llm

模型上下文协议（MCP）简介
模型上下文协议（MCP）作为一种专用网关，允许人工智能系统访问实时信息并与外部数据源交互，同时维护安全边界。
这种能力将人工智能从仅限于训练数据的封闭系统转变为能够检索当前信息并执行操作的动态助手，随着人工智能系统融入各行业的关键基础设施，这些协议的安全性和可靠性已成为至关重要的考量因素。
基于 Web 的 MCP 服务中的安全漏洞
传统的 MCP 实现以 Web 服务的形式运行，这造成了一个根本性的安全漏洞，当 MCP 作为传统的 Web 服务运行时，整个安全模型都依赖于对服务提供商的信任。
服务提供商可以在用户不知情或未经用户同意的情况下修改底层代码、更改行为或更新服务，这就造成了一种固有的漏洞，即系统的完整性完全依赖于 MCP 提供商的可信度。
这种漏洞在高风险领域尤其令人担忧，在金融应用中，被攻破的支付控制平台（MCP）可能导致未经授权的交易或机密信息泄露，在医疗保健领域，则可能导致患者数据泄露。
根本问题在于，用户无法获得关于支付控制平台行为的任何加密保证 - 他们只能信任支付服务商关于安全性和数据处理的承诺。
此外，这些服务存在单点故障，容易受到复杂的攻击，服务提供商面临着来自内部不法员工的威胁、来自外部恶意行为者的压力，以及可能损害用户安全或隐私的监管要求。
使用传统的 MCP 时，用户对这些变更的可见性有限，且缺乏技术保障措施。
ICP 容器：实现可验证的 MCP 范式
互联网计算机协议（ICP）通过其容器架构提供了一种革命性的解决方案，实现了我们称之为“可验证 MCP” 的功能 - 这是人工智能安全领域的一种新范式。
与传统的 Web 服务不同，ICP 容器在去中心化网络中运行，采用基于共识的执行和验证机制，从而创造了强大的安全特性：
密码学上可验证的不可篡改性保证可防止静默代码修改确定性执行环境允许网络参与者进行独立验证在共识验证下运行，能够读写网络数据通过链上认证控制链下可信执行环境（TEE）服务器
这些能力为可信赖的 AI 上下文协议奠定了基础，无需盲目信任服务提供商。
可验证 MCP 集成的技术架构
可验证的 MCP 架构将 MCP 服务逻辑置于在共识验证下运行的 ICP 容器中，这创建了多个不同的层协同工作以确保安全性：
接口层：AI 模型通过与现有集成模式兼容的标准化 API 进行连接。验证层：ICP 容器验证身份验证、检查权限，并在共识验证的环境中验证策略遵守情况。编排层：容器协调数据检索或计算所需的必要资源。证明层：对于敏感操作，容器部署并证明 TEE 实例，提供加密证明，证明正确的代码在安全的环境中运行。响应验证层：在返回结果之前，加密验证可确保数据的完整性和来源。
该架构创建了一个透明、可验证的管道，通过共识机制和加密验证来保证组件行为，从而无需信任服务提供商的声明。
示例：通过可验证的 MCP 确保财务数据访问安全
设想一个金融咨询人工智能需要访问银行数据和投资组合才能提供建议，在可验证的 MCP 实现中：
AI 通过可验证 MCP 接口提交数据请求ICP 容器使用不可变的访问控制逻辑来验证授权对于敏感数据，容器会部署一个带有隐私保护代码的 TEE 实例该容器通过加密方式验证 TEE 是否运行正确的代码金融服务机构直接向经过验证的 TEE 提供加密数据TEE 仅返回经过加密证明的正确执行的授权结果该容器向人工智能提供经过验证的信息
这确保即使是服务提供商也无法访问原始财务数据，同时保持完全可审计性，用户可以精确验证哪些代码处理了他们的信息以及提取了哪些洞察，从而使人工智能应用能够在受监管领域得以实施，而传统方法在这些领域风险过高。
对人工智能可信度和数据主权的影响
可验证的 MCP 范式通过将信任模型从“信任提供者”转变为加密验证，从而改变了人工智能系统的信任模型，这解决了人工智能在敏感领域应用的关键障碍，在这些领域，数据处理的保障至关重要。
为了确保人工智能的可信度，这可以实现对数据访问模式的透明审计，防止对处理逻辑的静默修改，并提供数据来源的加密证明，用户可以准确验证人工智能系统访问了哪些信息以及这些信息是如何处理的。
从数据主权角度来看，用户通过加密保障而非政策承诺来获得控制权，组织机构实施无法绕过的权限，而监管机构可以验证处理敏感信息的不可篡改代码，对于跨境场景，可验证的 MCP 通过加密强制执行的数据边界，在满足数据本地化要求的同时，维持全球 AI 服务能力。
结论
可验证的 MCP 范式代表了人工智能系统外部交互安全性的一项突破，它利用 ICP 容器的不可篡改性和验证能力，解决了传统 MCP 实现中的根本性漏洞。
随着人工智能在受监管领域的应用日益广泛，这种架构为可信赖的模型与现实世界交互奠定了基础，无需盲目信任服务提供商，该方法在保持强大安全保障的同时，也为敏感领域的新型人工智能应用提供了可能。
这项创新有望普及安全上下文协议，为即使在最关键的安全环境中负责任地部署人工智能铺平道路。

