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🗓 Time: 10 – 15/09/2025

👉 Join now: https://x.com/Jucom_VN/status/1965610867481014466

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In the old playbook of capital markets, fundraising and underwriting have always been a game for the few. At center stage are investment banks and major institutions, deciding who gets on stage and who secures the funding. Retail investors and communities could only wait in the dim corners of the secondary market, left to hold the bag. But in the world of Web3, the plot is being rewritten.

I. The Old Playbook of Capital Markets: A Missing Community

• When a listed company needs capital, the first step is often to approach an investment bank, negotiate a discounted placement or a private offering.
• The capital only circulates among institutions, while ordinary investors and communities can only wait passively, entering at the secondary market.
• Even worse, due to a lack of buy-side support, stock prices often come under pressure after fundraising, further diminishing market confidence.

II. The Potential of Community: From Voice to Momentum

• KOLs can guide investment directions;
• Community leaders can pool scattered small funds into collective strength;
• If this energy has a compliant, safe, and transparent mechanism for channeling it, it can become a new source of liquidity for financial markets.

III. The Emergence of XBrokers: Mechanism Innovation Led by Ju.com

1. Directed Equity Subscription Zone (Early-Bird Subscription)Listed companies can launch fundraising here, not only for institutions but also open to ordinary investors who have completed KYC.Investors participate via “blind box subscription,” enjoying the benefits of discounted allocations.Recommendations by community leaders and KOLs are directly converted into purchase orders.
2. 1:1 Real Stock Trading ZoneInvestors acquire real stocks, not token representations.Ju.com partners with licensed brokers to ensure compliant custody and trading of securities.This significantly boosts investor trust, and community-endorsed stocks can find steady secondary market support.
3. Stock Lending and Buyback MechanismInvestors can lend their stocks for 12 months and receive interest plus platform token $X incentives.The company must provide a reserve equal to 30% of the lending amount for $X buyback.This ensures fundraising funds are not just “hit and run,” but are transformed into long-term liquidity.

IV. The Changing Role of the Community: From Stock Recommender to Financial Participant

• KOLs: Not just recommending stocks, but truly participating in underwriting. Their influence directly drives fundraising results, and they receive corresponding incentives.
• Community members: No longer passive bag holders in the secondary market, but early shareholders able to join at a discount from the start.
• Listed companies: No longer facing institutional fundraising in isolation, but building a binding relationship with the community, enabling both capital raising and ongoing community support for market cap management.

V. Why Is This Important for Hong Kong?

1. Lower fundraising threshold: Ordinary investors can also participate in private placements, no longer locked out.
2. More sustainable liquidity: The lending + buyback mechanism ensures buy-side support doesn’t vanish quickly, making market caps more stable.
3. More compelling narrative: Hong Kong stocks are no longer just “an institutional market,” but an ecosystem that can be driven by the global community.

VI. Conclusion: A New Community-Driven Playbook for Finance

• Investment banks are no longer the sole underwriters;
• The community is no longer just a bystander;
• The Hong Kong capital market, for the first time, has a chance to reclaim its unique position in the global financial landscape through a liquidity revolution driven by the community.

For Hong Kong, this is a new way of organizing liquidity: allowing the market to regain its voice against Wall Street.

From KOL to broker, this is more than just an identity shift—it’s a rewriting of the financial narrative.Through XBrokers, Ju.com fuses community passion and KOL influence with real stock trading and compliance mechanisms, turning “voice” into real “momentum.”In this new playbook:The community is not just a spectator—it is the new financial engine. #JuCom #JuComVietnam #Kols #Broker

AI–Web3 will enter a “narrative-to-scale” inflection between 2025 and 2030: AI market spending continues to expand, data-center and energy constraints lift marginal costs, and Web3 fills a key gap for verifiable value settlement and data provenance. This Market Insights article provides a research-oriented, verifiable coordinate system and paths to deployment.

