甲骨文 (ORCL) 2025 Q1 法說會逐字稿

Hello, and welcome to the Oracle Corporation Q1 fiscal year 2025 earnings call.

您好，歡迎參加 Oracle 公司 2025 財年第一季財報電話會議。

(Operator Instructions) I would now like to turn the conference over to Ken Bond, Head of Investor Relations.

（操作員指示）我現在想將會議轉交給投資人關係主管 Ken Bond。

You may begin.

你可以開始了。

Thank you, Sarah, and good afternoon, everyone, and welcome to Oracle's first quarter fiscal year 2025 earnings conference call.

謝謝莎拉，大家下午好，歡迎參加 Oracle 2025 財年第一季財報電話會議。

A copy of the press release and financial tables, which includes a GAAP to non-GAAP reconciliation and other supplemental financial information, can be viewed and downloaded from our Investor Relations website.

您可以從我們的投資者關係網站查看和下載新聞稿和財務表格的副本，其中包括 GAAP 與非 GAAP 調整表以及其他補充財務資訊。

Additionally, a list of many customers who purchased Oracle Cloud Services or went live on Oracle Cloud recently will be available from the investor relations website.

此外，投資者關係網站還提供了許多最近購買 Oracle 雲端服務或上線 Oracle 雲端的客戶的清單。

On the call today are Chairman and Chief Technology Officer, Larry Ellison; and Chief Executive Officer, Safra Catz.

今天參加電話會議的是董事長兼技術長 Larry Ellison；兼首席執行官 Safra Catz。

As a reminder, today's discussion will include forward-looking statements, including predictions, expectations, estimates, or other information that might be considered forward-looking.

提醒一下，今天的討論將包括前瞻性陳述，包括預測、期望、估計或其他可能被視為前瞻性的資訊。

Throughout today's discussion, we will present some important factors relating to our business, which may potentially affect these forward-looking statements.

在今天的討論中，我們將介紹一些與我們業務相關的重要因素，這些因素可能會影響這些前瞻性陳述。

These forward-looking statements are also subject to risks and uncertainties that may cause actual results to differ materially from statements being made today.

這些前瞻性陳述也受到風險和不確定性的影響，可能導致實際結果與今天的陳述有重大差異。

As a result, we caution you against placing undue reliance on these forward-looking statements, and we encourage you to review our most recent reports, including our 10-K and our 10-Q and any applicable amendments for a complete discussion of these factors and other risks that may affect our future results or the marketplace of our stock.

因此，我們提醒您不要過度依賴這些前瞻性陳述，並鼓勵您查看我們最新的報告，包括我們的 10-K 和 10-Q 以及任何適用的修正案，以全面討論這些因素以及可能影響我們未來業績或我們股票市場的其他風險。

And finally, we are not obligating ourselves to revise our results or these forward-looking statements in light of new information or future events.

最後，我們沒有義務根據新資訊或未來事件修改我們的結果或這些前瞻性陳述。

Before taking questions, we'll begin with a few prepared remarks.

在回答問題之前，我們將先做一些準備好的評論。

And with that, I'd like to turn the call over to Safra.

說到這裡，我想把電話轉給薩夫拉。

Thanks, Ken, and good afternoon, everyone.

謝謝，肯，大家下午好。

Before I go to our Q1 numbers, I thought I'd take only a moment to review some of the things that you'll be hearing about over the next couple of days from Oracle.

在討論第一季的數據之前，我想我只需要花點時間回顧一下您將在接下來的幾天內從 Oracle 聽到的一些事情。

We are at Cloud World in Las Vegas, and Cloud World is where we come together with our customers and partners, share experiences and showcase our latest products and services.

我們在拉斯維加斯的雲端世界，雲端世界是我們與客戶和合作夥伴歡聚一堂、分享經驗並展示我們最新產品和服務的地方。

Our customers are our best folks people when they share how our technologies transform their enterprises.

當我們的客戶分享我們的技術如何改變他們的企業時，他們就是我們最好的夥伴。

The innovations from our labs and research centers in combination with feedback from our customers have helped us build superior products and services.

我們實驗室和研究中心的創新與客戶的回饋相結合，幫助我們打造了卓越的產品和服務。

You'll hear about new cutting-edge features within OCI, database, analytics, Fusion, NetSuite, and our industry applications.

您將了解 OCI、資料庫、分析、Fusion、NetSuite 和我們的行業應用程式中的新尖端功能。

We will also be showing new capabilities that we've been working on for a while, including embedded AI agents infusion and those drive productivity and efficiencies for our customers when they're rolled out.