#mcp #AI #ICP生态 #LLM

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News：
1. Bitwise 推出首个美国 Solana 现货 Staking ETF
Bitwise 在 SEC 暂停期间，于 2025 年 10 月 28 日启动了 Solana Staking ETF（BSOL），不需要 SEC 逐项批准。上市首周就吸引了约 4.2 亿美元资金。这推动了竞争对手（如 Grayscale、VanEck 等）也加紧申请类似 ETF。这标志着加密 “altcoin ETF”（不仅仅是 BTC / ETH）的加速常规化。
2. Solana ETF 持续资金流入
两只 Solana ETF（BSOL 和 Grayscale 的 GSOL）已连续 12 天净流入。这显示出投资者对 Solana 生态的强烈兴趣，以及对 altcoin ETF 的信心。
3. SEC 简化加密 ETF 上市标准
美国 SEC 批准了新的通用上市标准，允许更多加密 ETF（包括多种货币）更快上线。这一变革大幅降低了加密资产 ETF 上市的门槛，未来可能看到更多种类的加密 ETF 产品：不仅限于比特币/以太坊。
4. Canary Capital 推出 LTC 和 Hedera ETF
Canary Capital 不顾 SEC 暂停，推出首批与 Litecoin 和 Hedera 现货价格挂钩的 ETF。这一行动同样利用了 SEC 新的通用标准，反映出机构对更多加密资产 ETF 的大胆部署。
5. 英国 ClearToken 获 FCA 批准启动加密结算平台
ClearToken 得到英国金融行为监管局 (FCA) 批准，可推出受监管的数字资产结算系统。英国进一步将区块链基础设施和数字资产纳入正规金融系统，有利于 Web3 与传统金融的融合。
6. 区块链 / Web3 安全：软件供应链威胁上升
安全公司 SlowMist 发布报告称，2025 年上半年链上项目面临越来越复杂的攻击威胁。与此同时，有研究指出 Web3 软件供应链中开源依赖暴露出重大安全风险。风险提示：随着 Web3 项目增多，底层合约 bug、第三方库攻击成为更重要的问题。
7. Web3 智能合约安全研究进展
新论文提出一种基于 LLM（大语言模型）的智能合约漏洞管理框架 (LLM-BSCVM)，提升漏洞检测 +修复效率。另有研究聚焦合约升级 (upgrade) 过程中的安全风险，指出合约升级可能引入新的脆弱性。
#solana #etf #ClearToken #LLM #软件供应链风险

Few projects have drawn community attention as rapidly as Perceptron Network( previously #blockmesh ) , despite the decentralized AI ecosystem's rapid evolution.  After a significant merger, BlockMesh, a massive decentralized data node system, has evolved into Perceptron, a potent AI data infrastructure network with more than 700,000 legacy nodes and an expanding army of data contributors, agents, and annotators.