Summary: By 2030, both AI economic scale and compute consumption will expand in tandem. AI–Web3 convergence will concentrate on on-chain data rights/provenance, settleable trading of compute and models, RWA and payments, wallet-enabled agents, and privacy- and compliance-preserving computation. Core challenges are energy, liquidity, and regulatory alignment.

🔸 What Is AI–Web3?

AI–Web3 is the coupling of AI production factors (data, compute, models/apps) with on-chain primitives (identity, assets, settlement, governance): rights–measurement–settlement–governance occur on-chain, while training/inference–distribution–service occur off-chain. As AI moves to “scaled supply,” AI–Web3 makes value flows and accountability chains verifiable, auditable, and revenue-sharing by design.

🔻 Why Talk About AI–Web3 Now?

Three sets of data anchor “now → 2030” clearly:

• PwC estimates AI could add $15.7 trillion to the global economy by 2030 (+14% of GDP).
• McKinsey estimates generative AI could create $2.6–4.4 trillion in additional annual value.
• IEA projects data-center electricity use will roughly double to ~945 TWh by 2030, with AI as a key driver.

Hence AI–Web3 is necessary engineering to convert value and energy constraints into settleable and governable structures.

🔸 Market Size and Drivers

AI demand is not only “model upgrades” but “industry embedding.” IDC projects AI spending to reach $632 billion by 2028 (2024 guide); IDC also assesses the cumulative economic impact of AI investments could reach $22.3 trillion by 2030 (cumulative methodology). On the supply side, the IEA baseline flags an “electricity red line” with data-center power use doubling by 2030—implying compute cost, green power, and transmission bottlenecks will be first-order constraints for AI–Web3.

🔻 2023–2025 outbreak drivers:

• Capital–compute spiral: model scale, inference load, and capex reinforce each other (capex → compute → application returns). McKinsey’s value range explains broadening enterprise use cases.
• Supply constraints surfaced: IEA’s power curve and localized grid tightness make “low-carbon, near-source” supply more scarce.
• Verifiability demand rises: proliferation of AI outputs, IP/privacy concerns, and provenance push “proof of source” and “licensed settlement” toward standardization—precisely AI–Web3’s entry point.

🔸 Key Inflection: Energy, Compute, and Pricing

🔻 Energy curve rises

Global data-center electricity use may reach ~945 TWh by 2030; AI-optimized data centers could quadruple consumption, pressing grid and efficiency limits. AI–Web3 projects must treat “carbon/electricity” as settlement and governance parameters.

🔻 Commoditization of compute

Compute time slices, VRAM, and bandwidth will be standardized and listed; pricing will evolve from “raw compute” to multi-factor contracts that include energy/SLA/geo.

🔻 “Financialization” of data and models

Data licenses, fine-tuning incremental value, and inference quotas will be split into transferable claims, with AI-driven revenue sharing and buybacks.

🔸 Five AI–Web3 Convergence Points

🔻 On-chain provenance, rights, and revenue sharing for data

AI training and inference span multi-source data. On-chain proofs of origin and license credentials can fix “who provided/used what” to the ledger and automate revenue sharing by call volume—reducing infringement costs and legal uncertainty (consistent with McKinsey’s enterprise-value framing).

🔻 Settled markets for compute and inference quotas

Given IEA’s energy red line, compute should price by electricity cost, carbon intensity, and time of day. AI–composable settlement can package compute hours, VRAM, and bandwidth into tradable claims, with on-chain verification of delivery and reconciliation.

🔻 RWA 2.0: tokenizing from assets to “machine outputs”

Citi projects $4–5 trillion of tokenized assets by 2030, led by bonds/real estate. With AI, “model weight versions, inference quotas, data licenses” become new “output rights,” returning cash flows via licenses or buybacks as usage accrues.

🔻 Wallet-enabled AI agents and automated settlement

As enterprises hand workflows to AI agents, contracts and wallets define executable boundaries: budget ceilings, license scopes, and audit trails enforced on-chain reduce “uncontrolled calls.” This default “machine-to-machine” micro-payments + authorization pattern is native to AI–Web3.

