人工智能正在快速發展——但並不總是以人們所期望的方式。盡管頭條新聞仍然集中在龐大的基礎模型和炫目的演示上，但一種更爲安靜的轉變正在進行——這轉變的重點是讓人工智能在現實世界中真正發揮作用。

![](http://img.gateio.im/social/moments-765575cf59-d74407a11c-153d09-7649e1)



人工智能正在迅速發展——但並不總是以人們預期的方式發展。盡管頭條新聞仍然集中在大型基礎模型和炫目的演示上，但一個較爲安靜的轉變正在進行——這完全是關於讓人工智能在現實世界中真正發揮作用。

PAI3團隊最近的一篇帖子列出了三個超越流行詞的趨勢，指出AI技術棧如何在內部發生變化。以下是他們所涵蓋內容的分解，以及爲什麼這很重要。

1. 代理商正在成爲人工智能的真正主力軍

向ChatGPT詢問趣聞的時代已經讓位於更結構化、特定於工作的人造智能。這些是模塊化的人工智能單元，旨在執行任務：總結報告、管理加密貨幣投資組合、自動化重復工作流程，或充當數字研究助理。

與其使用一個龐大的模型試圖做所有事情，不如讓代理允許開發者(甚至非技術用戶)爲特定領域配置人工智能——然後將其部署爲自主運行。

這一變化對基礎設施來說是巨大的，因爲:

代理需要持續運行或按需運行。

他們需要安全地訪問工具、數據和API。

他們需要可擴展、具有成本效益的環境來運營。

這就是PAI3的去中心化節點的作用——提供一個分布式系統來托管和執行這些代理.

2. 推理是人工智能戰鬥實際進行的地方

訓練模型受到很多關注，但推理才是實際AI使用和成本的主導。每當用戶與AI系統交互時，推理是在幕後發生的事情。它計算密集，需要低延遲，並且必須在不超出預算的情況下擴展。

集中式雲服務提供商仍然是今天推理的默認選擇，但它們昂貴、不透明，並且越來越擁堵。

PAI3 顛覆了這一點，通過在全球貢獻者運營的獨立節點上啓用邊緣推理。這些節點運行容器化的 AI 工作負載，從 LLM 到代理，並在本地存儲加密數據。

這使得推斷：

更高效

更私密

對於提供計算的人員來說，經濟回報更高。

3. 去中心化正成爲人工智能的必要條件

隨着對人工智能的需求增加，集中控制的局限性——數據隱私風險、計算壟斷和單點故障——正變得越來越難以忽視。

解決方案？從頭重新思考基礎設施。

PAI3正在構建一個去中心化的計算網路，其中：

貢獻者運行節點並爲處理AI任務賺取報酬

AI代理通過去中心化推理機器安全部署和路由(DIM)

數據保持私密和加密——絕不會復制到中央服務器

經濟價值與提供實際效用的那些人共享

這是一張不僅僅用於運行人工智能的網路，而是爲了使其力量、經濟和訪問權民主化。

最後的思考

這些趨勢並不是假設——它們已經在實施中。PAI3的網路已經上線，正在增長，並證明了一種不同的AI基礎設施模型是可能的。一個不依賴於集中式雲壟斷或抽象代幣經濟的模型。一個計算、數據和獎勵在邊緣流動的模型。

想要探索如何運行節點、部署代理，或者僅僅想了解更多信息嗎？

訪問他們的官方網站或在 X 上查看他們 @Pai3Ai

AI is evolving rapidly—but not always in the ways people expected. While the headlines are still focused on massive foundation models and flashy demos, a quieter shift is underway—one that’s all about making AI actually work in the real world.

![](https://img.gateio.im/social/moments-765575cf59-d74407a11c-153d09-7649e1)



AI is evolving rapidly—but not always in the ways people expected. While the headlines are still focused on massive foundation models and flashy demos, a quieter shift is underway—one that’s all about making AI actually work in the real world.

A recent post by the team at PAI3 lays out three trends that go beyond buzzwords and point to how the AI stack is changing under the hood. Here’s a breakdown of what they covered—and why it matters.

1. Agents Are Becoming the Real Workhorses of AI

The era of asking ChatGPT for fun facts is already giving way to more structured, job-specific agents. These are modular AI units that are designed to do things: summarize a report, manage a crypto portfolio, automate repetitive workflows, or act as digital research assistants.

Instead of a single massive model that tries to do everything, agents allow developers (and even non-technical users) to configure AI for specific domains—and then deploy them to run autonomously.