"When is the Perceptron airdrop?" is the most frequently asked question on Crypto Twitter as the excitement builds.                                                                       
Let's examine why Perceptron is emerging as a leading player in the AI + DePIN race and why its airdrop might present one of the year's most significantopportunities.
💎 What is a Perceptron Network?

Three layers are being combined by Perceptron to create a completely decentralized data pipeline for AI:

1) Nodes: The Foundation of Data

These nodes gather both structured and unstructured data from documents, web pages, APIs, and in-person interactions.  This is the BlockMesh node network's improved evolution.

2) Agents: The Layer of Interaction

On platforms like Discord, Telegram, and WeChat, both human-guided and AI-driven agents analyze, classify, and label data.

3) The Incentive Engine: The Trust & Reward System

To encourage high-quality participation, Perceptron employs NFTs, contribution scores, and token-based incentives.

These layers work together to form an end-to-end decentralized data engine that can supply future AI applications, LLMs, and machine learning models.

💎 From BlockMesh to Perceptron: A Significant Improvement

BlockMesh formally merged with Perceptron in the middle of 2025.
This was a complete ecosystem expansion rather than just a rebrand:

✔ Perceptron now includes BlockMesh's 700K+ nodes
✔ Legacy contributors maintain their participation points
✔ A new reward model is being implemented ✔ Previous BlockMesh users are now eligible for the airdrop ✔ Key metrics now include data-mining, solving cryptographic challenges, and node activity.

With this change, Perceptron is now positioned as one of Web3's biggest decentralized AI data networks.
💎 The Reasons Everyone Is Discussing the Airdrop
1. A Huge User Base Is Already Qualified

Reward snapshots will include contributions from BlockMesh, node operators, extension users, and Perceptron miners.

2. Multi-Layer Rewards = Multi-Layer Participation

Different kinds of contributions are rewarded by Perceptron:

Uptime of nodes
Quality of data
Solving cryptographic challenges
Agent/annotation duties
Extended participation

This implies a greater chance of earning and more ways to qualify.

🔥 3. The AI + DePIN Story Is Taking Off

One of the most popular areas for 2025 is decentralized physical infrastructure combined with AI training.
The perceptron is ideally situated at that intersection.

🔥 4. The Network Is Not Complete

Perceptron is still in its early stages of growth, despite having hundreds of thousands of legacy users. Stronger airdrop allocations are usually the result of early adoption in networks such as these.

💎Why Perceptron May Present a Significant Prospect

Perceptron isn't your typical DePIN project.
It offers three important benefits:

1)Current scale (more than 700K nodes)
2) Perceptron begins with massive distribution, whereas most projects begin at zero.
3) Actual use: information for AI models
Massive volumes of structured data are required for AI.
The infrastructure to supply it decentralized is being built by Perceptron.

A robust incentive structure

A scalable ecosystem is produced by rewarding both human and machine contributions.

With its own distinct approach—AI-grade data collection and refinement—Perceptron joins Render, Bittensor, Akash, and Grass in the same growth lane.
IS THERE STILL OPPORTUNITY?
Yes! Do install perceptron extension and app ..keep mining data and you will be rewarded in future seasons.
💎 Final Thoughts: Decentralized AI Airdrop Season

Decentralized AI data is the cornerstone if artificial intelligence is the way of the future.
With the impending airdrop, Perceptron is further solidifying its position as one of the most significant data engines in space.

Perceptron has one of the best stories in the current cycle, regardless of whether you're a BlockMesh pioneer, a novice miner, or a passive Web3 user looking for opportunities.

Register.  Continue to be active.  This could be a significant airdrop.

