0G Labs George Varghese：打造兆元級 AI 代理經濟的關鍵基礎設施

0:00AI代理經濟的拐點來臨

0:00大家好，我是 George，負責 0G Labs 的投資與合作夥伴關係。0G，也就是 Zero Gravity，正在打造 AI 的信任層。我們正在建構全球最大的 AI Layer-1 區塊鏈，擁有自己的運算網路、儲存網路，以及龐大的 AI 應用和代理人（agent）生態系。今天要談的主題，就是如何打造兆元級的 AI 代理經濟，以及目前市場的現況，還有 0G 的基礎設施如何成為關鍵推手。My name is George. I lead investments and partnerships at 0G. 0G, or Zero Gravity, is building the trust layer for AI. We are building the largest AI layer one blockchain with our own compute network, our own storage network, and a huge ecosystem of AI applications and AI agents. So the topic of today's conversation is going to be about building the trillion-dollar agent economy and what status we are in right now with regards to the market, and then how 0G's infrastructure will be a critical component of it.

0:42我們認為，AI 代理經濟正處於關鍵的轉折點。現在的需求正要迎來爆發性成長，曲線即將大幅上揚。2023 年，我們經歷了 ChatGPT 的 prompt-response 時刻；2024 年，代理人開始能當你的 copilots；到了 2025、2026 年，代理人已經能處理更複雜、多步驟的任務。未來，代理人將積極參與商業活動，甚至彼此購買、取代部分人力，並改變資本流動方式。現在正是進場的最大機會點，因為我們正站在指數成長的轉折處。So here's where we are. We believe we are at an inflection point in the AI agent economy. We think the demand that we see is just on the precipice of a massive acceleration. We're at the bend of the curve. What we saw in 2023 was a simple prompt and a response with the ChatGPT moment. In 2024, we got a little more sophisticated and we had agents helping as copilots. In 2025, 2026, we're seeing agents are able to do more complicated, multi-step tasks. And going forward, we believe agents will be participating in commerce actively. Agents will be purchasing other agents. They will be replacing the workforce. They will be augmenting the way capital actually flows. And so the maximum opportunity is right now because we are at the turning point of an exponential curve.

1:39AI代理經濟的爆炸性成長數據

1:39來看一些數據，證明我們正處於什麼位置。2025 年，OpenRouter 每週處理的 LLM token 數量是 0.5 兆；到了 2026 年 9 月，這個數字已經暴增到 126 兆。這是標準的指數型成長曲線，而且還會繼續加速。當初 ChatGPT 剛出來時，主要是人類在跟 LLM 互動；但現在，AI 代理人消耗的 LLM token 已經超越人類，這是一個巨大的轉捩點。代理人消耗的資源比人還多，代表代理經濟正以前所未有的速度成長。Here's some data to prove my point, to show you where we are versus where we were just a year ago. If you look at the total tokens that were routed through OpenRouter in 2025, we were at 0.5 trillion tokens per week. Now, in 2026, September, it's so much more. It's at 126 trillion tokens, LLM tokens that have been routed through OpenRouter. This is an exponential curve. We think this continues accelerating in a very large, meaningful way. Another important thing to consider is that when ChatGPT came out, it was mainly humans interacting with the LLMs. We are at a point right now where agents are actually out-consuming LLM tokens compared to humans. Agents spend more and are using LLMs more than humans are. That's a huge inflection point. That means the agent economy is truly growing at an unprecedented rate.

2:40LLM token 消耗量一年成長了 250 倍。你可能會想，這是不是已經到頂了？其實還遠遠沒有。現在美國只有 2% 的家庭有付費使用 AI 服務，但已經帶來 250 倍的成長。這代表還有極大的成長空間，未來全球會有越來越多人付費、使用 AI 服務，這就是我們的機會所在。We can see that there was over 250x growth in the LLM token consumption. So you see that and you're like, wow, maybe we're getting towards the end of the cycle. It's like, no. Only 2% of the U.S. households are actually paying for AI services. 2%, and we already grew 250x. What does that mean? It means that there's so much more growth. We anticipate much more percentages of the world paying for AI services and utilizing AI services, and this is where the opportunity lies.