This shift is huge for infrastructure, because:

Agents need to run continuously or on demand.

They need to access tools, data, and APIs securely.

And they need scalable, cost-efficient environments to operate in.

That’s where PAI3’s decentralized nodes come in—offering a distributed system to host and execute these agents.

2. Inference Is Where the AI Battle Is Actually Being Fought

Training models gets a lot of attention, but inference is what dominates actual AI usage—and costs. Every time a user interacts with an AI system, inference is what happens behind the scenes. It’s compute-heavy, needs low latency, and has to scale without breaking budgets.

Centralized cloud providers are still the default for inference today, but they’re expensive, opaque, and increasingly congested.

PAI3 flips that on its head by enabling inference at the edge—on independent nodes operated by contributors around the world. These nodes run containerized AI workloads, from LLMs to agents, with encrypted data stored locally.

This makes inference:

More efficient

More private

And more economically rewarding for those providing the compute

3. Decentralization Is Becoming an AI Imperative

As the demand for AI increases, the limitations of centralized control—data privacy risks, compute monopolies, and single points of failure—are becoming harder to ignore.

The solution? Rethinking the infrastructure from the ground up.

PAI3 is building a decentralized compute network where:

Contributors run nodes and earn for processing AI tasks

AI agents are deployed and routed securely via a decentralized inference machine (DIM)

Data stays private and encrypted—never copied to central servers

Economic value is shared with those who provide actual utility

It’s a network designed not just to run AI, but to democratize its power, economics, and access.

Final Thoughts

These trends aren’t hypothetical—they’re already being implemented. PAI3’s network is live, growing, and proving that a different model for AI infrastructure is possible. One that doesn’t rely on centralized cloud monopolies or abstract tokenomics. One where compute, data, and rewards flow at the edge.

Want to explore how to run a node, deploy an agent, or just learn more?

Visit their official website or check them out on X @Pai3Ai

3 AI Trends Defining 2025 — And the Infrastructure That’s Quietly Powering Them

2025年定義的三大人工智能趨勢——以及默默推動它們的基礎設施

去中心化人工智能的推動正在加速。但偉大的願景伴隨着一個非常真實的技術挑戰：如何在全球分布的獨立機器網路上安全、高效且可驗證地運行強大的人工智能工作負載？這就是容器化人工智能進入視野的地方——而像PAI3這樣的平台也開始脫穎而出。

去中心化人工智能的推動正在加速。但偉大的願景伴隨着一個非常現實的技術挑戰：如何在一個全球分布的獨立機器網路上安全、高效且可驗證地運行強大的人工智能工作負載？

這就是容器化人工智能進入視野的地方——也是像PAI3這樣的平台開始脫穎而出的地方。


![](http://img.gateio.im/social/moments-765575cf59-0ba23251d6-153d09-7649e1)容器化 AI 到底是什麼？

容器化人工智能是指將人工智能模型—連同其所有代碼、依賴關係和數據路由—打包在一個自包含、隔離的環境中，稱爲容器。可以把它想象成一個密封的艙體，可以發送到世界任何地方的機器上運行，並返回結果—所有這一切都不會泄露內部的信息。

爲什麼這會是一個遊戲規則的改變者？因爲它使得無信任計算成爲可能。數據隱私得以維護。模型完整性得以保持。任務可以分配給匿名節點而不影響安全性。

爲了使去中心化的人工智能超越理論，進入實際部署，容器化是必不可少的。

PAI3 如何應用它

PAI3是一個去中心化的人工智能基礎設施項目，它不僅在理論上探討這個未來——而是在實際構建它。他們實現了加密容器，這些容器允許人工智能推理任務直接在貢獻者節點上運行，同時保護模型和輸入數據不被窺探。