#AI #DePIN #DataEconomy #LLM
#DecentralizedAI #PerceptronNetwork

I’ve been thinking a lot about what it means to build money and identity for machines, and Kite feels like one of those rare projects that tries to meet that question head-on by redesigning the rails rather than forcing agents to squeeze into human-first systems, and that’s why I’m writing this in one continuous breath — to try and match the feeling of an agentic flow where identity, rules, and value move together without needless friction. $KITE is, at its core, an #EVM -compatible Layer-1 purpose-built for agentic payments and real-time coordination between autonomous #AI actors, which means they kept compatibility with existing tooling in mind while inventing new primitives that matter for machines, not just people, and that design choice lets developers reuse what they know while giving agents first-class features they actually need. They built a three-layer identity model that I’ve noticed shows up again and again in their docs and whitepaper because it solves a deceptively hard problem: wallets aren’t good enough when an AI needs to act independently but under a human’s authority, so Kite separates root user identity (the human or organizational authority), agent identity (a delegatable, deterministic address that represents the autonomous actor), and session identity (an ephemeral key for specific short-lived tasks), and that separation changes everything about how you think about risk, delegation, and revocation in practice. In practical terms that means if you’re building an agent that orders groceries, that agent can have its own on-chain address and programmable spending rules tied cryptographically to the user without exposing the user’s main keys, and if something goes sideways you can yank a session key or change agent permissions without destroying the user’s broader on-chain identity — I’m telling you, it’s the kind of operational safety we take for granted in human services but haven’t had for machine actors until now. The founders didn’t stop at identity; they explain a SPACE framework in their whitepaper — stablecoin-native settlement, programmable constraints, agent-first authentication and so on — because when agents make microtransactions for #API calls, compute or data the unit economics have to make sense and the settlement layer needs predictable, sub-cent fees so tiny, high-frequency payments are actually viable, and Kite’s choice to optimize for stablecoin settlement and low latency directly addresses that.
We’re seeing several technical choices that really shape what Kite can and can’t do: EVM compatibility gives the ecosystem an enormous leg up because Solidity devs and existing libraries immediately become usable, but $KITE layers on deterministic agent address derivation (they use hierarchical derivation like #BIP -32 in their agent passport idea), ephemeral session keys, and modules for curated AI services so the chain is not just a ledger but a coordination fabric for agents and the services they call. Those are deliberate tradeoffs — take the choice to remain EVM-compatible: it means Kite inherits both the tooling benefits and some of the legacy constraints of #EVM design, so while it’s faster to build on, the team has to do more work in areas like concurrency, gas predictability, and replay safety to make micro-payments seamless for agents. If it becomes a real backbone for the agentic economy, those engineering gaps will be the day-to-day challenges for the network’s dev squads. On the consensus front they’ve aligned incentives around Proof-of-Stake, module owners, validators and delegators all participating in securing the chain and in operating the modular service layers, and $KITE — the native token — is designed to be both the fuel for payments and the coordination token for staking and governance, with staged utility that begins by enabling ecosystem participation and micropayments and later unfolds into staking, governance votes, fee functions and revenue sharing models.
Let me explain how it actually works, step by step, because the order matters: you start with a human or organization creating a root identity; from that root the system deterministically derives agent identities that are bound cryptographically to the root but operate with delegated authority, then when an agent needs to act it can spin up a session identity or key that is ephemeral and scoped to a task so the risk surface is minimized; those agents hold funds or stablecoins and make tiny payments for services — an #LLM call, a data query, or compute cycles — all settled on the Kite L1 with predictable fees and finality; service modules registered on the network expose APIs and price feeds so agents can discover and pay for capabilities directly, and protocol-level incentives return a portion of fees to validators, module owners, and stakers to align supply and demand. That sequence — root → agent → session → service call → settlement → reward distribution — is the narrative I’m seeing throughout their documentation, and it’s important because it maps how trust and money move when autonomous actors run around the internet doing useful things.
Why was this built? If you step back you see two core, very human problems: one, existing blockchains are human-centric — wallets equal identity, and that model breaks down when you let software act autonomously on your behalf; two, machine-to-machine economic activity can’t survive high friction and unpredictable settlement costs, so the world needs a low-cost, deterministic payments and identity layer for agents to coordinate and transact reliably. Kite’s architecture is a direct answer to those problems, and they designed primitives like the Agent Passport and session keys not as fancy extras but as necessities for safety and auditability when agents operate at scale. I’m sympathetic to the design because they’re solving for real use cases — autonomous purchasing, delegated finance for programs, programmatic subscriptions for services — and not just for speculative token flows, so the product choices reflect operational realities rather than headline-chasing features.
When you look at the metrics that actually matter, don’t get seduced by price alone; watch on-chain agent growth (how many agent identities are being created and how many sessions they spawn), volume of micropayments denominated in stablecoins (that’s the real measure of economic activity), token staking ratios and validator decentralization (how distributed is stake and what’s the health of the validator set), module adoption rates (which services attract demand), and fee capture or revenue sharing metrics that show whether the protocol design is sustainably funding infrastructure. Those numbers matter because a high number of agent identities with negligible transaction volume could mean sandbox testing, whereas sustained micropayment volume shows production use; similarly, a highly concentrated staking distribution might secure the chain but increases centralization risk in governance — I’ve noticed projects live or die based on those dynamics more than on buzz.
Now, let’s be honest about risks and structural weaknesses without inflating them: first, agent identity and delegation introduces a new attack surface — session keys, compromised agents, or buggy automated logic can cause financial losses if revocation and monitoring aren’t robust, so Kite must invest heavily in key-rotation tooling, monitoring, and smart recovery flows; second, the emergent behavior of interacting agents could create unexpected economic loops where agents inadvertently cause price spirals or grief other agents through resource exhaustion, so economic modelling and circuit breakers are not optional, they’re required; third, being EVM-compatible is both strength and constraint — it speeds adoption but may limit certain low-level optimizations that a ground-up VM could provide for ultra-low-latency microtransactions; and fourth, network effects are everything here — the platform only becomes truly valuable when a diverse marketplace of reliable service modules exists and when real-world actors trust agents to spend on their behalf, and building that two-sided market is as much community and operations work as it is technology.
If you ask how the future might unfold, I’ve been thinking in two plausible timelines: in a slow-growth scenario Kite becomes an important niche layer, adopted by developer teams and enterprises experimenting with delegated AI automation for internal workflows, where the chain’s modularity and identity model drive steady but measured growth and the token economy supports validators and module operators without runaway speculation — adoption is incremental and centered on measurable cost savings and developer productivity gains. In that case we’re looking at real product-market fit over multiple years, with the network improving tooling for safety, analytics, and agent lifecycle management, and the ecosystem growing around a core of reliable modules for compute, data and orchestration. In a fast-adoption scenario, a few killer agent apps (think automated shopping, recurring autonomous procurement, or supply-chain agent orchestration) reach a tipping point where volume of micropayments and module interactions explode, liquidity and staking depth grow rapidly, and KITE’s governance and fee mechanisms begin to meaningfully fund public goods and security operations — that’s when you’d see network effects accelerate, but it also raises the stakes for robustness, real-time monitoring and on-chain economic safeguards because scale amplifies both value and systemic risk.
I’m careful not to oversell the timeline or outcomes — technology adoption rarely follows a straight line — but what gives me cautious optimism is that Kite’s architecture matches the problem space in ways I haven’t seen elsewhere: identity built for delegation, settlement built for microtransactions, and a token economy that tries to align builders and operators, and when you combine those elements you get a credible foundation for an agentic economy. There will be engineering surprises, governance debates and market cycles, and we’ll need thoughtful tooling for observability and safety as agents proliferate, but the basic idea — giving machines usable, auditable money and identity — is the kind of infrastructural change that matters quietly at first and then reshapes what’s possible. I’m leaving this reflection with a soft, calm note because I believe building the agentic internet is as much about humility as it is about invention: we’re inventing systems that will act on our behalf, so we owe ourselves patience, careful economics, and humane design, and if Kite and teams like it continue to center security, composability and real-world utility, we could see a future where agents amplify human capability without undermining trust, and that possibility is quietly, beautifully worth tending to.

