我們在2025年觀看的內容（加密AI）

YAN

What We're Watching in 2025 (Crypto AI)

我們在2025年觀看的內容（加密AI）

1. The total market value of the crypto AI sector will reach $150 billion

1。加密AI行業的總市場價值將達到1500億美元

Currently, tokens in the crypto AI sector only account for 2.9% of the altcoin market cap, but I believe this proportion will not last long. As artificial intelligence gradually expands to new areas such as smart contract platforms, Meme, decentralized physical infrastructure (DePIN), proxy platforms, data networks, and intelligent coordination layers, its integration with DeFi and Meme tokens has become an inevitable trend.

目前，加密AI行業中的令牌僅佔Altcoin市值的2.9％，但我相信這一比例不會持續很長時間。隨著人工智能逐漸擴展到智能合約平台，模因，分散的物理基礎設施（DEPIN），代理平台，數據網絡和智能協調層等新領域，其與Defi和Meme標記的集成已成為不可避免的趨勢。

The reason for confidence in the crypto AI sector is that it sits at the intersection of two of the most powerful trends in technology:

對加密AI部門充滿信心的原因是，它位於技術中兩個最強大的趨勢的交匯處：

2. The revival of Bittensor

2。復興Bittensor

Bittensor (token name TAO) has been around for years. It is a veteran player in this field. Despite the craze around artificial intelligence, its token price has been hovering at the level of a year ago. But in fact, the digital hive mind behind Bittensor has quietly advanced, more subnets have emerged, registration fees have been reduced, and subnets have surpassed the corresponding technologies of Web2 in actual performance such as inference speed. At the same time, EVM compatibility has introduced DeFi-like functions, further enriching Bittensor's network.

Bittensor（Token Name Tao）已經存在了多年。它是該領域的資深球員。儘管人工智能圍繞著熱潮，但它的代幣價格一直在一年前的水平上徘徊。但是實際上，Bittensor背後的數字蜂巢思想已經悄悄地先進，已經出現了更多子網，降低了註冊費，並且子網在實際性能（例如推理速度）中超過了Web2的相應技術。同時，EVM兼容性引入了類似Defi的功能，進一步豐富了Bittensor的網絡。

So why hasn’t TAO surged? A steep inflation schedule and a shift in focus toward platforms geared toward AI agents have kept it limited. However, dTAO (expected Q1 2025) could be a major turning point. With dTAO, each subnet will have its own token, and the relative prices of those tokens will determine how releases are distributed.

那為什麼陶沒有湧動呢？陡峭的通貨膨脹時間表和將重點轉移到針對AI代理的平台的轉變，使其受到限制。但是，DTAO（預期的第1季度2025年）可能是一個主要的轉折點。使用DTAO，每個子網都會有自己的令牌，這些令牌的相對價格將決定發行版的分佈方式。

Why Bittensor has a chance to explode again:

為什麼Bittensor有機會再次爆炸：

Currently watching the various subnets and recording the actual progress they make in their respective fields. It is expected that at some point, there will be a DeFi summer similar to @opentensor's version.

目前正在觀看各種子網並記錄他們在各自領域的實際進度。預計在某個時候，會有一個類似於 @Opentensor的版本的Defi Summer。

3. The computing market is the next L1 transaction

3。計算市場是下一個L1交易

The insatiable demand for computing will become an obvious megatrend. Nvidia CEO Jensen Huang once said that the demand for inference will surge "a billion times." This exponential growth will break the planning of traditional infrastructure and urgently call for "new solutions."

對計算的無限需求將成為明顯的大趨勢。 NVIDIA首席執行官詹森·黃（Jensen Huang）曾表示，對推論的需求將“十億次”。這種指數增長將打破傳統基礎設施的計劃，並緊急要求“新解決方案”。

The decentralized computing layer provides raw compute (for both training and inference) in a verifiable and cost-effective manner. Startups like @spheronfdn, @gensynai, @atoma_network, and @kuzco_xyz are quietly building strong foundations to take advantage of this, focusing on products rather than tokens (none of these companies have tokens yet). As decentralized AI model training becomes feasible, the addressable market is expected to rise dramatically.