在他們的網路中，流程是這樣的：

1. AI任務被加密並容器化。
2. 任務通過去中心化推理機器(DIM)分發給節點。
3. 節點在不訪問原始數據的情況下處理這些任務。
4. 結果經過驗證，並以\$PAI3 代幣進行獎勵。

該模型消除了傳統基於雲的人工智能的中心瓶頸和數據漏洞。它還爲貢獻計算資源的節點運營者創造了真正的收益潛力。

這很重要

容器化人工智能不僅使網路更加安全，還使其更加可擴展。

工作負載隔離：每個任務獨立運行，降低了幹擾或數據泄露的風險。

硬件無關性：任務可以在不同的機器上運行，使人們更容易加入網路。

經濟高效：貢獻者根據驗證的表現獲得獎勵，而不僅僅是正常運行時間。

全球可訪問：任何擁有計算能力的人都可以支持 AI 工作負載，從而消除中介的作用。

這種方法支持更具包容性和韌性的基礎設施，並爲從醫療保健到金融的各種應用奠定基礎，同時保護隱私。

不僅僅是基礎設施

PAI3 不僅僅是在部署智能技術——他們還邀請建設者、研究人員和普通節點操作員參與 AI 經濟。使用容器化環境是他們認真負責、並且有目的地擴展的強烈信號。

他們並不是要完全取代集中式人工智能——而是爲那些相信分布式計算、隱私優先原則和社區驅動創新的人展示了一條可行的道路。

訪問pai3官方網站，看看他們正在構建什麼

這是少數幾個技術追趕願景的項目之一——而容器化的人工智能是推動它的引擎。

The push for decentralized AI is accelerating. But with great vision comes a very real technical challenge: how do you run powerful AI workloads on a globally distributed network of independent machines—securely, efficiently, and verifiably?That’s where containerized AI enters the picture—and where platforms like PAI3 are beginning to stand out.

The push for decentralized AI is accelerating. But with great vision comes a very real technical challenge: how do you run powerful AI workloads on a globally distributed network of independent machines—securely, efficiently, and verifiably?

That’s where containerized AI enters the picture—and where platforms like PAI3 are beginning to stand out.


![](https://img.gateio.im/social/moments-765575cf59-0ba23251d6-153d09-7649e1)What Is Containerized AI, Really?

Containerized AI is about packaging an AI model—along with all its code, dependencies, and data routing—in a self-contained, isolated environment known as a container. Think of it as a sealed pod that can be sent to a machine anywhere in the world, run there, and return results—all without leaking what's inside.

Why is that a game-changer? Because it makes trustless compute possible. Data privacy is maintained. Model integrity is preserved. And tasks can be distributed to anonymous nodes without compromising security.

For decentralized AI to move beyond theory and into practical deployment, containerization is a must.

How PAI3 Applies It

PAI3 is a decentralized AI infrastructure project that’s not just theorizing about this future—it’s building it. They’ve implemented encrypted containers that allow AI inference tasks to run directly on contributor nodes, all while shielding the model and input data from prying eyes.

Here’s how the process works in their network:

1. AI tasks are encrypted and containerized.
2. Tasks are dispatched to nodes via the Decentralized Inference Machine (DIM).
3. Nodes process these tasks without ever accessing raw data.
4. Results are verified and rewarded with \$PAI3 tokens.

This model eliminates the central bottlenecks and data vulnerabilities of traditional cloud-based AI. It also creates real earning potential for node operators who contribute compute resources.

Why This Matters

Containerized AI doesn’t just make the network more secure—it makes it more scalable.

Workload Isolation: Each job runs independently, reducing risk of interference or data leakage.

Hardware Agnostic: Tasks can run on diverse machines, making it easier for people to join the network.

Economically Efficient: Contributors are rewarded based on verified performance, not just uptime.

Globally Accessible: Anyone with compute power can support AI workloads, removing gatekeepers from the equation.

This approach supports a more inclusive and resilient infrastructure, and it creates the foundation for applications ranging from healthcare to finance, all while preserving privacy.

More Than Just Infrastructure

PAI3 isn’t just deploying smart tech—they’re inviting builders, researchers, and everyday node operators to participate in the AI economy. The use of containerized environments is a strong signal that they’re serious about scaling responsibly, and with purpose.

They're not trying to replace centralized AI entirely—but they’re showing a viable path for those who believe in distributed compute, privacy-first principles, and community-driven innovation.

Visit pai3 official site and see what they are building

This is one of the few projects where the tech is catching up to the vision—and containerized AI is the engine powering it.

Containerized AI: Why It Matters—And How PAI3 Is Building Around It

容器化人工智能：它爲何重要——以及PAI3是如何圍繞它構建的

好的，如果你最近對金庫策略掉以輕心，這裏給你一個提醒，讓你坐直一點。Summerfi ( 是的，之前被稱爲Oasis)的人剛剛通過Silo和Apostro推出了一個高風險、高回報的USDC金庫——這實際上非常有趣。事情是這樣的：這個新的金庫讓你接觸到Silo的USDC借貸市場，並增添了一些刺激——以Apostro的ACR策略爲形式，這一切都是關於風險意識的收益優化。

