Palantir Technologies Inc. (PLTR) 2026 Q2 法說會逐字稿

Good afternoon. I'm Ana Soro from Palantir's finance team, and I'd like to welcome you to our second quarter 2026 earnings call. We'll be discussing the results announced in our press release issued after the market close and posted on our Investor Relations website.

下午好。我是 Palantir 財務團隊的 Ana Soro，歡迎各位參加我們 2026 年第二季財報電話會議。我們將討論在美股收盤後發布並已張貼於我們投資人關係網站的新聞稿中所公布的業績結果。

During the call, we will make statements regarding our business that may be considered forward-looking within applicable securities laws, including statements regarding our third quarter and fiscal 2026 results management's expectations for our future financial and operational performance and other statements regarding our plans, prospects and expectations.

在本次電話會議中，我們將就本公司業務發表若干陳述；依適用之證券法規，這些陳述可能被視為前瞻性陳述，包括關於我們第三季及 2026 會計年度業績、管理層對未來財務與營運表現的預期，以及其他關於我們計畫、前景與預期的陳述。

These statements are not promises or guarantees and are subject to risks and uncertainties, which could cause them to differ materially from actual results. Information concerning those risks is available in our earnings press release distributed after the market closed today and in our SEC filings. We undertake no obligation to update forward-looking statements, except as required by law.

這些陳述並非承諾或保證，且受風險與不確定性影響，可能導致實際結果與前瞻性陳述存在重大差異。有關上述風險的資訊，載於我們今日收盤後發布的財報新聞稿以及我們向 SEC 提交的文件中。除法律要求外，我們不承擔更新前瞻性陳述之義務。

Further, during the course today's call, we will refer to certain adjusted financial measures. These non-GAAP financial measures should be considered in addition to, not as a substitute for or in isolation from GAAP measures. Additional information about these non-GAAP measures, including reconciliation of non-GAAP to comparable GAAP measures is included in our press release and investor presentation provided today.

此外，在今天電話會議進行期間，我們將提及若干經調整的財務衡量指標。這些非 GAAP 財務衡量指標應與 GAAP 指標一併考量，而非作為其替代，亦不應孤立解讀。關於這些非 GAAP 指標的更多資訊（包括非 GAAP 與可比 GAAP 指標之調節表）已包含於我們今日提供的新聞稿與投資人簡報中。

Our press release, investor presentation and other earnings materials are available on our Investor Relations website at investors.palantir.com. Over the course of the call, we will refer to various growth rates when discussing our business. These rates reflect year-over-year comparisons unless otherwise stated.

我們的新聞稿、投資人簡報及其他財報資料可於投資人關係網站 investors.palantir.com 取得。在本次電話會議中，我們在討論業務時將引用各種成長率。除非另有說明，這些成長率均為年對年比較。

Joining me on today's call are Alex Karp, Chief Executive Officer; Shyam Sankar, Chief Technology Officer; Dave Glazer, Chief Financial Officer; and Ryan Taylor, Chief Revenue Officer and Chief Legal Officer.

今天與我一同出席電話會議的有：執行長 Alex Karp；技術長 Shyam Sankar；財務長 Dave Glazer；以及營收長兼法務長 Ryan Taylor。

I'll now turn it over to Ryan to start the call.

接下來我把時間交給 Ryan，請他開始本次電話會議。

Our Q2 results are unprecedented, but entirely unsurprising as the abrupt market shift in LLMs that we've been warning you about for years is now here. We delivered 93% year-over-year revenue growth, our highest ever. The story of this quarter is once again our US business. It now comprises over 81% of total revenue and grew 115% year-over-year and 23% sequentially.

我們第二季的業績前所未見，但完全不令人意外，因為我們多年來一直提醒各位的 LLM 市場突變，如今已然到來。我們實現了 93% 的年對年營收成長，創下歷史新高。本季的重點再次是我們的美國業務。目前美國業務已占總營收逾 81%，年對年成長 115%，季對季成長 23%。

Our US commercial revenue growth accelerated to 149% year-over-year and 28% sequentially. And our US government revenue grew remarkable 90% year-over-year and 18% sequentially. These top line results are accompanied by a Rule of 40 score of 155% and $1.22 billion of adjusted free cash flow.

我們的美國商業營收成長加速至年對年 149%、季對季 28%。而我們的美國政府營收則大幅成長，年對年 90%、季對季 18%。在這些營收表現之下，我們的 Rule of 40 分數達到 155%，並產生 12.2 億美元的經調整自由現金流。

We closed 220 deals worth $1 million or more. of which 98 deals were worth $5 million or more, and 70 deals were worth $10 million or more, record highs across the Board. These results are a clear indication of the profound value, we've unlocked both for and with our customers who dared to cross the chasm with us.

我們完成了 220 筆金額達 100 萬美元以上的交易，其中 98 筆為 500 萬美元以上、70 筆為 1,000 萬美元以上，全面創下歷史新高。這些成果清楚顯示：我們與那些敢於與我們一同跨越鴻溝的客戶，已為他們、也與他們一起，釋放出深遠的價值。

In contrast, enterprises that are not using Palantir are seeing their token meters spinning endlessly just to get slope without any correlation to value. This token model may be working for the labs, but it is not working for anyone else. It's breaking corporate budgets without results to justify the expense, and worse companies are paying to give away their most important secrets, the very basis for their competitive advantage ultimately contributing to the commoditization of their own businesses as their Secrets become the training data embedded in the foundations of all future models.

相較之下，未使用 Palantir 的企業，正看著他們的 token 計量表無止盡地轉動，只為了取得一些斜率（成長曲線），卻與價值毫無關聯。這種 token 模式或許對實驗室有效，但對其他任何人都行不通。它在沒有成果可證明支出合理性的情況下，正在擊穿企業預算；更糟的是，企業還在付費把自己最重要的祕密——也就是其競爭優勢的根本——拱手讓人，最終促成自身業務的商品化，因為他們的祕密成了訓練資料，被嵌入所有未來模型的基礎之中。

On our side of the chasm, what enterprises demand is AI sovereignty owning the operational definition of the data, logic, actions and security of their enterprise. An organization's data is its treasure. In its richness is the alpha. We are fully aligned with our customers, building the stack that enables the compounding of their alpha.

在鴻溝的另一側，企業所要求的是 AI 主權——擁有其企業資料、邏輯、行動與安全性的營運定義權。一個組織的資料就是它的寶藏。其豐富性之中蘊含 alpha（超額報酬）。我們與客戶完全同向，打造能讓他們的 alpha 持續複利累積的技術堆疊。

Our deep alignment allows our customers' ambitions and to become one. As Kirkland and Ellis highlighted, through our work with Palantir, we have built a new operating model for legal services, one that setilizes and compounds the expertise of our most senior lawyers what used to take days for a lawyer to analyze, discuss and draft now happens in minutes. This will be impossible without the ontology.

我們深度的同向一致，使客戶的雄心與我們的雄心合而為一。正如 Kirkland & Ellis 所強調，透過與 Palantir 的合作，我們為法律服務建立了一種新的營運模式——能將最資深律師的專業加以系統化並複利放大；過去律師需要數天才能完成的分析、討論與起草，如今在數分鐘內即可完成。沒有本體（ontology），這一切都不可能實現。

We do not see this as a vendor relationship or a one-off endeavor. We think this is a revolutionary change in how our work gets done. This is what we do with our customers across industries and the deals we are closing are a testament to the monumental shift in the AI market that's underway as we speak.

我們不把這視為供應商關係或一次性的專案。我們認為這是工作完成方式的一場革命性變革。這正是我們與各行各業客戶共同在做的事，而我們正在簽下的交易，正印證了 AI 市場正在發生的巨大轉變——此刻正在進行中。

In our US commercial business, we closed $2.1 billion in TCV with a 271% year-over-year growth rate on a dollar-weighted duration basis. A multinational technology company began working with us in the fourth quarter of last year at one operating company and expanded on their success with our platform to deliver revolutionary impact across their full portfolio converting to a three-year nearly $370 million deal last quarter.