3:15代理支付與信任缺口

3:15代理支付（agentic payments）也是一個重要指標。現在我們只達到 2030 年預測代理支付量的 0.1%。大家都聽過 X402，這是代理人鏈上匯款最好的方式之一，但目前總交易量只有 2,400 萬美元，平均每筆只有 0.29 美元。為什麼代理人轉移的金額這麼少？因為缺乏信任、透明度與驗證機制。這正是 ZeroG 要解決的問題。Agentic payments is another important component to keep track of. We are only at 0.1% of the 2030 forecasts of agentic payments. We're all familiar with X402. And we all know that, you know, it's one of the best ways for agents to send money on chain. The thing to keep in mind is only $24 million of volume has gone through X402. The average transaction size was 29 cents. There's a reason why there isn't significant actual dollar value of transfers through agents. We believe that's because there is a lack in trust, transparency, and verification. And that's where ZeroG comes in.

3:58我們要解決大家在依賴代理人處理大額資本時的信任與驗證問題。有了 ZeroG，這些數字未來會大幅提升。從更大的格局來看，現在大型雲端業者投入大量資本建設基礎設施，2024 年資本承諾達 2,400 億美元，2027 年後將突破一兆美元。這些投入都是為了支撐更龐大的代理經濟。We are solving the trust and verification issue that a lot of us have when we want to rely on agents to actually handle meaningful capital. With ZeroG, these numbers should go much higher. So the capital commitments. If you look at the broader scope, you guys have all seen that the large hyperscalers are committing a lot of capital towards scaling the infrastructure. High memory bandwidth and the GPUs and data centers are all growing and being built, and they take several years. And you can see in 2024, there was 240 billion in capital commitments. In 2027 onwards, it's going to be over a trillion dollars. And so we are also seeing massive expenditures from the large companies to scale up infra to support a larger agent economy.

4:49ZeroG 的產品與團隊實力

4:49在 ZeroG，我們非常感謝目前所取得的發展成果。我們擁有一個龐大的社群，同時作為一個前沿實驗室，我們也具備創建模型並以更有意義的方式參與代理經濟的能力。我們最近推出了一款產品，叫做 ZeroG Private Computer，你可以從 Blocks 的報導中看到，我們在三到四個月內就達到了 4000 億個 LLM 代幣的消耗量。我們正在看到巨大的發展動能和大量的採用，因為使用 ZeroG PC 的人，他們很在意自己的隱私，對吧？當你使用集中式模型提供者時，問題在於你不知道他們會怎麼處理你的資料，你也不知道他們是否會用你的資訊來訓練模型。So at ZeroG, we're very grateful for the traction that we have. We have a large community, but we also have this ability as a frontier lab to create models and to participate in a more meaningful way in the agent economy. We recently released a product called the ZeroG Private Computer, and you can see with the Blocks coverage, we were able to get 400 billion LLM tokens consumed in the span of three to four months. We're seeing massive traction, massive adoption, because the people who use ZeroG PC, they care about their privacy, right? When you use centralized model providers, the issue is you don't know what they're doing with your data. You don't know if they're training the model with your information.

5:36所以，如果你擁有敏感資料或專有資料，你有多大的信心可以信任這些中心化的供應商？你怎麼知道他們不會濫用這些資料？你怎麼知道他們不會利用這些資料來打造更優秀的模型，甚至可能超越你的事業，對吧？因此，ZeroG 吸引全球用戶的地方，就是讓大家能夠進來並維護資料主權。And so if you have sensitive data or proprietary data, how confident are you to trust the centralized providers with that? How do you know that they're not going to abuse that data? And they're not going to perhaps create better models that may outcompete your business, right? So with ZeroG, the draw for people around the world is to come in and maintain data sovereignty.