🔻 Privacy computing and compliance routing

Across domains and jurisdictions, AI–Web3 must engineer tradeoffs between MPC/TEE/ZK and compliance routing (geo/sector allowlists): encode “usability + legality” into settlement parameters to create usable, compliant infrastructure.

🔸 Impact on the Crypto Industry

• Trading and clearing: AI brings metered B2B/B2C inference transactions on-chain, increasing automation and auditability.
• Assets and collateral: data-license fees and inference cash flows can be securitized as collateral, expanding on-chain collateral sets (aligned with Citi’s RWA scale).
• Market-making and risk: new derivatives (compute/inference futures, data-license forwards) create new MM pools; energy data becomes a risk factor.
• Compliance and custody: enterprises will demand “whitelisted chains + compliant routing + audit reports,” upgrading compliant infra and custodial services.
• L1s and L2s: high-frequency, small-value AI settlement favors low-fee, high-throughput networks; expect purpose-built chains/L2s with data/compute as native assets.

🔸 Authoritative Figures Cited

• $15.7 trillion AI contribution to global economy by 2030 (PwC)
• $2.6–4.4 trillion annual value from generative AI (McKinsey)
• Global AI spending to reach $632 billion in 2028 (IDC latest spending guide)
• Data-center electricity to double to ~945 TWh by 2030 (IEA baseline)
• $4–5 trillion in tokenized assets by 2030 (Citi GPS)

🔸 FAQ

▫️ What mainly determines AI’s growth? A: Three things: renewable availability and electricity price curves; maturity of compliant interfaces for data and models; and the share of enterprise workflows that are “machine-executable” (whether budgets/permissions are written into on-chain wallets).

▫️ Where do RWA and AI intersect? A: First, the on-chain availability of traditional assets (Citi’s $4–5T provides base collateral). Second, tokenized cash-flow claims on “machine outputs,” mapping usage-derived returns into on-chain revenue shares.

Why do enterprises need on-chain settlement instead of traditional API billing? A: AI’s edge is automated settlement + auditable revenue sharing. When use cases span organizations and geographies, on-chain credentials and auto-sharing cut reconciliation and legal friction.

Will energy and carbon become pricing factors? A: Yes. The IEA’s 2030 power curve implies “carbon/electric intensity” will be priced in; AI–Web3 contracts will encode SLA + energy jointly as settlement parameters.

When researching an AI–Web3 project, what’s primary? A: Three checks: real usage (not just TVL); verifiable provenance/licensing with a clear revenue-share path; and whether energy/compliance parameters are embedded in contracts and reports.

🔸 Key Takeaways

• By 2030, AI’s economy and energy use expand together; the IEA power curve anchors supply-side constraints, pushing AI to add “settleable and governable” layers.
• PwC/IDC/McKinsey provide a value/spending coordinate system: macro value, IT spend, and enterprise use cases advance in parallel.
• Five convergence points (provenance & revenue-share, compute settlement, RWA, agent wallets, privacy & compliance) will define AI–Web3’s moat.
• Industry opportunities lie in settlement & contractization, market-making & hedging, compliant custody & audit, and low-carbon supply.
• Key risks: energy costs, regulatory synchrony, and fragmented liquidity—necessitating “whitelisted infra + trusted credentials + unified reconciliation.”

#JuCom #JuComVietnam #JuCoin #cryptocurrency

Bucket provides collateralized debt positions (CDPs) and fixed-cost borrowing on Sui. Users can mint the BUCK stablecoin by collateralizing assets such as SUI, LSTs, and ETH. The protocol stabilizes the peg via PSM, redemption, and the Tank mechanism, and benefits from the rollout of native stablecoins on Sui. This Token Insights piece systematically analyzes its positioning, core mechanisms, the BUT token, and ecosystem roadmap.

Summary: Bucket is a major CDP protocol on Sui: post collateral → borrow BUCK with predictable fees; maintain the peg using PSM/redemptions/Tank; BUT is used for governance/incentives; the ecosystem is growing alongside Sui’s native stablecoin expansion.