分散的計算層以可驗證且具有成本效益的方式提供了原始計算（用於培訓和推理）。 @spheronfdn，@gensynai，@atoma_network和@kuzco_xyz之類的初創公司正在悄悄地建立強大的基礎來利用這一點，專注於產品而不是代幣（這些公司都沒有代表）。隨著分散的AI模型培訓變得可行，可尋址市場預計將急劇上升。

For the encrypted AI sector, let’s compare it with the L1 sector:

對於加密的AI部門，讓我們將其與L1部門進行比較：

Just as Solana emerges as a leader in the L1 space, the winner here will dominate a whole new frontier, paying close attention to three criteria: reliability, cost-effectiveness, and developer-friendly tooling.

就像Solana成為L1領域的領導者一樣，這裡的獲勝者將主導著一個全新的邊界，密切關註三個標準：可靠性，成本效益和開發人員友好的工具。

4. AI Agents will flood into blockchain transactions

4。AI代理商將湧入區塊鏈交易

By the end of 2025, 90% of on-chain transactions will no longer be triggered by humans manually clicking "Send". Instead, these transactions will be executed by an army of AI Agents that will continuously rebalance liquidity pools, distribute rewards, or perform micropayments based on real-time data feeds.

到2025年底，人類手動點擊“發送”將不再觸發90％的鏈交易。取而代之的是，這些交易將由AI代理商的大軍執行，這些代理商將根據實時數據提要不斷重新平衡流動性池，分發獎勵或進行微付款。

None of this is as far-fetched as it seems. Everything we have built in the past seven years (L1, rollups, DeFi, NFTs, etc.) has quietly paved the way for an on-chain world dominated by AI.

這些都沒有像看起來那樣牽強。我們過去七年中建造的所有東西（L1，卷，defi，nfts等）悄悄地為一個由AI主導的鏈界世界鋪平了道路。

So, why is there this shift?

那麼，為什麼會有這種轉變？

AI agents generate a staggering amount of on-chain activity, but the biggest challenge will be to make these AI agent-driven systems accountable to humans. As the ratio of transactions initiated by AI agents to those initiated by humans increases, new governance mechanisms, analytical platforms, and audit tools will be needed.

AI代理產生了驚人的鏈上活動，但最大的挑戰是使這些AI代理驅動的系統對人類負責。隨著AI代理與人類發起的交易的比率增加，需要新的治理機制，分析平台和審計工具。

5. Interaction between agents: The rise of the AI swarm concept

5。代理之間的互動：AI群概念的興起

AI agent swarms refer to tiny artificial intelligence entities working together seamlessly to execute grand plans, which sounds like the plot of the next popular sci-fi or horror movie. Most current AI agents operate in isolation, with few and unpredictable interactions. However, AI agent swarms will change this situation, allowing multiple AI agents to exchange information, negotiate, and make joint decisions in a network.

AI特工群是指無縫合作以執行宏偉計劃的微小人工智能實體，這聽起來像是下一部流行的科幻電影或恐怖電影的情節。當前的大多數AI代理都是孤立地運行的，幾乎沒有可預測的相互作用。但是，AI代理會改變這種情況，使多個AI代理可以在網絡中交換信息，談判並做出聯合決策。

These AI Agent swarms can be thought of as decentralized collectives of specialized models, each contributing its unique expertise to larger, more complex tasks. The potential is staggering. For example, one swarm might coordinate distributed computing resources on a platform like Bittensor, while another swarm can verify the source of content in real time to prevent false information from spreading on social media. Each AI Agent in the swarm is an expert and performs its respective task with precision.

這些AI代理群可以被認為是專門模型的分散集體，每個集體都為更大，更複雜的任務貢獻了其獨特的專業知識。潛力令人震驚。例如，一群人可能會在像Bittensor這樣的平台上協調分佈式計算資源，而另一個群可以實時驗證內容來源，以防止虛假信息在社交媒體上傳播。群中的每個AI代理都是專家，並精確地執行其各自的任務。

These swarm networks will be far more intelligent than any single isolated AI. In order for agent swarms

這些群網絡將比任何一個孤立的AI都更加聰明。為了代理人群