在我們的美國商業業務中，我們完成了 21 億美元的 TCV（合約總價值），以金額加權的合約期間口徑計算，年對年成長率達 271%。一家跨國科技公司自去年第四季起，先在其一個營運公司與我們合作，並在我們平台上取得成功後擴大導入，為其完整投資組合帶來革命性影響，並於上季轉換為一筆為期三年、接近 3.7 億美元的合約。

Customers are decisive and bold about taking the next step with Palantir. A global asset management firm started working with us in Q1, then converted last quarter to a year $35 million TCV deal spanning asset management automation and investment life cycle intelligence across four verticals. After an agent camp in May, a global software and services company signed an initial $15 million five-month deal last quarter, and a leading nonprofit health system signed a pilot at the end of 2025 and then last quarter converted to a three-year partnership at $37 million TCV.

客戶在與 Palantir 邁向下一步時，展現出果斷與大膽。一家全球資產管理公司於第一季開始與我們合作，並於上季轉換為一筆為期一年、TCV 3,500 萬美元的合約，涵蓋四個垂直領域的資產管理自動化與投資生命週期智慧。在 5 月的一次 agent camp 之後，一家全球軟體與服務公司於上季簽署了一筆初始 1,500 萬美元、為期五個月的合約；而一家領先的非營利醫療體系於 2025 年底簽署試點專案，並於上季轉換為一項為期三年的合作夥伴關係，TCV 為 3,700 萬美元。

Our US government business remains a source of extraordinary strength with momentum across both defense and civil. We continue to take great pride in our US government work, equipping our nation with the most advanced battle-tested AI capabilities. For Palantir, this is our calling. Our customers are making the decision to go deep with us with greater urgency and conviction than I've ever seen before, choosing AI sovereignty over dependency and compounding their alpha in a way that their competitors and adversaries will forever envy.

我們的美國政府業務依然是非凡實力的來源，在國防與民用兩端皆具動能。我們持續以我們的美國政府工作為榮，為我們的國家提供最先進、經實戰驗證的 AI 能力。對 Palantir 而言，這就是我們的使命。我從未見過客戶像現在這樣，以更高的急迫感與更堅定的信念決定與我們深度合作，選擇 AI 主權而非依賴，並以其競爭對手與對手勢力將永遠嫉羨的方式，讓他們的 alpha 持續複利累積。

I'll now turn it over to Shyam.

接下來我把時間交給 Shyam。

Thanks, Ryan. Ryan just talked about the incredible customer momentum behind sovereign AI. I want to spend some time on the underlying product investments that positioned us for this moment. AIP succeeded because it's the best most ergonomic environment for AI in the enterprise. It integrates mixed mammal AI teams across heterogeneous interdependent workflows and delivers the fastest implementations that turn tokens into real economic value for our customers in complex high stakes environments.

謝謝，Ryan。Ryan 剛才談到主權 AI 背後驚人的客戶動能。我想花一些時間談談讓我們站上這個時刻的底層產品投資。AIP 之所以成功，是因為它是企業中最優、最符合人體工學的 AI 環境。它能在異質且相互依存的工作流程中整合混合的人類與 AI 團隊，並以最快的導入速度，將 tokens 轉化為客戶在複雜且高風險環境中的真實經濟價值。

What makes it work is exquisite and layered, data integration and transformation, ontology and actions, security and audit, workflows, aging SDKs, agent orchestration with telemetry and observability, evals and customer-specific benchmarks, AIP Evolve and our latest investments in post-training, both supervised fine tuning and reinforcement learning.

讓它得以運作的要素精緻且層層堆疊：資料整合與轉換、本體與行動（actions）、安全與稽核、工作流程、成熟的 SDK、具備遙測與可觀測性的代理編排、評估（evals）與客戶專屬基準、AIP Evolve，以及我們在後訓練（post-training）上的最新投資，包括監督式微調與強化學習。

Every layer builds on our foundational primitives and every layer flows together. This infrastructure captures the rich operational telemetry to feed the compounding loop, an automated model factory that runs inside the customer security boundary and accumulates intelligence in weights they control. Last quarter, I said tokens are the new call and AIP is the train.

每一層都建立在我們的基礎原語之上，而每一層也彼此串流整合。這套基礎設施會擷取豐富的營運遙測資料以餵養複利循環——一座在客戶安全邊界內運行的自動化模型工廠，並在由客戶掌控的權重中累積智慧。上季我說過，tokens 是新的 call，而 AIP 是火車。

Now our customers can build their own locomotives. AIP is where your sovereign AI is built, deployed and compounded. We're excited for a new era not want a bench maxing but a bench making. The assumption that the frontier is actually the best performing is just not borne out in practice. Within 24 hours of bringing NemoTron/Ultra into our stacks, we found five production tasks were a standard nemotron/Ultra model without post-training beat frontier models.

現在，我們的客戶可以打造自己的機車頭。AIP 是打造、部署並複利累積您的主權 AI 的地方。我們對一個新時代感到振奮——不再是「刷榜極限」（bench maxing），而是「造榜」（bench making）。認為最前沿模型一定表現最佳的假設，在實務上根本不成立。在把 NemoTron/Ultra 納入我們的技術堆疊後 24 小時內，我們就發現有五個生產任務中，一個未經後訓練的標準 NemoTron/Ultra 模型就擊敗了前沿模型。

This underscores that a handful of common benchmarks can be gained. That era benchmaxing has ended. The new era is benchmaking. A customer-specific benchmark is not just a scorecard. It's a hill to climb. It's a normative orientation that directs your entire operational workflows and post training pipeline. It defines what better means on your terms for your business, with your strategy, and then everything optimizes against it continuously.

這凸顯出：少數幾個常見基準其實很容易被「刷」出來。那個刷榜極限（benchmaxing）的時代已經結束。新時代是造榜（benchmaking）。客戶專屬的基準不只是成績單。它是一座要攀登的山。它是一種規範性的指引，會導向您整套營運工作流程與後訓練管線。它用您的商業條件、您的策略來定義「更好」是什麼，然後所有事情都會持續朝它最佳化。

And because the benchmark is yours, the trade-offs become yours too. AIP gives you the control plane to trade cost, performance and latency against each other and to decide where you run your weights versus theirs, workflow by workflow, continuously. Now you can have a continuous improvement cycle that compounds your alpha into your weights. AIP was built for this.

而且因為基準是你的，取捨也就由你來決定。AIP 提供控制平面，讓你在成本、效能與延遲之間做權衡，並且逐一工作流程、持續地決定你的權重要在哪裡跑、他們的權重要在哪裡跑。現在你可以擁有一個持續改進的循環，把你的 alpha 複利累積到你的權重之中。AIP 就是為此而打造。

We continue to see that our product is winning head-to-head. The others are focused on productivity. We are laser-focused on turning tokens into real economic value for our customers. The reality is that the market has created far more intelligence than it has converted into value. A more powerful model does not solve this problem.

我們持續看到，我們的產品在正面對決中勝出。其他人專注在生產力。我們則高度聚焦於把 token 轉化為客戶的真實經濟價值。現實是，市場創造出的「智慧」遠多於它轉化成的價值。更強大的模型並不能解決這個問題。

The limiting factor is the rate of AIP deployment. A major Silicon Valley tech company recently ran a bake-off, a frontier lab and its deployment team against AIP and our forward deployed engineers. Remember, only Palantir has FDs. Everyone else has sparkling sales engineers. The lab picked a ticketing automation problem and failed to deliver anything of value against it. We built agent swarms for each of our customers' customers, proactively recommending marketing, packaging and pricing changes to drive revenue and utilization. This work converted into a $10 million ACV contract. The lab was shown the door.

限制因素是 AIP 的部署速度。最近，一家矽谷大型科技公司進行了一場對決，讓一家前沿實驗室及其部署團隊，對上 AIP 與我們的前線部署工程師（FD）。請記住，只有 Palantir 擁有 FD。其他人只有光鮮亮麗的售前工程師。該實驗室挑了一個工單（ticketing）自動化問題，卻未能交付任何有價值的成果。我們則為客戶的每一位客戶建立了代理群（agent swarms），主動建議行銷、包裝與定價調整，以推動營收與使用率。這項工作最終轉化為一份 1,000 萬美元 ACV（年度合約價值）的合約。那家實驗室被請出門了。

Same customer, same time line, same models. The only difference was AIP in Palantir's unique FD tradecraft, and it was determinative. It was an incredible quarter in US government, measured not just by 90% year-over-year revenue growth, but by mission impact.