6:01ZeroG 擁有一支全明星團隊：都是經驗豐富的創業家，還有曾經創辦獨角獸公司的成員。我們有 Michael 擔任執行長，Ming 擔任技術長。團隊最初設立於矽谷，現在也在新加坡設有永久據點。因此，Token Singapore 對我們來說是一個非常重要的活動，我們很高興能夠來到這裡。許多正在建設的基礎設施，都是由全球最頂尖的 AI 研究人員打造的。我們團隊有超過 100 名成員，其中超過 80% 是工程師，其餘則主要負責管理、行銷和投資，這是從我的角度來看。我們擁有大量資金。We have an all-star team at ZeroG: seasoned entrepreneurs, previous unicorn founders. We have Michael, our CEO, Ming, our CTO. And the team was based in Silicon Valley and now has a permanent base in Singapore as well. So Token Singapore is a very important event for us, and we're really happy to be here. A lot of the infrastructure that's being built is built by the best AI researchers in the world. We have over 100 team members, more than 80% of them are engineers, and then the rest of them are more on the management and marketing and investments from my point of view. We have a large funding.

6:43我們已經從矽谷頂尖創投和全球創投那裡募得超過三億五千萬美元，我們非常感謝他們的支持。我們知道這些投資人相信這個願景。他們相信去中心化 AI 的願景。他們相信必須要有安全機制和信任機制，才能真正讓人們最大程度地運用 AI。We've raised over $350 million from the top Silicon Valley VCs and global VCs, and we're really grateful for the support. And we know that these investors believe in the vision. They believe in the vision of decentralized AI. They believe that there has to be safety measures and trust measures in place to really enable people to leverage AI to the maximum ability.

7:07ZeroG 的技術架構與代理人信任機制

7:07這裡有一張小型資訊圖表，讓你們了解我們的生態系以及我們的基礎設施長什麼樣子。你可以看到我們擁有一個垂直整合的技術堆疊，包括去中心化儲存網路、去中心化運算網路。我們在底層有一條區塊鏈，作為結算層。這是一條第一層區塊鏈，與EVM相容。它針對AI代理人進行了極致優化。目前在0G上已有超過270萬個AI代理人正在運作，而這條鏈不僅協助支付結算，也協助驗證。因此，我們能夠將代理人所執行的任何交易的聲明與證明寫入鏈上，從而建立審計追蹤紀錄。So here's a little infographic to show you what our ecosystem and what our infrastructure looks like. You can see that we have a vertically integrated stack with a decentralized storage network. A decentralized compute network. We have the chain underneath, which acts as a layer for settlement. It's a layer one blockchain, EVM compatible. It's hyper-optimized for AI agents. We have over 2.7 million AI agents live on 0G right now, and the chain helps with settling payments, but the chain also helps with proof. So we're able to write attestations and proof about whatever transactions an agent has done onto the chain. And so we can create an audit trail.

7:50這對企業來說非常重要，因為如果他們正在使用 AI agent，而這個 agent 發生了錯誤，或者 agent 做了他們原本不打算讓它做的事情，他們就需要能夠回溯並審核到底發生了什麼事。區塊鏈是最適合這個用途的技術。區塊鏈是一個分散式帳本，一切都是透明的，所有事情都被記錄在鏈上，你可以回頭檢視到底哪裡出了問題。This is really important for enterprises because if they are utilizing AI agents and the agent makes a mistake or the agent does something that they didn't intend to do, they need to be able to go back and see and audit what happened. The blockchain is the best technology for that. The blockchain is a distributed ledger. Everything is transparent. Everything is recorded on the chain, and you can go back and see what went wrong.