![](https://img.gateio.im/social/moments-765575cf59-9ecfefee50-153d09-7649e1)好的，如果你最近對投資策略有所忽視，這裏提醒你稍微坐直一點。

Summerfi (是的，曾經被稱爲Oasis的團隊)剛剛通過Silo和Apostro推出了一個高風險、高回報的USDC金庫——這實際上相當有趣。

這裏是交易內容：
這個新金庫讓你接觸到Silo的USDC借貸市場，並增加了一些刺激因素——Apostro的ACR策略，專注於風險意識的收益優化。

TL;DR: 這個保險庫借出USDC，而Apostro在幕後進行數學運算，以嘗試提高你的收益。

當然，這並不是你那種輕鬆的周日駕車穿越DeFi策略。Summerfi 明確表示——這一次有點鋒利。更多的波動性，更多的不確定性，還有，是的，更多的潛在漲。這就像是穩定幣金庫的雙倍濃縮咖啡版本。

那麼，這個到底是爲誰準備的呢？

如果你是一個已經對借貸協議和DeFi金庫有良好了解的人，並且希望在保持鏈上和透明的情況下測試一種更實驗性的方法——這可能正是你所需要的。

如果你剛剛開始，聽到“風險策略”這幾個詞就頭疼，或許可以先從他們的DSR保險庫開始。(說真的，沒什麼可羞愧的——那是很不錯的選擇。)

夏天金融不斷給我們提供選擇，難道這不是很驚人嗎？保守一點？選擇 Maker 的 DSR。想要冒險一點？試試 Apostro 增強路線。所有都是非托管的。全自動化。非常順暢。

哦，你可以在儀表板上直接跟蹤保險庫的風險信號和統計數據。如果你喜歡像看《權力的遊戲》一樣觀看圖表，這非常有幫助。

想試試新的 USDC + Apostro 金庫嗎？請訪問 summerfi 的官方網站，看看吧。只需記住：更高的獎勵往往伴隨着更高的風險。小心開始，保持好奇，了解你的退出方式。

開心的存 vaulting，朋友們。

Okay, so if you’ve been sleeping on vault strategies lately, here’s your nudge to sit up a bit.Summerfi (yeah, the folks formerly known as Oasis) just introduced a higher-risk, higher-reward USDC vault via Silo and Apostro—and it’s actually pretty interesting.Here’s the deal:This new vault gives you exposure to Silo’s USDC lending market with some added spice—in the form of Apostro’s ACR strategy, which is all about risk-aware yield optimization. 

![](https://img.gateio.im/social/moments-765575cf59-9ecfefee50-153d09-7649e1)Okay, so if you’ve been sleeping on vault strategies lately, here’s your nudge to sit up a bit.

Summerfi (yeah, the folks formerly known as Oasis) just introduced a higher-risk, higher-reward USDC vault via Silo and Apostro—and it’s actually pretty interesting.

Here’s the deal:
This new vault gives you exposure to Silo’s USDC lending market with some added spice—in the form of Apostro’s ACR strategy, which is all about risk-aware yield optimization. 

TL;DR: the vault lends USDC, and Apostro does the mathy stuff behind the scenes to try and juice your returns.

Of course, this isn’t your chill, Sunday-drive-through-DeFi strategy. Summerfi makes it clear—this one’s got a bit of edge to it. More volatility, more uncertainty, and yeah, more potential upside too. It’s like a double espresso version of a stablecoin vault.

So, who’s this really for?

If you’re someone who already has a good feel for how lending protocols and DeFi vaults work—and you’re looking to test a more experimental approach while keeping things on-chain and transparent—this could be your alley.

If you're just getting started and the words “risk strategy” give you a headache, maybe start with their DSR vaults instead. (Seriously, no shame—those are solid.)

Isn't it amazing Summerfi keeps giving us options. Conservative? Go with Maker's DSR. Feeling adventurous? Test the Apostro-enhanced route. All non-custodial. All automated. All smooth.

Oh, and you can track the vault’s risk signals and stats right there in the dashboard. Super helpful if you're the type that likes to watch charts like it’s Game of Thrones.

Want to try out the new USDC + Apostro vault? Head over to summerfi's official website and take a look. Just remember: higher rewards often come with higher risk. Start small, stay curious, and know your exits.

Happy vaulting, friends.

IAmDefiGem

2025年定義的三大人工智能趨勢——以及默默推動它們的基礎設施

容器化人工智能：它爲何重要——以及PAI3是如何圍繞它構建的

Summerfi最新的Vault並不適合膽小的人(但可能值得)