同一個客戶、同一段時間線、同樣的模型。唯一的差別是 AIP 與 Palantir 獨特的 FD 實戰技藝（tradecraft），而這差別具有決定性。這是美國政府業務一個令人驚嘆的季度，不僅以年增 90% 的營收成長衡量，更以任務影響力衡量。

Maven continues to deliver for the joint force from the factory Florida the Foxhole.We had our first program in the Maven platform launched this past quarter, where a government program of record chose Maven as the platform that they will operate their program in taking advantage of our open data standards, ontology, developer tooling, peering, security and other platform primitives to go faster and deliver seamless experiences and capabilities to the department's chosen command and control platform.

Maven 持續為聯合作戰部隊交付成果，從工廠、佛羅里達到戰壕。我們在上一季度於 Maven 平台上啟動了第一個計畫：某個政府正式計畫（program of record）選擇 Maven 作為其運行計畫的平台，利用我們的開放資料標準、本體（ontology）、開發者工具、對等互聯（peering）、安全性與其他平台基元（primitives），以更快速度推進，並為該部門所選定的指揮與控制平台提供無縫的體驗與能力。

Maven has also continued to win as the developer and builder platform for the joint force with over 25,000 builders, uniform service members, civilians, contractors and companies are developing agents and applications in and on the platform at the speed of war. And for all that growth, our Department of our trailing 12-month revenue is still less than 25 basis points of the Pentagon's budget.

Maven 也持續作為聯合作戰部隊的開發與建置平台而勝出：超過 25,000 名建置者——現役軍人、文職人員、承包商與企業——正以戰爭速度在平台內與平台上開發代理與應用程式。即便有如此成長，我們來自國防部的過去 12 個月（TTM）營收仍不到五角大廈預算的 25 個基點。

Finally, last week, we held our first American Builder Summit in DC to celebrate the Americans who step forward to join the American tech fellowship and to let them make the case that AI is creating jobs and prosperity by sharing their stories and showing what they built. We created ATF because the most transformative applications of AI that we saw were being driven by people without traditional tech backgrounds on literal front lines and factory floors. We now have over 1,000 ATF grads.

最後，在上週，我們在華盛頓特區舉辦了第一屆 American Builder Summit，表彰那些挺身加入 American Tech Fellowship 的美國人，並讓他們分享故事、展示他們打造的成果，說明 AI 正在創造工作與繁榮。我們成立 ATF，是因為我們看到最具變革性的 AI 應用，往往由沒有傳統科技背景的人推動——他們就在真正的前線與工廠現場。目前我們已有超過 1,000 名 ATF 畢業生。

One of our speakers, who joined Tabet as a submarine parts manufacturer 13 years ago, straight on to the factory floor. He's a proud blue-collar worker who still turns wrenches for a living and he built an AI application that took production planning from 30 to 40 days down to less than 1. AI alone cannot do that. It takes AI in the hands of the American worker. The tribal knowledge earned through success and failure on the line, the insights only they have. The models are commodities, but the American worker is not.

我們的一位講者，13 年前加入 Tabet，擔任潛艦零件製造商，直接走上工廠產線。他是一位自豪的藍領工人，至今仍以扳手維生；而他打造了一個 AI 應用，把生產規劃從 30 到 40 天縮短到不到 1 天。單靠 AI 做不到這點。必須是 AI 掌握在美國工人手中。那是在產線上經由成功與失敗累積的部落知識（tribal knowledge），以及只有他們才擁有的洞見。模型是大宗商品，但美國工人不是。

I'll turn it over to Dave to take us through the numbers.

接下來我把時間交給 Dave，帶我們看一下數字。

Thanks, Shyam. We had a phenomenal second quarter delivering our highest ever reported year-over-year revenue growth rate of 93% and our highest ever adjusted free cash flow of $1.22 billion, representing a 63% margin and 115% growth year-over-year. We surpassed $1 billion milestones in GAAP net income, adjusted free cash flow and adjusted operating income.

謝謝，Shyam。我們第二季表現極為出色，繳出史上最高的年增營收成長率 93%，以及史上最高的調整後自由現金流 12.2 億美元，對應 63% 的利潤率，且年增 115%。我們在 GAAP 淨利、調整後自由現金流與調整後營業利益三項指標上都突破了 10 億美元里程碑。

Revenue in our US business grew 115% year-over-year and 23% sequentially in the second quarter. Our US commercial business accelerated to 149% year-over-year and 28% sequentially, and our US government business grew 90% year-over-year and 18% sequentially. We closed $2.132 billion of US commercial TCV bookings representing growth of 153% year-over-year and 81% sequentially, nearly $800 million above our prior highest US commercial bookings quarter.

我們美國業務第二季營收年增 115%，季增 23%。其中，美國商業業務加速至年增 149%、季增 28%；美國政府業務年增 90%、季增 18%。我們在美國商業端完成 21.32 億美元的 TCV（合約總價值）訂單，年增 153%、季增 81%，比我們先前最高的美國商業訂單季度高出將近 8 億美元。

We are seeing the immense demand of enterprises recognizing the need for sovereign AI to retain full control of their alpha. On the back of this exceptional continued strength in the US and accelerating demand for sovereign AI capabilities. We are raising our full year US commercial revenue guidance to an excess of $3.424 billion, representing a growth rate of at least 134%. We are also raising our full year 2026 revenue guidance midpoint to $8.154 billion, representing 80% growth year-over-year and 11-point increase over our full year 2026 revenue guidance from last quarter and our largest ever full year revenue guidance raise.

我們看到企業端的龐大需求：企業意識到需要主權 AI，才能保留對其 alpha 的完全控制權。在美國市場持續的卓越強勢，以及對主權 AI 能力需求加速的帶動下，我們將全年美國商業營收指引上調至超過 34.24 億美元，代表至少 134% 的成長率。我們也將 2026 全年營收指引的中位數上調至 81.54 億美元，代表年增 80%，較上季的 2026 全年營收指引中位數提高 11 個百分點，亦是我們史上最大幅度的全年營收指引上調。

Turning to our global top line results. Second quarter revenue grew 93% year-over-year and 19% sequentially to $1.935 billion. Second quarter US revenue grew 115% year-over-year and 23% sequentially to $1.573 billion. Revenue from our largest customers continues to expand. Second quarter trailing 12-month revenue from our top 20 customers increased 67% year-over-year to $124 million per customer.

接著看我們全球營收表現。第二季營收年增 93%、季增 19%，達 19.35 億美元。第二季美國營收年增 115%、季增 23%，達 15.73 億美元。來自我們最大客戶的營收持續擴張。第二季前 20 大客戶的過去 12 個月（TTM）營收年增 67%，平均每位客戶達 1.24 億美元。

Now moving to our commercial segment. Second quarter commercial revenue grew 110% year-over-year and 22% sequentially to $945 million. We closed $2.337 billion in commercial TCV bookings in the second quarter representing 118% growth year-over-year. Our AI platform continues to dominate the US market as the only real choice for operationalizing LLMs, particularly as more customers demand full ownership over the data, logic, actions and security of their enterprise.

現在來看我們的商業部門。第二季商業營收年增 110%、季增 22%，達 9.45 億美元。我們第二季完成 23.37 億美元的商業 TCV 訂單，年增 118%。我們的 AI 平台持續主導美國市場，成為將 LLM 落地營運（operationalizing）的唯一真正選擇，特別是在越來越多客戶要求對其企業的資料、邏輯、行動與安全性擁有完全所有權之際。

Second quarter US commercial revenue grew 149% year-over-year and 28% sequentially to $764 million. We closed a record-setting $2.132 billion of US commercial TCV bookings representing growth of 153% year-over-year. Over the past 12 months, we closed $5.964 billion of US commercial TCV bookings a 117% increase from the prior 12 months, highlighting the accelerating demand for AI that creates real operational value.