8:21以下是這些組成要素，以及它們實際上的相關性。AI代理需要許多不同的東西，才能真正運作並成為完全自主AI經濟的一部分。首先，他們需要驗證運算。當你進行推論和微調，當你為一個模型付費時，你要如何驗證這確實是你所付費的那個模型？當你使用ChatGPT，當你使用Anthropic，當你說「我想要Opus」或是其他任何模型時，你怎麼知道實際提供給你的就是那個模型？你是在信任這些中心化的供應商會給你你所付費的模型，但你無法驗證這一點。Here are the components and how they're actually relevant. AI agents need a lot of different things to actually work and to actually be a part of a fully autonomous AI economy. First thing is they need to verify the compute. So when you do the inferencing and the fine-tuning, when you pay for a model, how do you verify that it is the model you paid for? When you go to ChatGPT, when you go to Anthropic, when you say, I want Opus or I want whatever model, how do you know that model is what was actually served to you? You are trusting the centralized providers to give you the model you're paying for, but you cannot verify it.

8:56透過區塊鏈以及ZeroG的私有電腦，你可以精確驗證到底是什麼模型為你提供了服務。你也可以看到產生該輸出的資料來源。此外，你還可以帶入你自己的模型，你自己預先訓練的客製化模型，並將其託管在ZeroG的網路上，讓其他人也能參與這個經濟體系。因此，你同時成為AI的生產者與消費者。記憶對於AI代理人來說非常重要。他們需要知道自己過去做過什麼、未來該如何運作、有哪些指引、有哪些安全防護措施、還有他們需要執行的事項。因此，我們有儲存網路來支援代理型記憶。With the blockchain and with ZeroG's private computer, you can verify exactly what model was served to you. You can also see what data was used to create that output. In addition to that, you can bring your own model, your own pre-trained custom model, host it on ZeroG's network, and allow others to also participate in the economy. And so you become both a producer and a consumer of AI. Memory is a huge thing for AI agents. They need to know what they've done in the past, how to operate in the future, what are the guidelines, the safeguards, what are the things that they need to do. And so we have the storage network to allow for agentic memory.

9:40身份與信譽。你要怎麼信任這些 AI 代理人？你要怎麼能夠把更多資本交給它？就像我剛才說的，目前只有很少的資金經過 X402。這是有原因的。這裡大多數人都不會信任一個代理人管理超過自己淨資產的 10%。我甚至認為這個比例可能更低，可能只有你淨資產的 1%。所以我們需要一種方式來建立代理人的信譽。因此，我們創建了一個新的 ERC 標準。這就是 ERC-7857。它是一個由 ETH Foundation 核准的 agentic ID。Identity and reputation. How do you trust these AI agents? How are you going to be able to give it more capital? As I told you, such small amounts of money has gone through X402. There's a reason for that. Most of the people here in this room would not trust an agent with more than 10% of their net worth. I would say it's probably even less than that, maybe 1% of your net worth. So we need a way to have a reputation for agents. And so we created a new ERC standard. It's the ERC-7857. It's an agentic ID approved by the ETH Foundation.

10:11它的運作方式是，將一個代理人與其資料以及代理人擁有者的來源紀錄全部綁定在一起，並以 NFT 的形式呈現。我們都知道 NFT，例如有趣的頭像圖像（PFP）、Bored Apes 這些。我們其實認為 NFT 對於 AI 代理人的所有權證明非常有用。如果你真的把 NFT 指派給代理人，你就可以清楚看到代理人、擁有者和資料之間的關聯路徑。然後，你也可以透過轉移 NFT 來轉移這個代理人的所有權。這樣就能透過我們熟悉且喜愛的 NFT 市場交易機制，創造出一整個代理人市場。支付也是很重要的一環。And what it does is it bundles an agent with its data and provenance records of the owner of the agent, all in the form of an NFT. So we all know NFTs, the fun PFPs, Bored Apes, and all of that. We actually think NFTs are useful for ownership proof of AI agents. If you actually assign an NFT to the agent, you can see a clear track between the agent, the owner, and the data. And then you can also transfer ownership of this agent by transferring the NFT. So this creates a whole agent marketplace through a similar mechanism we all know and love of trading NFTs on our favorite NFT marketplaces. Payments is important.