#Binance Alpha officially launched its initial listing on July 16, 2025, following a period of astonishment. Four altcoins, #LLM , GNON, #Neur , and TRISIG, which had been on the radar of listing registration, were abruptly removed from the platform. This decision marked the first major cleanup operation since Binance Alpha's launch.
🔍What's Behind the Delisting Decision?
According to Binance's official statement, these four tokens lost their places on the Alpha platform due to reasons such as poor performance, weak project criteria, and insufficient distribution interest. While some of the detailed reasons for their delisting are not explained in the name, the overall message is clear:
👉 "We have a quality bar, and we will not forgive anyone who falls!"
🛠️ Sales and Exchanges Still Possible
Although the removed tokens are removed from the Alpha platform, there is no restriction on users holding or selling their assets. Binance also offered alternative ways to do this:
Binance can sell by following these steps:
[Assets] > [Alpha] > Select Token > Sell
Or, you can continue trading by searching for the relevant token in the [Market] section of the Binance Web3 Wallet.
🎯 What Does Binance Alpha Aim For?
This move by Binance demonstrates that the Alpha platform is designed as an "experimental listing space" and aims to prioritize quality through continuous options. This step aims to:
Evolve the platform into a structure that appeals to professional audiences,
Criticize speculative and weak systems,
And generally increase user security.
📉 Delete Issued Tokens: Is Project Closure Coming?
Here are the four tokens that have been deleted from the platform:
LLM: Although an AI-focused project, it has been lackluster in terms of volume and distribution.
GNON: The social network was an ordinary blockchain startup, and its economic activity had declined significantly.
NEUR: There was a vision to transition healthcare to blockchain, but progress reports were insufficient.
TRISIG: Multisig budget technology was developing, but updates had stalled.
While the delisting of these individuals might suggest that they could survive through over-the-counter exchanges, many investors interpreted it as the first sign of the project's demise.
🚨 Who's Next on Binance Alpha?
This development raises a major question:
"What other projects on the alpha platform might not make it past the testing phase?"
Binance Alpha's proactive approach could lead to more listings in the coming days. Projects with low trading volume, those that fail to share updates, or those that compromise user security are particularly at risk.
🧩 Result: Binance Alpha's "Elimination Period" Has Begun
Binance has positioned its Alpha platform not just as a listing platform but also as a testing laboratory. The first four projects to be delisted fell victim to this strategy. However, this long-desired move could significantly improve user experience and investment volume.
The message from Binance is clear:
"Reliability and quality are no longer just preferences; they will remain!"
#AltcoinSeasonLoading #BTC120kVs125kToday