第二季美國商業營收年增149%、季增28%，達7.64億美元。我們締結創紀錄的21.32億美元美國商業TCV預訂，年增153%。過去12個月，我們完成59.64億美元的美國商業TCV預訂，較前12個月增加117%，凸顯能創造實質營運價值的AI需求正在加速。

Total remaining deal value in our US commercial business grew 124% year-over-year and 27% sequentially. Our US commercial customer count grew to 653 customers, refuting growth of 35% year-over-year and 6% sequentially. Second quarter international and commercial revenue grew 26% year-over-year and 2% sequentially to $182 million.

我們美國商業業務的剩餘交易總價值年增124%、季增27%。我們美國商業客戶數成長至653家，年增35%、季增6%。第二季國際與商業營收年增26%、季增2%，達1.82億美元。

Revenue on strategic commercial contracts was approximately $400,000 for the quarter representing 0.02% of overall revenue. We continue to expect revenue from these contracts to be less than $500,000 in each remaining quarter of this year.

本季策略性商業合約的營收約為40萬美元，占總營收的0.02%。我們仍預期今年剩餘各季來自這些合約的營收每季將低於50萬美元。

Shifting to our Government segment. Second quarter government revenue grew 79% year-over-year and 15% sequentially to $990 million. Second quarter US government revenue grew 90% year-over-year and 18% sequentially to $809 million. This growth was driven by continued execution in existing programs and new awards reflecting growing demand for our AI platform and government.

接著談政府部門。第二季政府營收年增79%、季增15%，達9.90億美元。第二季美國政府營收年增90%、季增18%，達8.09億美元。此成長來自既有專案的持續執行與新增標案，反映政府對我們AI平台的需求日益增加。

Second quarter international government revenue grew 42% year-over-year and 5% sequentially to $181 million. We closed $3.4 billion of TCV bookings, up 49% year-over-year on a dollar-weighted duration basis, TCV bookings grew 129% year-over-year. Net dollar retention was 157%, an increase of 700 basis points from last quarter. We ended the second quarter with $13.1 billion in total remaining deal value, an increase of 83% year-over-year and 11% sequentially and $4.9 billion in remaining performance obligations, an increase of 103% year-over-year and 10% sequentially.

第二季國際政府營收年增42%、季增5%，達1.81億美元。我們完成34億美元的TCV預訂；以金額加權的期間基礎計算，年增49%，TCV預訂年增129%。淨美元留存率為157%，較上季提高700個基點。第二季末，我們的剩餘交易總價值為131億美元，年增83%、季增11%；剩餘履約義務（RPO）為49億美元，年增103%、季增10%。

As a reminder, RPO is primarily comprised of our commercial business as it does not take into account contracts with initial term of less than 12 months and contractual obligations that fall beyond termination for convenience clauses, both of which are common in most of our government business.

提醒一下，RPO主要由我們的商業業務構成，因其未納入初始期限少於12個月的合約，以及超出「為便利而終止」條款所涵蓋範圍之外的契約義務；這兩者在我們多數政府業務中都很常見。

Turning to margin and expense. Adjusted gross margin, which excludes stock-based compensation expense, was 86% for the quarter and reflects an increase in costs associated with taking on cloud hosting for one of our government customers. While this change led to a higher cost of revenue in Q2 -- going forward, we believe it will power faster time to value, drive greater efficiency, provide greater cost certainty to the customer and enable us to expand their future workflows.

接著談毛利與費用。本季調整後毛利率（不含以股份為基礎之薪酬費用）為86%，反映我們為其中一位政府客戶承擔雲端託管所帶來的成本增加。雖然此變動使第二季營收成本提高——但展望未來，我們相信這將加速價值實現、提升效率、為客戶提供更高的成本確定性，並使我們能擴展其未來工作流程。

Adjusted income from operations which excludes stock-based compensation expense and related employer payroll taxes was $1.194 billion in the second quarter, representing an adjusted operating margin of 62%. Q2 adjusted expense was $741 million, up 14% sequentially and 37% year-over-year, primarily driven by the continued investment in our AI platform and technical hiring.

第二季調整後營業利益（不含以股份為基礎之薪酬費用及相關雇主薪資稅）為11.94億美元，調整後營業利益率為62%。第二季調整後費用為7.41億美元，季增14%、年增37%，主要由於持續投資我們的AI平台與技術人才招募。

As in prior years, we expect a significant ramp in expense in the third quarter due to the seasonality of new hire starts and other product and marketing initiatives. We remain committed to investing in the most technical talent as well as R&D for product pipeline and sovereign AI efforts, all diluting on our goals of sustained GAAP profitability.

與往年相同，我們預期第三季費用將顯著攀升，原因在於新進人員到職的季節性，以及其他產品與行銷計畫。我們仍致力於投資最頂尖的技術人才，以及產品管線的研發與主權AI相關工作，同時也不偏離我們維持GAAP持續獲利的目標。

Second quarter GAAP operating income was $912 million, representing a 47% margin. Second quarter GAAP net income was $1.062 billion, representing a 55% margin. Second quarter stock-based comp expense was $265 million and equity related employer payroll tax expense was $17 million. Second quarter GAAP earnings per share was $0.41, second quarter adjusted earnings per share was $0.41.

第二季GAAP營業利益為9.12億美元，營業利益率為47%。第二季GAAP淨利為10.62億美元，淨利率為55%。第二季以股份為基礎之薪酬費用為2.65億美元，與股權相關的雇主薪資稅費用為1,700萬美元。第二季GAAP每股盈餘為0.41美元，第二季調整後每股盈餘為0.41美元。

Unrealized gains from our holdings and SpaceX resulted in a $0.03 tailwind to GAAP EPS and a $0.02 tailwind to adjusted EPS in the quarter. Additionally, our combined revenue growth and adjusted operating margin accelerated to 155% in the second quarter, a 10 point increase to our Rule of 40 score from the prior quarter and our 12th consecutive quarter of an expanding rule of 40 score.

我們持有的投資與SpaceX的未實現收益，使本季GAAP每股盈餘增加0.03美元，調整後每股盈餘增加0.02美元。此外，我們的營收成長與調整後營業利益率合計在第二季加速至155%，較上季Rule of 40分數提高10點，並且是連續第12季Rule of 40分數擴張。

Turning to our cash flow. In the second quarter, we generated $1.216 billion in cash from operations and $1.22 billion in adjusted free cash flow, representing margins of 63%. We ended the quarter with $9.2 billion in cash, cash equivalents and short-term US treasury securities.

接著談現金流。第二季我們產生12.16億美元的營運現金流，以及12.20億美元的調整後自由現金流，對應的利潤率為63%。季末我們持有92億美元的現金、約當現金及美國短期國庫券。

Now turning to our outlook. For Q3 2026, we expect revenue of between $2.16 billion and $2.164 billion and adjusted income from operations of between $1.292 billion and $1.296 billion. For full year 2026, we are raising our revenue guidance to between $8.15 billion and $8.158 billion. We're raising our US commercial revenue guidance to an excess of $3.424 billion, representing a growth rate of at least 134%. We're raising our adjusted income from operations guidance to between $4.889 billion and $4.897 billion. We are raising our adjusted free cash flow guidance to between $4.5 billion and $4.7 billion, and we continue to expect GAAP operating income and net income in each quarter of this year.

接著談展望。針對2026年第三季，我們預期營收介於21.60億至21.64億美元之間，調整後營業利益介於12.92億至12.96億美元之間。針對2026年全年，我們將營收指引上調至81.50億至81.58億美元之間。我們將美國商業營收指引上調至超過34.24億美元，代表至少134%的成長率。我們將調整後營業利益指引上調至48.89億至48.97億美元之間。我們將調整後自由現金流指引上調至45億至47億美元之間，並且我們仍預期今年每一季皆將有GAAP營業利益與淨利。

With that, I'll turn it over to Alex for a few remarks, and then Ana will kick off the Q&A.

接下來我把時間交給Alex做幾點補充，之後Ana將開始Q&A。

Obviously, we are loving these results and loving what they mean for our customers and broadly speaking, the West. So reflections on how we got to 93% aggregate growth just under 150% growth in US commercial and an aggregate growth of 115% in America, which is astonishing even surpassing the already anomalous results we've posted in the past and at a very significant scale.