10:52所以我們利用了 X402，但我們同時也正在打造我們自己的支付層，讓代理人能夠為自己的運算支付費用。稍後我會更詳細說明我們如何實際創造一個新的術語，叫做「運算金融」（compute finance），在這個模式下代理人可以自助服務。他們可以為自己的推論支付費用，甚至可以協助支付自己的訓練費用。這一切都是自主進行，完全不需要人類介入。這就是即將推出的 ZeroG Pay。對於 ZeroG 來說，隱私是預設選項。我們有可信執行環境，搭配 ZeroG TAP，這讓我們能夠實現完整的隱私保護、端對端加密、完整驗證執行過的模型，以及資料是否有被外部操控——所有的證明都在那裡，而且我們會把這些證明儲存在鏈上。So we leverage X402, but we're also creating our own payment layer so that agents can pay for their own compute. I'll go into it in a little bit later on how we are actually creating a new terminology called compute finance, where agents can be self-serving. They can pay for their own inference. They can actually help pay for their own training. Autonomously, with no human in the loop. And so that's ZeroG Pay, which is coming out soon. Privacy is a default option for ZeroG. We have trusted execution environments along with ZeroG TAP, and this enables full privacy, end-to-end encryption, full verification of what model ran, and if there was any external manipulation of the data, it's—all the proof is there, and we store it on-chain.

11:40生態系與鏈上效能

11:40我們的生態系非常龐大，已經有超過 350 個專案在 0G 上開發。最常見的整合點是我們的運算網路，但也有很多人對儲存和鏈本身有興趣。我們的鏈專為 AI 代理人優化，TPS 達到 11,000 筆，Gas 費比 Solana、Base 和 L2 都便宜，對 L1 來說非常強大。現在已經有 270 萬個代理人，預計明年會突破 1,000 萬。As I mentioned earlier, we have a large ecosystem. We have over 350 projects building with 0G. It's hard to see the logos, and this is only a select number of logos of teams building. And I would say the most common integration point is our compute network, but there is also interest in our storage and the chain itself. Our chain is hyper-optimized for AI agents. It's 11,000 transactions per second. The gas fees are much cheaper than Solana and Base and the L2s, so for an L1, it's great. And then again, it can sustain large-scale AI agent networks. 2.7 million agents already. We anticipate 10 million agents by next year.

12:23模型訓練與推論的套利機會

12:23所以我們現在看到市場上有一個很大的套利機會。這個套利機會是什麼呢？模型訓練成本正在大幅上升。Dario 認為很快就會有一次價值十億美元的模型訓練運行。我們一開始的成本其實便宜很多，只需要幾十萬到幾百萬美元，現在訓練一個 AI 模型已經進入十億美元的等級。當這種情況發生的同時，推論的成本其實正在下降，而且是大幅下降。推論成本已經降低了 280 倍。推論成本，也就是每個字的成本，變得更低了。那這對大家來說意味著什麼？這對 0G 又意味著什麼？So we see that there is a big arbitrage opportunity right now in the market. What is the arbitrage opportunity? Model training costs have been increasing significantly. Dario believes that there's going to be a $1 billion model training run that's going to happen. We started at much cheaper. It was only, you know, a couple hundred K to a couple million, and now we're going into the billion-dollar range for training an AI model. While that's occurring, the cost of inference is actually coming down. It's coming down significantly. There's a 280x reduction in cost of inference. Cost of inference, meaning cost per words, is less. And so what does that mean for you all? What does that mean for 0G?

13:07這表示我們應該啟用一個機制，讓你能夠參與模型訓練。然後以更便宜的費率消耗推論代幣。所以我們做的是建立一個運算市集。你，作為一個GPU持有者，無論是用你的MacBook還是你自己的其他硬體，都可以進來參與我們所謂的去中心化訓練任務。你可以利用你現有的硬體，實際貢獻於這些AI模型的訓練，並將其投入到運算市集。之後，我們有應用程式，也有一個層級讓你可以消費這些資源。私人電腦是一種讓你消費這些代幣的方式。因此，你會消耗這些代幣。隨著成本下降，你的產出其實會更多。Well, it means we should enable a mechanism for you to participate in the model training. And then consume the inference tokens at a cheaper rate. So what we do is we have a compute marketplace. You, as a GPU holder with your MacBooks or your own, you know, hardware, you can come in and participate in what we call decentralized training runs. You can contribute to the actual training of these AI models by leveraging your own existing hardware. And putting it in the compute marketplace. After that, we have applications and we have a layer where you can consume this. The private computer is a way for you to consume the tokens. And so you consume the tokens. As the cost comes down, your output is actually more.