我們還將展示我們已經研究了一段時間的新功能，包括嵌入式人工智慧代理注入，以及在推出後為客戶提高生產力和效率的功能。

And as an Oracle Fusion customer myself, I take great pride once again in my team's ability to have us announce earnings and give guidance nine days after the quarter ended.

身為 Oracle Fusion 的客戶，我再次為我的團隊能夠在季度結束九天後宣布收益並提供指導而感到非常自豪。

Many, many of our customers ask us how to replicate our results.

很多很多客戶問我們如何複製我們的結果。

And at Cloud World, we will be having a lot of Oracle playbook conversations this week.

在 Cloud World，我們本週將進行大量 Oracle 策略對話。

You've already seen today's announcement of our partnership with Amazon Web Services, which has now joined Microsoft Azure and Google Cloud in making OCI and Oracle available in their respective clouds.

您已經看到了我們今天宣布的與 Amazon Web Services 的合作夥伴關係，Amazon Web Services 現在已加入 Microsoft Azure 和 Google Cloud 的行列，使 OCI 和 Oracle 在各自的雲端中可用。

Needless to say, we think our MultiCloud strategy will expand the ubiquity and popularity of differentiated technologies especially the Oracle Database.

不用說，我們認為我們的多雲策略將擴大差異化技術（尤其是 Oracle 資料庫）的普遍性和流行度。

Larry will share more details in just a moment.

拉里稍後將分享更多細節。

But now to Q1, which was clearly another outstanding quarter, with total revenue at the high end of my guidance and earnings per share, $0.04 above the high end of guidance.

但現在到了第一季度，這顯然是另一個出色的季度，總收入處於我的指導的高端，每股收益比指導的高端高出 0.04 美元。

Currency was essentially in line with my guidance.

貨幣基本上符合我的指導。

And as usual, I'll be discussing our financials using constant currency growth rates as this is how we manage the business.

像往常一樣，我將使用恆定的貨幣成長率來討論我們的財務狀況，因為這就是我們管理業務的方式。

Total cloud revenue, that's SaaS and IaaS, was up 22% at $5.6 billion, with SaaS revenue of $3.5 billion, up 10%; and IaaS revenue of $2.2 billion, up 46%, on top of the 64% growth reported last year.

雲端總營收（即 SaaS 和 IaaS）成長 22%，達到 56 億美元，其中 SaaS 營收為 35 億美元，成長 10%； IaaS 營收達到 22 億美元，較去年成長 64% 成長 46%。

As a reminder, we exited the advertising business last quarter, which had the effect of lowering the total cloud applications revenue by 2% this quarter.

提醒一下，我們在上個季度退出了廣告業務，這導致本季雲端應用程式總收入下降了 2%。

Total cloud services and license support for the quarter was $10.5 billion, up 11%, driven again by our strategic cloud applications, autonomous database and OCI.

本季雲端服務和授權支援總額為 105 億美元，成長 11%，這再次受到我們的策略雲端應用程式、自主資料庫和 OCI 的推動。

Application subscription revenues, which includes product support were $4.8 billion and up 7%.

應用程式訂閱收入（包括產品支援）為 48 億美元，成長 7%。

Our strategic back-office SaaS applications now have annualized revenues of $8.2 billion and were up 18%.

我們的策略後台 SaaS 應用程式目前年收入達 82 億美元，成長了 18%。

Infrastructure subscription revenues, which includes license support, were $5.8 billion and up 14%.

包括許可證支援在內的基礎設施訂閱收入為 58 億美元，成長 14%。

Infrastructure cloud services revenue was up 46% and up 49% when you are excluding our legacy hosting services.

基礎設施雲端服務收入成長了 46%，如果不包括我們的舊託管服務，則成長了 49%。

Our infrastructure cloud services now have an annualized revenue of $8.6 billion, OCI consumption revenue was up 56% and demand continued to outstrip supply.

我們的基礎設施雲端服務目前年化收入為 86 億美元，OCI 消費收入成長 56%，且持續供不應求。

Cloud database services, which were up 23% and now have annualized revenues of $2.1 billion.

雲端資料庫服務成長了 23%，目前年收入為 21 億美元。

Very importantly, as on-premise databases migrate to the cloud, on OCI directly, or through our database at cloud services with Azure, Google, and AWS.

非常重要的是，隨著本地資料庫直接遷移到雲，在 OCI 上，或透過我們在 Azure、Google 和 AWS 雲端服務上的資料庫。

We expect those cloud database revenues collectively will be the third leg of revenue growth alongside OCI and strategic SaaS.