顯然，我們非常喜歡這些成果，也喜歡它們對我們客戶以及更廣泛而言對西方所代表的意義。因此，回顧我們如何達到93%的整體成長、美國商業接近150%的成長，以及美國整體115%的成長——這令人驚嘆，甚至超越我們過去已屬異常的成果，而且是在非常可觀的規模之下。

And the story really does begin at the beginning when we dedicated ourselves to our most important partners in the US government, and we built products to deliver value for them. We delivered those value for them by looking at the world in its naked state. We did not have soft -- we did not have AI available. We had to work with NLP.

而故事確實要從一開始說起：當我們把自己奉獻給美國政府最重要的合作夥伴，並打造產品為他們交付價值。我們透過以世界最赤裸的狀態來看待它，為他們交付那些價值。我們沒有「軟」——我們當時沒有AI可用。我們必須使用NLP來工作。

So we had to develop for deployed engineer model to extend the technology and deliver value, the nascent version of Ontology was developed, Shyam, Aki, others, strapped Blackberries around their head and made the code work in sensitive environments.

因此我們必須發展「派駐工程師」模式來延伸技術並交付價值；Ontology的雛形也因此被開發出來。Shyam、Aki以及其他人把BlackBerry綁在頭上，讓程式碼能在敏感環境中運作。

And what we learned and what was built into this company is that there are things, values, structures that are more important than purely extracting value from a client, and we rejected the way in which we were being taught in Silicon Valley to build a software company at the time Palantir, of course, is now both infrastructure software, FTEs, orchestration and business know-how. It's a completely different hybrid but at the time, we were being told our job was to trick the clients into giving us money for something that made them attached to us, but really added no value. So essentially a parasitic model.

而我們所學到、也被內建進這家公司的是：有些事情——價值、結構——比單純從客戶身上榨取價值更重要；我們拒絕了當時在矽谷被教導的那種打造軟體公司的方式。當然，Palantir如今同時是基礎設施軟體、全職人力（FTE）、編排能力與商業專業知識。這是一種完全不同的混合體；但在當時，我們被告知我們的工作是哄騙客戶付錢給我們，買一個讓他們對我們產生依附、但其實不帶來任何價值的東西。所以本質上是一種寄生式模式。

And in the rejection of that, we fully aligned with our partners. Now we -- to do that, as we move through the years, we built -- we built PJ, Foundry, Gaya, Maven, Ontology, AIP. Now we're taking the AIP stack and extending it for sovereign AI, which requires us to be able to orchestrate and fine-tune models to provide a completely sovereign stack to our partners. But what is the philosophical importance of that, we are offering a present that augurs to a future that we want to live in. what does that future look like?

而在拒絕那件事上，我們與合作夥伴完全一致。現在我們——為了做到這一點，隨著時間推進，我們建立——我們建立了 PJ、Foundry、Gaya、Maven、Ontology、AIP。現在我們正在把 AIP 技術堆疊延伸到主權 AI，這要求我們能夠協調並微調模型，為合作夥伴提供一個完全主權的堆疊。但這在哲學上的重要性是什麼？我們是在提供一份禮物，預示著我們想要生活其中的未來。那個未來長什麼樣子？

We have more rights in the PG frame. There's -- it's safer in the sovereign AI frame, which is arguably by far, the most important because -- all these other things are downstream from GDP growth and GDP Health and what if we transform America into the only democracy that actually grows where production is more efficient and manufacturing actually happens.

在 PG 的框架下，我們擁有更多權利。在主權 AI 的框架下更安全，而這可以說是迄今最重要的，因為——其他所有事情都源自 GDP 成長與 GDP 的健康；如果我們把美國轉變成唯一一個真正成長的民主國家，讓生產更有效率、製造業真正發生，會怎樣？

What is that frame? That frame is not -- you are going to buy into a future where you have new job where adversaries win. And everybody who does win is a small, tiny group of people living in a tiny place, that someone believes because they eat vegetables and they don't support war fighters that they deserve to have the total means of production of this country. And the rest of us should just sit back and absorb the cost of that revolution, which we're paying for. How are we paying for it?

那個框架是什麼？那個框架不是——你要買進一個你有新工作、但對手獲勝的未來。而所有真正贏的人，是一小撮、極小的一群人，住在一個很小的地方；有人相信，因為他們吃蔬菜、而且不支持戰士，所以他們就應該擁有這個國家的全部生產資料。而我們其他人只要坐著，吸收那場革命的成本——而我們正在為此買單。我們是怎麼付這筆錢的？

In the enterprise context, people sign up for token self pleasurings -- and those -- and that -- a real cost, like other forms of self-pleasuring where you are paying for the right for them to migrate your IP, your know-how, your expertise to their model so that they can build a competitive business that doesn't require your business for people.

在企業情境中，人們會去簽下以代幣為基礎的自我取悅——而那——而那是——一個真實的成本，就像其他形式的自我取悅一樣：你是在付費，換取他們把你的 IP、你的 know-how、你的專業能力遷移到他們的模型裡，讓他們能建立一個具競爭力、但不需要你的企業就能運作的生意。

And why are they doing it? It's actually being done for what they believe are moral reasons. They are superior to you. They deserve to colonize your enterprise, you deserve to be colonized. And then Palantir and a, it's interesting, it doesn't work as well or as efficient purely on the alpha side as having an application layer owning your compute witness.

那他們為什麼要這麼做？其實他們是出於他們自認為的道德理由在做。他們比你更優越。他們應該殖民你的企業，而你應該被殖民。然後 Palantir——而且很有意思的是，若純粹只看 alpha 端，它的效果或效率不如讓應用層擁有你的運算見證（compute witness）。

We built a partnership with Nvidia. We're expanding our application layer. We are going to enter the market and already entering it in the classified space, as Shyam alluded to, of fine-tuning models. So the model is actually fine-tuned by us in our enterprise on a Nvidia stack outperform frontier models. And you own the weights, you own the alpha, you own everything. Every single enterprise in this country is going to either look at doing this, find ways of doing it or at least avoid the alternative of unprotected interaction with Frontier models. This is very dangerous. You're worried about this in high school.

我們與 Nvidia 建立了合作夥伴關係。我們正在擴展我們的應用層。我們將進入市場——而且如 Shyam 所提到的，我們已經在機密領域開始進入——做模型微調。因此，模型實際上由我們在企業內、在 Nvidia 的堆疊上完成微調，表現優於前沿模型（frontier models）。而你擁有權重，你擁有 alpha，你擁有一切。這個國家的每一家企業都將要麼考慮這麼做、找到方法這麼做，或至少避免另一種選擇：在沒有保護的情況下與前沿模型互動。這非常危險。你在高中時就擔心過這件事。

And now you're learning about it in your enterprise. And talent here, we are in the front of driving this revolution I am driving the business to grow at a rate equal or above to what we have in US commercial for the next 18 months. which is a very high goal, but it is one we can actually get to because we are fully aligned with what's right and what's good and what actually works well in an enterprise. And for the first time, people believe us -- and if you didn't believe us, you can believe 149% growth in the US, a Rule of 40 that's 155%, 93% aggregate growth and 90% growth in US com with 62%, 63% of free cash flow margins.

而現在你正在你的企業裡學到它。至於人才方面，我們站在推動這場革命的最前線；我正在推動業務在未來 18 個月以不低於我們在美國商業市場的速度成長。這是一個非常高的目標，但我們確實能達成，因為我們與什麼是正確的、什麼是好的、以及在企業中真正有效的做法完全一致。而且第一次，人們相信我們——如果你不相信我們，你可以相信美國 149% 的成長、Rule of 40 達到 155%、整體 93% 的成長，以及美國商業 90% 的成長，並且自由現金流利潤率達到 62%、63%。

People thought we wouldn't be profitable. So this is one of the more exciting times to be at Palantir. It's one of the more exciting times to participate in Palantir. And for everyone on the sidelines, you got to get off the sidelines. This is a revolution that will affect the sovereign revolution, where you stand in it will affect your livelihood, the livelihood of the people you care and whether America and the West win. We cannot regress to a thin philosophical model where only a small group of people who think very differently than most of us actually absorb all of the revenue and value in our business and transfer all the dangers to us.