🟠 What is Bucket?

Bucket calls itself a “decentralized stablecoin protocol.” Users deposit collateral into the contract to open CDPs and mint BUCK, a USD-pegged stablecoin. The project emphasizes “fixed (or predictable) borrowing costs” to reduce funding uncertainty. Official docs state BUCK is over-collateralized and supports multiple collateral types (SUI, SUI LSTs, ETH, etc.).

🟠 Why on Sui?

In 2024, Sui onboarded native stablecoins (USDC, AUSD, FDUSD, USDY), significantly improving DeFi capital efficiency. Its Move object model plus parallel execution allow collateralization and liquidations to be processed concurrently with low latency—well-suited to Bucket’s high-frequency settlement needs.

🔻 Architecture and Mechanisms: BUCK’s “Three-Pronged” Peg

🟠 PSM: 1:1 Channels with USDC/USDT

The PSM maintains its own vault with a minimum collateral ratio of 100%, enabling direct 1:1 swaps between BUCK and USDC/USDT (PSM in fee 0%, PSM out 0.3%), which quickly pulls price back to $1 during deviations.

🟠 Redemptions: Face-Value Swap for Collateral, Prioritizing Low-CR Vaults

BUCK holders can redeem at face value for any whitelisted collateral. The system reduces debt from vaults in ascending order of collateralization ratio, protecting overall solvency (exceptions include TCR < 110% or redemptions disabled within 14 days of deployment, both codified in rules).

🟠 Tank and Liquidations: Settling Debt with BUCK to Receive Collateral

When a vault is liquidated, the Tank repays debt by burning BUCK and receives collateral in return, allowing participants to acquire collateral at a discount. This sustains system solvency and reinforces the peg. Sui’s ecosystem directory lists PSM/CDP/Tank/Redeem as a coordinated “stability combo,” enabling developers to integrate them modularly.

🟠 Technical Notes: Why Bucket Fits Sui

Sui’s object model and parallel execution let independent transactions confirm simultaneously, reducing congestion risk during redemptions and liquidations. Bucket’s modules align with Move’s object-centric design (collateral, vaults, PSM vaults are all objects), recording “who holds what and when” more directly.

🟠 Fixed Cost and Product Form

The website and socials repeatedly stress “fixed rate/predictable cost,” designing leverage and compounding paths for users “long SUI and BTC/ETH,” reducing interest-rate volatility in position management. With native Sui stablecoins live, BUCK–USDC/FDUSD/USDY trading/settlement routes are smoother, offering a practical “USD base” for collateralized borrowing and cross-protocol liquidity.

🟠 Token and Economic Model: BUCK vs. BUT

• BUCK: Bucket’s USD-pegged stablecoin.
• BUT: The protocol token used for governance, incentives, and ecosystem distribution (with a deBUT locking model). The terminology page clearly distinguishes their roles and data scopes.

🟠 BUT Supply and Circulation

The official BUT overview and dashboards show: total supply 1 billion; circulating ~395 million (time-varying), plus cumulative slashing and staking/unlock metrics. Some third-party trackers list a public sale window and size in 2025-01. Official sources and reputable aggregators prevail.

🟠 deBUT: Updated Locking and Incentive Model

In an Aug 2025 Medium post, the team updated deBUT to bind long-term participants via a clearer lock–weight–incentive relationship, aiming to “make the system friendlier to long-term supporters.”

🟠 Ecosystem Position and Data Corroboration

Stablecoin Indicators

Aggregator dashboards show BUCK market cap around $69.66 million, along with issuance/redemption flows, reflecting Bucket’s share in Sui’s stablecoin track. Price-tracker pages also show BUCK trading tightly around $1 over the past 24 hours.

🟠 Official Milestones

The team’s retrospectives note that after launch, Bucket entered Sui’s top-10 protocols with TVL climbing to about $38 million (historical reading; current TVL should follow real-time dashboards/official disclosures).