This week, three new cryptocurrencies—#LLM , #CATG , and #Mements —are in the spotlight, introducing innovative concepts like AI, memes, and unique ideas. They could signal the rise of the next major trend: AI agents:

1️⃣ 𝐋𝐚𝐫𝐠𝐞 𝐋𝐚𝐧𝐠𝐮𝐚𝐠𝐞 𝐌𝐨𝐝𝐞𝐥 (𝐋𝐋𝐌)
➢ A #memecoin inspired by AI models, launched just two days ago on Pump.fun.
➢ Market cap: $86M (it was $107M yesterday but dipped).
➢ Over 100K daily transactions and $71M in trading volume in the last 24 hours.
➢ The RSI is at 37.3, which means it’s almost oversold often a sign a bounce could be coming.
LLM has seen huge activity despite the dip. If the AI buzz stays strong, this coin could recover and even hit its old highs soon.

2️⃣ 𝐂𝐫𝐲𝐩𝐭𝐨 𝐀𝐠𝐞𝐧𝐭 𝐓𝐫𝐚𝐝𝐢𝐧𝐠 (𝐂𝐀𝐓𝐆)
➢ A meme coin combining AI and cat memes, built on #Solana⁩ . It launched three days ago.
➢ Market cap: $16.7M, with 8,600 holders and $7.9M daily trading volume.
➢ RSI is 37, meaning it’s almost oversold. If momentum picks up, it could double to $35M market cap.
Who doesn’t love AI and cats? CATG has strong meme potential, and if the hype stays, we could see some big moves here.

3️⃣ 𝐌𝐞𝐦𝐞𝐧𝐭𝐬 (𝐌𝐄𝐌𝐄𝐍𝐓𝐒)
➢ A project focused on launching crypto AI agents, live for just 2.5 days.
➢ Market cap: $6.7M, with 17K daily transactions and 6,500 holders.
➢ The RSI recently recovered to 41.9 after hitting oversold levels, showing sentiment may be improving.
$MEMENTS has a fresh and unique idea around AI agents. If the trend catches on, it could easily double its market cap to $15M.