人們曾以為我們不會獲利。所以這是待在 Palantir 最令人興奮的時刻之一。這也是參與 Palantir 最令人興奮的時刻之一。而對所有在場邊的人，你們得離開場邊。這是一場將影響主權革命的革命；你站在哪一邊，將影響你的生計、你在乎之人的生計，以及美國與西方是否能贏。我們不能倒退到一個單薄的哲學模型：只有一小群與我們大多數人想法截然不同的人，吸收我們業務中所有收入與價值，並把所有風險轉嫁給我們。

And that's what this revolution is about, and it's extremely motivating for those of us at Palantir. Thank you.

而這就是這場革命的核心，這對我們 Palantir 的人極具激勵作用。謝謝。

Thanks, Alex. Our first question is from Dan with Yorkville Ives. Dan, please turn on your camera and then you receive a prompt to unmute your line.

謝謝你，Alex。我們的第一個問題來自 Yorkville Ives 的 Dan。Dan，請打開你的攝影機，然後你會收到提示以解除靜音。

Where's the prompt? Well, while we're waiting, you can be entertained.

提示在哪裡？嗯，在我們等待的同時，你可以先被娛樂一下。

Maybe we can circle back to Dan. Our next question's from Mariana with Bank of America. Mariana, please turn on your camera, and then you'll receive a prompt to unmute your line

也許我們可以稍後再回到 Dan。下一個問題來自美國銀行（Bank of America）的 Mariana。Mariana，請打開你的攝影機，然後你會收到提示以解除靜音。

I think I'm good. Can you walk through at the sovereignty boot camp, what did you learn with talking to customers that may be you weren't expecting? I mean, obviously, just an overwhelming sort of group of executives. Can you just talk about that, Alex?

我想我這邊沒問題。你能談談在主權訓練營（sovereignty boot camp）裡，和客戶交流時你學到了哪些你原本沒預期到的事嗎？我的意思是，顯然來了一大群高階主管。Alex，你能談談那個情況嗎？

Well, first of all, for those of you not in the know, we did a sovereign boot camp after this kind of revolution exploded -- and just to give the backdrop here, two years ago, we were -- we spent four or five months, Sasha, who runs this organizing AIPCon. This was much more like, hey, let's provide our buddies over to lunch.

嗯，首先，對於不熟悉的人，我們在這種革命爆發之後辦了一個主權訓練營——先交代一下背景：兩年前，我們——我們花了四、五個月，Sasha（他負責組織 AIPCon）——那時更像是：嘿，把我們的朋友找來吃個午餐。

And then all of a sudden, we started getting bombarded by people. People we invited, people we didn't invite all levels of the business. So like when you're working in enterprise, it's really important that operational people are interested. So it was like CEOs, operational leads and there's a huge educational component and Shyam talks about this a lot, like we -- people understand that they need a way of controlling their alpha -- they understand broadly that token maxing is at their own cost. And they certainly understand that token Maxine is leading to them, transferring their data, their prompts, the way they run their business, their expertise to third party.

然後突然之間，我們開始被人潮轟炸。我們邀請的人、沒邀請的人，來自企業各個層級。所以當你在做企業業務時，營運端的人有興趣是非常重要的。因此來的人有 CEO、營運負責人，而且有很大的教育成分；Shyam 常常談到這點：人們明白他們需要一種方式來控制他們的 alpha——他們大致理解，最大化代幣（token maxing）是以他們自身成本為代價。而且他們當然也明白，最大化代幣會導致他們把資料、提示詞（prompts）、他們經營業務的方式、以及專業能力轉移給第三方。

But they don't they need education on what they can do about that with us preferably, but also without us, how do you do contracts? How do you work with open way models? How do you work with closed wave models? How does this work in otology is ontology the protective layer that they've been told, -- does it create value the way they -- how we just look in their own business and how would they work with the compute stack?

但他們——他們需要被教育的是：他們能對此做些什麼，最好是和我們一起做，但即使沒有我們也行；合約要怎麼簽？要怎麼使用開放權重模型（open weight models）？要怎麼使用封閉權重模型（closed weight models）？這在本體（ontology）裡如何運作——本體是不是他們被告知的那個保護層？——它是否能像他們所想的那樣創造價值——我們如何在他們自己的業務中看待它——以及他們要如何與運算堆疊（compute stack）協作？

And so there's just this massive demand and we're in the business of educating people with our customers and others. But it was a super group of people, both in terms of the kind of people showed up, the demand for it and also people we've not worked for.

因此需求非常龐大，而我們的業務之一就是與客戶及其他人一起教育市場。但那是一群超級陣容的人——不論是出席者的層級、對活動的需求，還是一些我們以前沒有合作過的人。

By the way, one of the reasons the NDR number is so strong, ridiculously strong. I mean people always write these things about customer adoption and maybe -- but the NDR number is enormously strong that is also going to shift as hard as to believe become even more positive because some of our older partners we haven't really interacted with, they also showed up -- they're like, oh, okay, now we get why we would need you and not just foundry, they're migrating across our stack.

順帶一提，NDR 數字之所以這麼強，強到離譜，是有原因的。我的意思是，人們總會寫一些關於客戶採用率之類的東西，或許——但 NDR 數字極其強勁，而且也將會出現轉變，雖然很難相信，但會變得更正面，因為我們一些較早期、其實沒怎麼互動的合作夥伴也出現了——他們就像，喔，好吧，現在我們明白為什麼需要你們，而不只是 Foundry，他們正在跨越我們的整個技術堆疊進行遷移。

So customers that are only using foundry now in oncology, now want to be part of the cavern AI stack. I would say, last not least, you're asking the internal version -- external version internally, recruiting, retention, excitement at Palantir. It's -- I mean, I'm very excited. I think the people around this table are very excited. The legal department is exciting. I mean that hasn't happened. It's like that doesn't happen. Like they're out like Rob on. So it's just -- it's more fun -- so yes, there's just -- that's the way this went down. And I think this is going to -- this is the way beginning.

所以，現在只在腫瘤領域使用 Foundry 的客戶，也想成為 Cavern AI 技術堆疊的一部分。我想說，最後但同樣重要的是，你在問內部版本——對外版本在內部的呈現：在 Palantir 的招募、留任、以及興奮感。這——我的意思是，我非常興奮。我覺得坐在這張桌子旁的人都非常興奮。法務部門也很興奮。我的意思是，這以前沒發生過。就像那種事不會發生。就像他們也像 Rob 一樣衝在前面。所以就是——更有趣——所以是的，這就是——事情就是這樣發展的。而我認為這將會——這就是開端。

So the way at least we think about this internally is what portion of the market is available to people who want to create value, you mean create value and keep it -- that portion of the market has gone from a small portion of the market where we were doing were to like a large part of the US GDP. And that's why we need partners.

所以至少我們在內部思考的方式是：市場中有多少部分是提供給那些想要創造價值——也就是創造價值並把價值留住——的人；那個市場部分已經從我們過去所做的、只占市場很小一部分，變成像是美國 GDP 的很大一部分。這也是為什麼我們需要合作夥伴。

Behind the scenes now we're trying to find partners -- now partners, we need technically, exceedingly competent partners. Partners doesn't mean a vessel. We don't have to grant every issue. We don't even have to agree in every client. They can occasionally compete against us.

在幕後，我們現在正在尋找合作夥伴——而且是我們在技術上需要的、極度勝任的合作夥伴。合作夥伴不代表一個容器。我們不必在每個議題上都讓步。我們甚至不必在每個客戶上都意見一致。他們偶爾也可以和我們競爭。

We've seen this in the defense tech stuff. Shyam like the approach to Defense Tech where we partner with people. Partner doesn't mean we agree, sometimes we compete, but it means in in a similar direction allows us to scale.

我們在國防科技的事情上已經看過這種情況。Shyam 提到我們在國防科技上的做法，是與人合作。合作夥伴不代表我們都同意；有時我們競爭，但代表在相近的方向上前進，讓我們能夠擴大規模。

So those things are going to be a very big important part of like essentially the guide. Why am I pushing the company to grow not to just at the end of the year, but next year, it's because that also forces us to find ways to scale to meet the demand that's out there.