🟠 Multi-Collateral and Front-End Tools

Ecosystem directories and wallet/aggregator pages indicate Bucket supports SUI, LSTs, ETH, BTC, and other collateral types, and offers a Swap SDK so front ends can serve as stable exchange gateways.

Some public dashboards have yet to standardize protocol-level TVL for Bucket, but BUCK market cap, trading pairs, and mechanism modules cross-validate its activity and importance in Sui DeFi.

🟠 Recent Progress and Timeline

Mechanism hardening: completed PSM/redemption/Tank docs and parameters; clarified fees and thresholds.

Asset expansion/activities: socials announced acceptance of certain LP tokens as collateral and ecosystem campaigns, improving composability and reach.

BUT data pages: launched BUT overview and staking stats, revealing total supply, circulation, and deBUT metrics.

🟠 Future Plans

1. Stablecoin depth: continue “strong peg” via PSM × redemptions; broaden BUCK–USDC/FDUSD/USDY accessibility across primary and secondary markets.

2. Collateral spectrum: expand LST/LP/blue-chip collateral under a risk framework, with finer-grained liquidation parameters.

3. Token and governance: lengthen the “lock–weight–revenue share” design around BUT/deBUT to increase market-making and risk participation. The above projections align with official direction.

🟠 FAQ

🟧 How are borrowing costs made predictable? By exposing fixed/predictable rates and clear parameters, users can estimate carry at vault creation, reducing uncertainty from “usage-driven rate spikes.”

🟧 Why does BUCK trade close to $1? Through the 1:1 PSM channel, face-value redemptions, and Tank-backed liquidations, creating arbitrage and mean-reversion forces when price deviates.

🟧 What’s BUCK’s relationship with Sui’s native stablecoins? In 2024, Sui onboarded USDC, AUSD, FDUSD, and USDY, giving Bucket smoother pegs, market-making, and settlement environments.

🟧 What’s the difference between BUT and BUCK? BUCK is the stablecoin users mint and use; BUT is the protocol token for governance and incentives (including the deBUT locking model).

🟧 Is there an authoritative TVL figure now? Historically, Bucket entered Sui’s top-10 with TVL ≈ $38m; real-time scale should follow official and reputable dashboards, while BUCK market cap and depth serve as indirect evidence.

🟠 Key Takeaways

Bucket: a Sui-based CDP protocol supporting multi-asset collateral and fixed-cost BUCK borrowing.

Peg toolkit: PSM (1:1 USDC/USDT) + redemptions + Tank jointly maintain $1.

BUT/deBUT: 1B total supply, circulating and staking data displayed; governance/incentives are iterating.

Ecosystem fit: Sui’s native stables, parallel execution, and object model reduce congestion and liquidation friction.

Data corroboration: BUCK market cap ~ $69.66m and multi-collateral whitelist highlight Bucket’s importance in Sui’s stablecoin track.

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🔹 Since 2013, Ju.Com has been serving the global community with spot trading, derivatives, copy trading, staking, ETFs and Launchpad, with over 300 collaborative projects across AI, DePIN, DeFi and RWA.❤️

Meet Ju.Com at TOKEN2049 Singapore this month.

👉 Details: https://x.com/token2049/status/1965751058774606100

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↗️ Test your prediction skills every week! Predict the closing price of #JU, leave a comment below 👇.

💰 Top 10 people who predict closest to the closing price at 11:00 AM (UTC+7), September 16, 2025 will share 50 USDT!

⏳ Time: September 10, 2025 – September 17, 2025

📢 How to participate:

1️⃣ Join https://t.me/Jucom_Vietnam/103553, post a prediction with the syntax "#JUPriceGuess + price" and send it to the Telegram group. Example: #JUPriceGuess $23.33

2️⃣ Make sure the prediction is submitted before 11:00 AM (UTC+7), 16/09/2025

3️⃣ Each person can only participate once, no editing is allowed. If multiple people predict the same price, the reward will go to the first submitter.

🛫 Join us every week and seize the chance to win!

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