我們預計這些雲端資料庫收入將成為繼 OCI 和策略 SaaS 之外的收入成長的第三個支柱。

Database subscription revenues, which includes database license support, were up 4%.

包括資料庫授權支援在內的資料庫訂閱收入成長了 4%。

Software license revenues were up 8% to $870 million, including Java, which saw excellent growth.

軟體授權收入成長 8%，達到 8.7 億美元，其中 Java 成長強勁。

So all in, total revenue for the quarter were $13.3 billion, up 8% from last year.

總而言之，本季總營收為 133 億美元，比去年成長 8%。

Shifting to gross profit and operating income.

轉向毛利和營業收入。

The gross profit dollars of cloud services and license support grew 9% in Q1 as our cloud businesses continue to scale the gross margins of both cloud applications and cloud infrastructure has each been climbing higher.

隨著我們的雲端業務不斷擴大，雲端應用程式和雲端基礎設施的毛利率都在攀升，第一季雲端服務和授權支援的毛利成長了 9%。

We continue to display operating expense discipline, Q1 operating income growing 14% and the operating margin was 43%.

我們持續維持營運支出紀律，第一季營運收入成長 14%，營運利潤率為 43%。

The non-GAAP tax rate for the quarter was 18.9% with non-GAAP EPS at USD1.39, up 17% in USD, up 18% in constant currency.

本季非 GAAP 稅率為 18.9%，非 GAAP 每股盈餘為 1.39 美元，以美元計算成長 17%，以固定匯率計算成長 18%。

The GAAP EPS was USD1.03, up 20% in USD and up 22% in constant currency.

GAAP 每股盈餘為 1.03 美元，以美元計算成長 20%，以固定匯率計算成長 22%。

Including in my guidance at the beginning of the quarter was the expected completion of an assessment of the useful lives of our server networking equipment, including an increase of the estimated lives from five years to six years effective at the beginning of this fiscal year.

我在本季度初的指導中包括預計完成對伺服器網路設備使用壽命的評估，包括從本財年年初起將估計壽命從五年增加到六年。

This change in accounting estimate reduced Q1 operating expenses by about $197 million.

會計估計的這項變更減少了第一季營運費用約1.97億美元。

At quarter end, we had nearly $11 billion of cash and marketable securities, a short-term deferred revenue balance was $11.5 billion, up 2%.

截至季末，我們擁有近 110 億美元的現金和有價證券，短期遞延收入餘額為 115 億美元，成長 2%。

Operating cash flow for Q1 was $7.4 billion, while free cash flow was $5.1 billion.

第一季營運現金流為 74 億美元，自由現金流為 51 億美元。

On a trailing 12-month basis, operating cash flow was $19.1 billion and free cash flow was $11.3 billion.

過去 12 個月的營運現金流為 191 億美元，自由現金流為 113 億美元。

Our remaining performance obligations or RPO is now $99 billion, up 52% in constant currency.

我們的剩餘履約義務或 RPO 目前為 990 億美元，以固定匯率計算成長了 52%。

Now, while we typically see a seasonal decline of RPO in Q1, we signed several large deals this past quarter, resulting in a sequential increase in RPO compared to the decline that we typically see based on our experience over the previous five years.

現在，雖然我們通常會在第一季看到RPO 季節性下降，但我們在上個季度簽署了幾筆大型交易，導致RPO 與我們根據過去五年的經驗通常看到的下降相比出現了環比上升。

Further, our cloud RPO grew more than 80% and now represents nearly three-fourths of total RPO.

此外，我們的雲端 RPO 成長了 80% 以上，目前佔總 RPO 的近四分之三。

And approximately 38% of total RPO is expected to be recognized as revenue over the next 12 months, which reflects the growing trend of customers wanting the larger and longer contracts as they see firsthand how Oracle Cloud services are benefiting their businesses.

預計未來12 個月內，RPO 總額的大約38% 將被確認為收入，這反映出客戶越來越希望獲得更大、更長的合同，因為他們親眼目睹了Oracle 雲端服務如何使他們的業務受益。

We spent $2.3 billion on CapEx this quarter, given the demand that you see in our RPO growth and the additional demand we have and see in our pipeline, I expect the fiscal year 2025 CapEx will be double what it was in fiscal 2024.