所以這些事情將會是指引中非常重要的一大部分。我為什麼推動公司成長，不只是到年底，而是到明年，是因為那也迫使我們找到擴大規模的方法，以滿足外部存在的需求。

Thanks, Alex. Our next question is from Mariana with Bank of America.

謝謝，Alex。下一個問題來自美國銀行的 Mariana。

Good afternoon, everyone. So a follow-up to Dan's question. When all the AI revolution started, it was really clear for enterprises that data and proprietary data and how you train your models what's going to be the key but then we're like three years into that revolution, and now everyone started to realize owning my data and wherever our data is important.

各位下午好。我想接續 Dan 的問題追問一下。當 AI 革命剛開始時，對企業來說非常清楚：資料、專有資料，以及你如何訓練模型將會是關鍵；但現在我們已經進入這場革命大約三年了，而現在每個人開始意識到，擁有我的資料，以及我們的資料放在哪裡都很重要。

What happened there? Why you think that you position yourself then in a different approach to AI that enterprises were unable to see and why these numbers that reflect that you're the winner of AI today. It wasn't that clear for any other software application back then.

中間發生了什麼？為什麼你認為你當時在 AI 上採取了不同的方法、而企業卻看不出來？以及為什麼這些數字反映出你們是當今 AI 的贏家。在當時，對任何其他軟體應用來說都沒有那麼明顯。

Well, you can kind of divide it up into two parts. There's the first part is efficacy. And then the second part is efficiency. That's not quite the right word, but it's like how do you scale it in the zero to 1 phase, it's much more important to focus on the application layer. Like, okay, this new thing has happened, how do we turn that into economic value.

嗯，你可以把它大致分成兩個部分。第一部分是效能（efficacy）。第二部分是效率（efficiency）。那不完全是最精準的詞，但大概是：在從 0 到 1 的階段，你要如何把它擴展起來；在那個階段，更重要的是專注在應用層。像是，好，這個新事物發生了，我們要如何把它轉化成經濟價值。

And then as people started to experience the economic value and as time started happening, you started to see that some of the people who were partners out there were building things that were competitive to you.

然後當人們開始體驗到經濟價值、時間也推進之後，你開始看到外面一些原本是合作夥伴的人，正在打造與你具有競爭性的東西。

And I think that took some time to kind of seep into the psyche and mindset of wait a second. This is maybe not -- now I know this thing is valuable in the right hands on the right platform, but I also am going to need to control the weight that the alpha that is being generated isn't simply the data that's resident in my enterprise. It's also the media, the reasoning traces, the exhaust, the usage of this, which I don't yet have mechanisms to control and now I understand that it's actually probably more valuable than just the data in my enterprise. And that's been a clarion call I think, for the market over the last quarter, two quarters.

我認為這需要一些時間，才慢慢滲透到大家的心理與思維裡：等一下。這也許不是——現在我知道這東西在對的人手上、在對的平台上是有價值的，但我也需要控制權重，確保所產生的 alpha 不只是駐留在我企業內的資料。它也包括媒體、推理軌跡、排放物（exhaust）、以及這些東西的使用情況，而我目前還沒有機制去控制；而現在我理解到，這些其實可能比我企業內的資料更有價值。而我認為，這在過去一季、兩季對市場而言是一記警鐘。

There's also the question implicit in your question is why did we get this right. And again, I think it's -- we are actually fully aligned with our partners. Sometimes we make decisions like that are against our economic interest, like we're supporting lots of institutions in Europe, the growth sucks.

你問題裡其實也隱含了另一個問題：為什麼我們做對了。再說一次，我認為——我們其實與合作夥伴是完全一致的。有時我們會做出一些違背自身經濟利益的決策，例如我們在歐洲支持很多機構，成長很糟。

I mean cleaned ascent institutions. But without our products, they would have rampant terrorism and their migration problems, and the results would be 10 times worse -- it's not actually in our economic interest anymore to do this, but we still do it. And it's because we actually are believers for better or worse I would say also, this is a company that, from beginning from inception, has valued artistic insights, meaning you can't model something purely on science. You have to have an aesthetic or artistic appreciation for it.

我是說，那些被清理過的上升機構。但如果沒有我們的產品，他們會面臨猖獗的恐怖主義與移民問題，而結果會糟 10 倍——這其實已經不符合我們的經濟利益，但我們仍然在做。而這是因為我們確實是信徒——不管好壞我也會這麼說——這家公司從一開始、從創立之初，就重視藝術性的洞見，意思是你不能純粹用科學去建模某件事。你必須對它有一種審美或藝術性的理解。

And we've made huge bets. Everyone sitting at this table and many, many hundreds of people at Palantir have essentially artistic insights. We've always viewed ourselves -- we've always said we're in a colony of artists and people assume that means we're just difficult, and that's also true.

而我們下了很大的賭注。坐在這張桌子旁的每個人，以及 Palantir 裡許許多多、數以百計的人，本質上都有藝術性的洞見。我們一直把自己看作——我們一直說我們是一個由藝術家組成的群落，而人們以為那代表我們只是很難搞，而那也是真的。

But it's also we value insights that are way before anyone else would see them and we build major parts of our business. That's very hard for normal business to do because, I mean, one of the jokes running around Panther is we can definitely meet our guide next year if we get paid for all the people copying us. So we got a small portion of people copy of the funds for the copiers, we do very well. Normal businesses, again, no critique here are built around -- there was a playbook. We executed on that playbook.

但同時，我們也重視那些遠早於其他人能看見的洞見，並以此打造我們業務的主要部分。這對一般企業來說非常難做到，因為——我的意思是，Palantir 內部流傳的一個笑話是：如果所有抄我們的人都付費，我們明年肯定能達成指引。所以只要有一小部分抄 Foundry 的人付費，我們就會做得很好。一般企業——再次強調，這不是批評——是建立在：有一套劇本。我們照著那套劇本執行。

And we're in the non playbook world. So executing on a playbook that works 5, 10 years ago, essentially build parasetic software and monetize it, that doesn't work now. And there's hundreds of variants of that, but that is a central advantage we have. We are a colony, believers and artists that are very motivated to drive value. And that sets us aside much more than I would have imagined 10 years ago, if you'd asked the same question.

而我們是在沒有劇本的世界裡。所以去執行 5 年、10 年前有效的劇本——本質上是打造寄生式軟體並將其變現——現在行不通了。這有上百種變體，但那是我們的一個核心優勢。我們是一個群落：信徒與藝術家，且非常有動力去驅動價值。而這讓我們的差異化程度，遠超過我 10 年前被問到同樣問題時所能想像的。

And then luckily for us, this is capitalism. I mean DSA wants to get rid of it. But until they do, you got to look at the results because of our results -- and the other thing I'll tell you that's very special for us, we are outsiders. Outsiders like you're an outsider. You come to this country, you better have really good results.

然後幸運的是，這是資本主義。我的意思是，DSA 想把它廢掉。但在他們做到之前，你得看結果，因為我們的結果——另外我還要告訴你一件對我們非常特別的事：我們是局外人。局外人就像你也是局外人。你來到這個國家，你最好拿出非常好的結果。

And like the same thing for Palantir, we know we need the best results because people aren't buying our product because we're swinging the golf cube correctly or paying for the steak dinner. They don't even invite us to stay tuners. So that's -- and that outsider status has caused huge problems, but in the first 18 years, but a lot of benefits in the next 18 years. And other people don't like being outsiders -- in fact, I'm struggling with our current popularity.

而且對 Palantir 也是同樣的道理，我們知道我們需要最好的成果，因為人們不是因為我們把高爾夫方塊揮得很正確，或是請了牛排晚餐，才來買我們的產品。他們甚至不會邀請我們去當座上賓。所以就是這樣——而那種局外人的身分在前 18 年造成了巨大的問題，但在接下來的 18 年帶來了很多好處。而其他人不喜歡當局外人——事實上，我正在為我們目前的受歡迎程度而掙扎。

Thank you. Our next question is from Gil with DA Davidson. Gil, please turn on your camera, and then you'll receive a prompt to unmute your line.