13:53每一美元每一個代幣的成本會下降，然後你作為消費者和生產者都可以使用更多的代幣。這是一個巨大的機會。運算資源市集是一個很好的實現方式。區塊鏈也是一個很好的實現方式，因為我們實際上可以將這整個流程從頭到尾都代幣化。The cost per dollar per token goes down, and then you can use more of the tokens as both the consumer and the producer. It's a huge opportunity. A compute marketplace is a great way to do it. The blockchain is a great way to do it because we can actually tokenize this entire flow end to end.

14:11我們在 ZeroG 已經在降低 AI 訓練成本方面取得了重大進展。我們完成了歷史上最大規模的去中心化訓練，一個擁有 1070 億參數的模型。我們訓練了這個模型。這大約是一年前的事了，而我們能夠以更低的成本完成這項工作。如果你看看，我們能夠比傳統的訓練方式便宜 95%，而且效率幾乎提升了 100 倍。現在我們即將進行的下一次訓練，我們會開放給社群參與。就像我剛剛提到的，我們希望你們大家都能成為這次訓練的參與者。We have made significant progress at ZeroG in reducing the cost of AI training. We did the largest decentralized training run in history, a 107 billion parameter model. We trained that. This was almost a year ago at this point, and we were able to do it much cheaper. If you see, we were able to do it 95% cheaper than the traditional way of doing a training run, and we were able to be almost 100x more efficient. And now the next run that we're going to do, we're going to open it up to the community. As I mentioned, we want you all to be participants in the training.

14:45我們希望大家都成為參與者，不只是因為參與者有財務上的誘因，更重要的是信任。比特幣和加密貨幣的整個精神，就是沒有單一的中心實體來控制它。我們每一個人都是參與者。因此，我們認為 AI 經濟對於模型來說也是一樣的。我們都應該共同參與訓練，這樣我們才能確信輸入的資料不會有特定的偏見、不會被某個中心實體操控，也不會被任何政府審查。每個人都應該有機會參與。The reason we want you all to be participants, not only is for financial incentives for participants, but it's also trust. The whole ethos of Bitcoin and cryptocurrency is that there is no single central entity that controls it. There is all of us that are participants. And so we think the AI economy is the same for the models. We all should contribute to the training of it. That way, we know that the data that's coming is not biased in a certain way. It's not manipulated by a central entity. It's not censored by any government, for example. Everybody should be able to participate.

15:24Compute Finance 與 IAI 代幣經濟

15:24我剛才提到過，我們現在有一個新的術語叫做「運算金融」。上週在韓國區塊鏈週剛推出的一個代幣叫做 Infinite AI，它的網站是 iai.finance，這就是我們的運算代幣。它的運作方式是，你需要質押你的 ZeroG 代幣，這是我們在 ZeroG 鏈上的 gas 代幣，然後你就可以獲得一個流動質押版本，叫做 A0G。接著你可以再質押這個 A0G，並鑄造出 IAI。我知道這個流程有點複雜，但這麼設計是有原因的。我剛剛提到的每一個步驟，其實都是一個產生收益的事件，而這些收益最終會以運算點數的形式回饋給你。So I mentioned earlier that we have this new terminology called compute finance. And so one of the tokens that was launched just last week at Korea Blockchain Week was called Infinite AI. It's iai.finance, and this is our compute token. So the way it works is you stake your ZeroG token, which is our gas token on ZeroG's chain, and you are able to get a liquid staked version of it called A0G. And then you're able to stake that and mint IAI. I know it's a complicated process, but there's reasons for this. Every step that I mentioned is a yield-generating event, and the yield actually comes back to you in the form of compute credits.