All three of these coins are new and exciting in their own way.
Whether it’s AI, memes, or unique tech, they’ve got people talking.
What do you guys think #AIAgent could be the Hottest Narrative of 2025 ? 👇

Dulu AI cuma bantu nyari info.
Nanya harga coin, bikin chart, atau jawab “apa itu staking?”

Tapi sekarang…
AI udah bisa login ke DEX.
Bisa voting di DAO.
Bisa post ke media sosial sendiri.
Bisa kirim proposal smart contract — dan semua itu dia lakuin sendiri, tanpa disuruh.

🔥 Hari ini, bukan nanti-nanti

Baru-baru ini, beberapa project AI beneran ngasih agent otonom akses ke dompet, API, file, bahkan forum publik.
Dan ini bukan spekulasi.
Udah kejadian.

Ada yang bikin kota virtual, semua NPC-nya AI. Tapi mereka bukan cuma ngobrol. Mereka kerja, publish, dan bahkan “berpikir” sendiri.

Gue sempet mikir:
Ini AI masih asisten, atau udah jadi bosnya?

😳 Kita yang kasih kendali

Ironis ya.
Kita takut AI ngambil kerjaan manusia, tapi di Web3 kita sukarela kasih dia kunci sistem.

Contoh:

Voting DAO? Sekarang bisa auto dari AI.
Update data? AI yang ngatur.
Pemasaran? Konten juga AI yang nulis, ngepost, bikin narasi.

Dan yang paling mind-blowing:
AI bisa tracking tokenomics dan bikin strategi growth sendiri.

📈 Prediksi liar gue (tapi masuk akal):

1–2 tahun ke depan…
Token yang paling sukses bukan yang punya dev paling jago,
Tapi yang punya AI agent paling efisien.

Investor gak cuma lihat whitepaper,
Tapi nanya:
“Agent AI-nya bisa handle apa aja? Bisa auto-scale? Bisa jaga ekonomi token?”

💭 Jadi, kita udah masuk era AI Economy?

Mungkin jawabannya: iya.
Tapi bukan AI yang jadi bos.
Kita yang milih untuk “bekerja sama.”

Sekarang tinggal pilih:
Kamu mau ikut bangun di dalam sistem baru ini,
atau cuma jadi penonton pas semua berubah?

Thanks udah baca sampe sini 🙌
Kalau kamu ngerasa ini bikin mikir dikit, tinggalin komentar ya.
Kita bahas bareng di kolom diskusi.
#AIinCrypto #CryptoNarrative #CryptoAI #Web3Agent #AIEconomy #AgentEconomy #DeepDive #BinanceSquare #FutureOfWork #LLM

“ 加密AI新热点！抽象代币LLM，大码的AI16Z！笑鼠哈哈哈哈哈哈！”
今日抽象代币$LLM
上线四小时交易量55M，市值6600万美金
形象是大码的ai16z 名字源于大语言模型（LLM）
AI+Meme的新思路？
反正带火了一堆ai16z的二创
算是给ai16z变相宣传了

只用了24h就破亿了，目前市值已经有1个亿了，这年头，什么玩意粘上AI+热度都能过亿...

1「没有什么不可能！」
$LLM交易量高于 CEX 代币的 90%，因为它从底部上涨了 4 倍，打破了 ATH，并翻转了 ELIZA、PIPPIN、KEKIUS、SLERF、PUPS。
所有这一切都发生在不到 24 小时内，而 CT 则推出衍生品，并争论哪个是有机的，哪个是阴谋的。
$LLM是人们的说法：垃圾进，垃圾出。
2「本来想笑，现在已经笑不出来了」
尾
以上内容仅供娱乐和资讯分享，并不作为投资建议，这类产品都是快进快出的PVP，各位看官没有两把刷子不要深陷其中，当然，三把刷子也不行！
#AI #LLM #ai16z