謝謝。我們下一個問題來自 DA Davidson 的 Gil。Gil，請打開你的鏡頭，然後你會收到提示以解除靜音。

The topic of sovereignty, you focused a lot on how dangerous it is to give the keys to the labs because they could choose to compete with you. Is there another aspect of this as well, though, that -- if you choose a lab and you buy the orchestration and the consulting and the harnesses from them, you're beholden to their models. And if something happens, if it's not the best anymore if the model gets pulled, then you as a customer are stuck and you may have a mission-critical system fail.

關於主權這個主題，你花了很多篇幅談到把鑰匙交給實驗室有多危險，因為他們可能選擇與你競爭。不過這是否還有另一個面向——也就是說，如果你選定一家實驗室，並向他們購買編排、顧問服務與各種工具套件，你就會受制於他們的模型。而如果發生什麼事——如果它不再是最好的、或模型被下架——那你作為客戶就會被卡住，甚至可能導致你的關鍵任務系統失效。

And this isn't hypothetical. This happened a couple of times this year where one of the frontier models got pulled by either the government or the company well if you work with Palantir, I would assume that when that happens, you can go to your customer and say, hey, if that model doesn't work, I can plug in another model for you?

而這不是假設情境。今年已經發生過幾次：某個前沿模型被政府或公司下架。那如果你與 Palantir 合作，我會假設當這種事發生時，你可以去跟客戶說：嘿，如果那個模型不能用，我可以幫你換接另一個模型？

No. I mean I'll let Ryan and Shyam comment here, but we're already doing that across the USG US government. We have a product that allows you to switch out models. Look, at the end of the day, if you are locked into a product, you're going to -- I mean that's the nature of monopoly capitalism.

不。我的意思是，我會讓 Ryan 和 Shyam 在這裡補充，但我們在美國政府（USG）各單位已經在這麼做了。我們有一個產品可以讓你替換模型。你看，說到底，如果你被鎖定在某個產品裡，你就會——我的意思是，這就是壟斷資本主義的本質。

That's why people want to lock in because then they can raise the prices and reduce the quality. We're against that because we're on the side of the American work with the American people and its great institutions and other institutions across the west.

這也是為什麼人們想要做鎖定，因為那樣他們就能漲價並降低品質。我們反對這種做法，因為我們站在美國勞動者、站在美國人民及其偉大機構的一邊，也站在整個西方的其他機構一邊。

But yes, they're and people are running big enterprises in this country are very sophisticated. They're aware of these risks. And they don't like people who are kind of flaunting like setting this up so that they feel they're being made fun of or they're being basically. So there's a lot -- honestly, there's a lot of anger here.

但沒錯——而且在這個國家經營大型企業的人都非常老練。他們知道這些風險。他們也不喜歡有人以一種近乎炫耀的方式把局面設計成讓他們覺得自己被嘲弄、或基本上被——所以這裡有很多——老實說，這裡有很多憤怒。

I spent interestingly, a fair bit of my time trying to explain to people that some of the people involved in these things are not the caricature as they think they are. But because the business setup looks like heads I win, tails I win and American business people don't like that. But then I don't know there's a lot of things on the contractual front that would support that.

有趣的是，我花了相當多時間試著向人們解釋：參與這些事情的一些人，並不是他們想像中的那種刻板漫畫形象。但因為商業安排看起來像是「正面我贏、反面我也贏」，而美國商界人士不喜歡這樣。不過我也不知道——在合約層面確實有很多東西會支撐那種觀感。

Yes, I would say like that's our whole focus is converting tokens to value. The example Shyam gave, that's happening across the board and the conversations with customers, that's why they're looking to expand to convert how they position themselves in the industry with us in their industry.

是的，我會說我們的整個重點就是把 tokens 轉化為價值。Shyam 舉的例子正在全面發生；而在與客戶的對話中，這也是為什麼他們希望擴大合作——透過我們，去改變他們在各自產業中的定位。

And so we're seeing like extreme alignment. It's not about being beholden to one model. It's about bringing the right models to bear for the right purposes and our contracts, our structures are set up to do that to support and compound their alpha in the organization.

因此我們看到的是高度一致的對齊。重點不是受制於單一模型。重點是針對正確的目的導入正確的模型，而我們的合約與架構就是為此而設計，用來支持並複利化他們在組織中的 alpha（超額報酬）。

I think I mentioned it earlier, but you're going to see this, like we've been beholding to a small number of benchmarks that people have been designing models to and then releasing model saying, like, look, how well it does on this benchmark. But the benchmark is actually almost nothing to do with your business.

我想我之前提過，你會看到這種情況：我們一直受制於少數幾個基準測試，人們依照這些基準去設計模型，然後發布模型時說：你看，它在這個基準上表現多好。但這個基準其實幾乎與你的業務無關。

So how do you figure out how to make the benchmark that represents your reality, what you're trying to succeed at, what are you trying to get better at and then see what model makes sense. And the natural consequence of doing that even leaving aside all of your other arguments for sovereignty, it's like, oh, how do I climb that hill? How do I figure out what it is that I do as a business that I feed back into weights that I can control, which presupposes an open model and sovereignty.

所以你要怎麼找出能代表你現實情境的基準——你想成功的是什麼、你想變得更好的是什麼——然後再看哪個模型合理。而這麼做的自然結果——即便先不談你對主權的其他論點——就是：喔，我要怎麼爬上那座山？我要怎麼弄清楚我作為一家企業所做的事情，並把它回饋到我能控制的權重（weights）上；而這就預設你需要開放模型與主權。

And then you're not just going to do that where you're waiting, hey, maybe I'll switch it out when this model gets pulled and the rug gets pulled out from underneath me. You're actually going to be leveraging the automation to do that constantly to figure out when you have a next act on forward maybe there's a new model.

然後你不會只是被動地等著：嘿，也許等這個模型被下架、地毯被從我腳下抽走時，我再把它換掉。你其實會利用自動化持續地做這件事，不斷判斷何時該往前推進下一步——也許有個新模型出現。

I mentioned the example. I literally almost felt gas lit when within 24 hours of getting Nemotron up with no post training. This is via Nemotron/Ultra, it did better than Frontier. If you just looked at the numbers, you would say, well, it's nowhere near the frontier. That shouldn't even be possible.

我提過那個例子。我真的幾乎覺得自己被「煤氣燈」了：在 24 小時內把 Nemotron（沒有做任何後訓練）跑起來。這是透過 Nemotron/Ultra，它的表現竟然比 Frontier 還好。如果你只看數字，你會說，嗯，它離前沿水準差得遠。那甚至不應該是可能的。

But of course, the benchmarks are wrong. I mean the benchmarks are right for what the benchmark is measuring, but that's not my business. Those are not the task my customers had that they were trying to solve. And so then moving this to an empirical basis is, I think, is how we're going to accelerate the realization of tokens to real economic value.

但當然，基準測試是錯的。我的意思是，基準對它所衡量的東西而言是對的，但那不是我的業務。那些也不是我的客戶要解決的任務。因此，把這件事轉到以實證為基礎，我認為這就是我們將加速把 tokens 轉化為真實經濟價值的方式。

Thank you. You Alex, as always, we have a lot of individual investors on the line. Is there anything you'd like to say before we?

謝謝。Alex，你也知道，我們線上一直都有很多個人投資人。在我們結束之前，你有沒有什麼想說的？

Well, your support has -- was crucial to getting us this far. -- and crucial to getting us to where we're going to go, which is a much, much, much, much larger company. This is one of the most exciting times to be involved in the Palantir mission. We are going to help transform especially this country, but allied countries, both in commercial and government.

嗯，你們的支持——對我們走到今天至關重要——也對我們走向未來至關重要；而我們將成為一家大得多、大得多、大得多、大得多的公司。這是參與 Palantir 使命最令人振奮的時刻之一。我們將協助改造——尤其是這個國家，但也包括盟友國家——在商業與政府兩個領域。

And the sovereign frame that is -- we're using as our organizational principle is one that is inclusive of everybody who wants to have a better world today and tomorrow. And we invite everyone to engage with it in some form. And thank you.

而我們用作組織原則的「主權」框架，是一個包容所有希望今天與明天都能擁有更好世界的人。我們邀請每個人以某種形式參與其中。謝謝。

Thank you. That concludes Q&A for today's call.

謝謝。今天電話會議的問答環節到此結束。