考慮到我們在RPO 成長中看到的需求以及我們在管道中看到的額外需求，本季度我們在資本支出上花費了23 億美元，我預計2025 財年的資本支出將是2024 財年的兩倍。

As always, we remain careful to pace our investments appropriately and in line with booking trends.

一如既往，我們仍然謹慎地根據預訂趨勢適當調整投資節奏。

We now have 85 cloud regions live, another 77 planned with more to follow.

我們現在有 85 個已上線的雲區域，另外還計劃有 77 個雲區域，後續還會有更多雲區域。

We have public cloud regions.

我們有公有雲區域。

We have dedicated cloud customer regions.

我們有專門的雲端客戶區域。

We have national security regions.

我們有國家安全區。

We have sovereign regions.

我們有主權地區。

We have Oracle alloy regions with our partners, and we have MultiCloud regions with Azure and Google Cloud and now shortly with AWS as well.

我們與合作夥伴建立了 Oracle 合金區域，並與 Azure 和 Google Cloud 建立了多雲區域，現在很快也將與 AWS 建立合作夥伴關係。

This sizing flexibility and deployment optionality of our cloud regions continue to be significant advantages for us in the marketplace.

我們的雲端區域的規模靈活性和部署可選性仍然是我們在市場上的顯著優勢。

As we've said before, we're committed to returning value to our shareholders through technical innovation, strategic acquisitions, stock repurchases, prudent use of debt and the dividend.

正如我們之前所說，我們致力於透過技術創新、策略性收購、股票回購、審慎使用債務和股利來為股東回報價值。

This quarter, we repurchased 1.1 million shares for a total of $150 million.

本季度，我們回購了 110 萬股股票，總金額為 1.5 億美元。

In addition, we paid out dividends of $4.4 billion over the last 12 months.

此外，我們在過去 12 個月內支付了 44 億美元的股息。

And the Board of Directors again declared a quarterly dividend of $0.40 per share.

董事會再次宣布季度股息為每股 0.40 美元。

Before I dive into specific Q2 guidance, I'd like to share some overarching thoughts and the benefits that I expect they will bring over the coming years.

在深入討論具體的第二季度指導之前，我想分享一些總體想法以及我預計它們將在未來幾年帶來的好處。

First, the Oracle database is thriving, and the MultiCloud agreements we now have with Microsoft, Google, and AWS make it easier for our customers to run their Oracle databases in the cloud.

首先，Oracle 資料庫正在蓬勃發展，我們現在與 Microsoft、Google 和 AWS 簽訂的多雲協議使我們的客戶可以更輕鬆地在雲端中運行其 Oracle 資料庫。

Second, we are rapidly expanding our OCI capacity to meet the demand that you see in our 52% RPO cloud growth.

其次，我們正在快速擴大 OCI 容量，以滿足您在我們 52% RPO 雲端成長中看到的需求。

Third, while much attention is focused on our GPU related businesses, our non-GPU infrastructure business continues to grow much faster than our competitors.

第三，雖然我們的 GPU 相關業務受到許多關注，但我們的非 GPU 基礎設施業務的成長速度仍遠遠快於競爭對手。

And finally, our strategic SaaS app continue to grow while we are starting to see more and more of our industry-based cloud apps come online.

最後，我們的策略 SaaS 應用程式持續成長，同時我們開始看到越來越多的基於產業的雲端應用程式上線。

All these trends point to revenue growth going higher.

所有這些趨勢都表明收入成長將會更高。

We will discuss the implications of these positive trends at our financial analyst meeting on Thursday.

我們將在周四的金融分析師會議上討論這些正面趨勢的影響。

For fiscal 2025, we remain very confident and committed to full-year total revenue growth growing double digits and full year total cloud infrastructure revenue growing faster than last year.

對於2025財年，我們仍然非常有信心，並致力於全年總收入成長兩位數，全年雲端基礎設施總收入成長速度快於去年。

Let me now turn to my guidance for Q2, which I'll review on a non-GAAP basis.

現在讓我談談我對第二季的指導，我將在非公認會計原則的基礎上進行審查。

If currency exchange rates remain the same as they are now, currency should have about a 1% positive effect on total revenue and as much as a $0.03 positive effect on EPS, hard to know for sure.

如果貨幣匯率保持與現在相同，貨幣應該對總收入產生約 1% 的正面影響，對 EPS 產生高達 0.03 美元的正面影響，但很難確定。

However, the actual currency impact may be different.

然而，實際的貨幣影響可能有所不同。

Total revenues are expected to grow from 7% to 9% in constant currency and are expected to grow between 8% and 10% in USD at today's exchange rate.

