👏👏
It's great to see such a strong focus on rewarding the ecosystem. ✅️🆒️

Vesting
The 12-month cliff for investor and team allocations significantly enhances the project's credibility and demonstrates long-term commitment.

A team willing to wait a full year for their reward shows that they really believe in the project and aren't just looking for quick cash.
#Robo ​#Robotics ​#MachineEconomy #TOKENOMICS

For the serious investors on Binance Square, understanding the Fabric Protocol ($ROBO) supply dynamics is key to navigating the current price action. With the TGE (Token Generation Event) happening now, here is the official breakdown:
​⚙️ The Numbers
​Total Supply: 10,000,000,000 $ROBO (10 Billion)
​Initial Circulating Supply: ~2,231,000,000 $ROBO (approx. 22.3%)
​Public Sale Price: ~$0.04 (via Kaito Capital)
​FDV (Fully Diluted Valuation): ~$400 Million
​📦 Token Allocation & Vesting
​The Fabric Foundation has designed a long-term release schedule to prevent massive sell pressure:
​Ecosystem & Community (29.7%): Dedicated to "Proof of Robotic Work" incentives and community growth.
​Investors (24.3%): 1-year cliff followed by 36-month linear vesting.
​Foundation Reserve (18.0%): Locked for long-term research and stewardship.
​Core Team: Subject to a strict 12-15 month cliff before linear release.
​💡 Core Utility: More than just a "Coin"
​$ROBO is the gas for the Robot Economy. Its utility is hard-coded into the protocol:
​Network Fees: Every robotic task, identity verification, and data exchange requires $ROBO.
​Coordination Staking: To register hardware (like the Minibot M1) on the network, operators must stake
ROBO as a "Work Bond" to ensure performance.
​Governance: Holders vote on fee structures and hardware standards for the global fleet.
​Analyst Note: While the initial unlock at TGE provides liquidity, over 75% of the supply is locked in long-term vesting. This suggests the team is betting on a multi-year adoption curve rather than a short-term pump.
​Are you watching the ROBO/USDT pair on KuCoin and Bybit today? The volatility is high! 📉📈
​#Tokenomics #FabricProtocol #CryptoAnalysis #DePIN #Web3Robotics

3 AM. reading through MIRA's verification flow for the fourth time. and honestly? kept getting stuck on the same question nobody seems to want to answer 😂

if MIRA verifies an AI output and that output is still wrong, what actually happens to the person who trusted the label?

what bugs me:

verification flow is technicaly sound. AI generates output, MIRA breaks it into atomic claims, nodes vote, supermajority consensus reached, cryptographic proof logged on Base. clean process.
but consensus isn't truth. 2/3 of nodes agreeing on something wrong doesn't make it right. it makes it a verified mistake. and that's a completely different problem than what MIRA's marketing addresses.

the #tokenomics angle nobody discusses:

Mira demand is built on one assumption: verification volume drives staking demand. more AI outputs verified, more nodes needed, more Mira staked, price supported.

but here's what that model quietly requires. enterprises and agents using MIRA need to believe the verified label carries real liability weight. if it doesn't, they route verification off-chain or skip it entirely for cost reasons.

allocation breakdown matters here. ecosystem and community hold significant share, unlock pressure building. token demand needs to outpace supply increase. that only happens if verification becomes genuinely sticky, meaning users trust the label enough to pay for it repeatedly.
if the liability gap stays unresolved, stickiness stays theoretical. no enterprise pays for a certificate that protects nobody.

my concern though:

the mechanism of harm is specific. user receives MIRA-verified output. trusts it because of the label. acts on it. output was wrong but achieved supermajority consensus among nodes running different LLMs with different training data. nobody is legally responsible. smart contract logged the proof. proof just proves consensus happened, not that consensus was correct.
that gap between verification certificate and truth certificate is where the real risk lives. and right now nothing in MIRA's design closes it.

what they get right:

atomic claims decomposition is genuinely underrated. breaking holistic AI output into individual verifiable facts forces a granularity most systems avoid. subjective framing cant hide inside an atomic claim the way it hides inside a paragraph. each statement either survives node scrutiny or it doesnt.
diverse LLM architecture across nodes is smart security thinking. different model families, different training data, different failure modes. coordinated hallucination becomes statistically unlikely when your verifier pool uses GPT, Claude, Grok and Llama simultaneously. one model's blind spot gets caught by another's strength.
Klok copilot integration is real traction, not vaporware. billions of tokens processed daily means the infrastructure handles genuine load. KGeN and Phala partnerships extend reach into gaming and secure compute, two verticals where AI verification actually matters. Chainlink built economic security for price data. MIRA applying same model to AI truth is logical progression, not imitation.

what worries me:
dual reading on the atomic claims approach.
positive: forces precision, eliminates vague outputs, catches hallucinations at the claim level before they compound into wrong decisions.
negative: complex AI reasoning isn't always decomposable into clean atomic facts. nuanced analysis, probabilistic statements, contextual judgements — these resist atomization. if MIRA can only verify the simple stuff, enterprises route complex queries elsewhere and Mira demand concentrates in low-value verification.
which reading matters more depends entirely on how sophisticated the decomposition engine actually is. and that detail isnt public yet.

honestly don't know if MIRA becomes essential infrastructure every AI application needs or a technically impressive system solving a liability problem nobody has legally defined yet.
watching enterprise adoption and whether any major AI platform integrates MIRA for something beyond copilot use cases.
what's your take - verification layer the internet needs or solution looking for a problem with legal teeth?? 🤔

#Mira @Mira - Trust Layer of AI $MIRA

説明
暗号におけるトークノミクスの意味を最も簡単な方法で学びましょう。投資する前に、シンプルな物語の例を使って供給、需要、バーン、インフレーションを理解します。
導入
小さな町にある二つの玩具店を想像してください。
ショップAは毎日無限の玩具を印刷します。
ショップBは特別な玩具を100個だけ作り、二度とそれ以上は作りません。
しばらくすると、どの玩具がより価値が高くなりますか？
限られたもの。
このシンプルな物語はトークノミクスを説明します。
トークノミクスを理解していれば、なぜ一部の暗号通貨が強く成長し、他のものが失敗するのか理解できます。

数週間にわたってMIRAを無視してきた。ようやくノード経済をマッピングした。そして正直なところ？中央集権の問題は、ほとんどの人が見ているところではない 🤭
誰もが「検証は分散型ですか？」と尋ねる。間違った質問。より良い質問は：実際にノードを運営する余裕があるのは誰か。
私が気に障ること：
検証するためには、Miraをステークし、AI推論を実行する。オープンに聞こえる。しかし、LLM推論にはGPUハードウェア、稼働時間、スラッシングを生き延びるための十分なステークが必要。このことが、最初の投票が行われる前に小規模オペレーターを静かに排除する。
構造は分散型。実践では集中型。