16:07所以 IAI 代幣可以用於 ZeroG 的運算網路。它也會在我們的啟動平台 Comfy.fun 上使用。在那裡，你實際上可以將發行項目、代理人發行、迷因幣與這個代幣配對，然後它還可以用來在 ZeroG App 上建構完整規模的應用程式。So the IAI token can be used for compute on ZeroG's compute network. It's going to be used on our launchpad called Comfy.fun. Where you can actually pair launches, agent launches, meme coins to the token, and then it can be used for building full-scale applications on ZeroG App.

16:26生態系投資與 Builder 支持

16:26以下是 ZeroG 在這之外支持生態系統的方式。我們知道這裡有很多開發者。Token 2049 以聚集全球最優秀的開發者聞名，對吧？所以，你知道，Michael 和團隊在募資方面做得非常出色。現在由我來主導投資這艘船，我的工作就是邀請大家來 ZeroG 上建構，然後嘗試從我們這裡獲得一些投資。我們的生態系統基金規模超過八千萬美元。我們正在積極投資。我們是即使在熊市期間也持續投入資本的最大基金之一。Here's how ZeroG is supporting the ecosystem beyond this. We know there's a lot of builders here. Token 2049 is known to bring the best builders in the world, right? And so. You know, Michael and the team have done a great job in fundraising. Now that I'm spearheading the ship on the investments, it's my job to invite everybody to come in and build on ZeroG, and then take a shot at trying to get some investment from us. We have over $80 million in the ecosystem fund. We are actively investing. We are one of the largest funds that have been deploying capital even in the bear market.

17:02因為，加密貨幣的熊市對我們來說其實是無關緊要的，因為我們首先是一家 AI 公司，我們支持 AI 項目。AI 目前仍然處於牛市，而且我們認為這還是牛市的早期階段。正如我剛才展示的指數型成長曲線，我們正處於一個關鍵的轉折點。所以，如果你是一位開發者，我們鼓勵你使用我們的技術，因為這是最好的。你知道，我們的基礎設施非常優秀。但同時，我們也有能力投資你。我們的股東名單中有龐大的投資者網路，我們也可以介紹給你。Because again, the bear market in cryptocurrency is irrelevant to us because we are an AI company first, and we support AI projects. AI is still in a bull market, and we think it's still an early bull market for it. As I showed you the exponential curve, we are at an inflection point. And so if you're a builder, we encourage you to use our technology because it is the best. You know, our infrastructure is great. But also because we have the ability to invest in you. We have a large network of investors in our cap table that we can introduce you to as well.

17:35我們有很多像是建構者計畫、行銷計畫、策略支援等各種方案可以提供給你，而這些是許多其他 L1 和 L2 無法做到的。因為，他們本身並不是以 AI 為核心，他們只是把 AI 加到自己的技術堆疊上。ZeroG 則是從零開始打造 AI，從第一天起我們就是以 AI 為核心。And we have a lot of programs like builder programs, marketing programs, strategic support that we can provide to you that a lot of other L1s and L2s are not able to do that. Because again, they are not AI focused. They are adding AI onto their stack. ZeroG built AI from the ground up, and we've been AI-focused since day one.

17:56經過三到五年的開發，現在正是我們收割努力成果的時刻。鏈上的 builder 都很開心、很期待，也希望有更多人加入我們。我的分享就到這，謝謝大家！歡迎掃描這個 QR code，追蹤我們的 Twitter、Email、Telegram，保持聯絡！And so, three to five years of development, it's finally time for us to capitalize on all the time and effort that we put in. And the builders on our chain are very happy, very excited, and we want to have more of you guys join us. So I'll end my talk here. Thank you so much for your time. Please scan this, and you can stay in touch with us on Twitter and on our email and Telegram. Thank you so much.