以固定匯率計算，總收入預計將從 7% 增長到 9%，以當前匯率計算，預計總收入將增長 8% 到 10%。

Total cloud revenue is expected to grow from 23% to 25% in constant currency and 24% to 26% in USD.

以固定匯率計算，雲端總收入預計將從 23% 成長到 25%，以美元計算將從 24% 成長到 26%。

Non-GAAP EPS is expected to grow between 6% to 10% and be between $1.42 and $1.46 in constant currency, and non-GAAP EPS is expected to grow 8% to 12% and be between USD1.45 and USD1.49. My EPS guidance for Q2 assumes a base tax rate of 19%.

以固定匯率計算，非GAAP 每股盈餘預計將成長6% 至10%，介於1.42 美元至1.46 美元之間；非GAAP 每股盈餘預計將成長8% 至12%，介於1.45 美元至1.49 美元之間。我對第二季 EPS 的指導假設基本稅率為 19%。

However, onetime tax events could cause actual tax rates to vary.

然而，一次性稅務事件可能會導致實際稅率發生變化。

And with that, sorry, it was so long.

抱歉，時間太長了。

And with that, I'll turn it over to Larry for his comments.

接下來，我將把它交給拉里徵求他的意見。

Thank you, Safra.

謝謝你，薩弗拉。

Today, Oracle has 162 cloud data centers, live and under construction throughout the world.

如今，Oracle 在全球擁有 162 個已啟用且正在建置的雲端資料中心。

The largest of these data centers is 800 megawatts, and it will contain acres of NVIDIA GPU clusters able to train the world's largest AI models.

其中最大的資料中心容量為 800 兆瓦，將包含數英畝的 NVIDIA GPU 集群，能夠訓練世界上最大的 AI 模型。

That's what's required to stay competitive in the race to build one, just one, of the most powerful artificial neural networks in the world.

這就是在建構世界上最強大的人工神經網路的競賽中保持競爭力所需要的。

The stakes are high, and the race goes on.

賭注很高，比賽仍在繼續。

Soon Oracle will begin construction of data centers that are more than a gigawatt.

很快，甲骨文將開始建置超過千兆瓦的資料中心。

Building giant data centers with ultra-high apartments RDMA networks and huge 32,000 node NVIDIA GPU clusters is something that Oracle has proven to be very good at.

事實證明，利用超高單元 RDMA 網路和龐大的 32,000 個節點 NVIDIA GPU 叢集建立巨型資料中心是 Oracle 非常擅長的事情。

It's the reason we're doing so well in the AI training business.

這就是我們在人工智慧培訓業務中表現出色的原因。

I

我

t's important to remember that we first developed those high-performance RDMA networks to interconnect our Exadata CPU cluster hardware that powers our Exadata database cloud service.

請務必記住，我們首先開發這些高效能 RDMA 網路是為了互連為 Exadata 資料庫雲端服務提供支援的 Exadata CPU 叢集硬體。

The Oracle Database Cloud service running on Exadata and exascale RDMA clusters, provide an order of magnitude, better performance, better scalability, better reliability, and better security than other databases.

運行在 Exadata 和百億億次 RDMA 叢集上的 Oracle 資料庫雲端服務比其他資料庫提供了一個數量級的更好的效能、更好的可擴展性、更好的可靠性和更好的安全性。

And it's still the world's only autonomous, fully self-driving database.

它仍然是世界上唯一的自主、完全自動駕駛的資料庫。

Our large and loyal customer base understand and appreciate the many technical advantages of using the Oracle database.

我們龐大且忠實的客戶群了解並欣賞使用 Oracle 資料庫的許多技術優勢。

And those customers wanted us to find a way to make the very latest and best Oracle technology available on other clouds in addition to OCI.

這些客戶希望我們找到一種方法，讓最新、最好的 Oracle 技術可以在 OCI 以外的其他雲端上使用。

We found a way.

我們找到了方法。

With today's AWS announcement, our customers will be able to use Oracle's latest Exadata and exascale RDMA clusters with the latest versions of our database software, from within the Microsoft Azure cloud, from within the Google Cloud and from within the AWS cloud.

隨著今天 AWS 的發布，我們的客戶將能夠在 Microsoft Azure 雲端、Google 雲端和 AWS 雲端中使用 Oracle 最新的 Exadata 和百億億次級 RDMA 叢集以及最新版本的資料庫軟體。

This will enable customers to use the Oracle database anywhere and everywhere.

這將使客戶能夠隨時隨地使用 Oracle 資料庫。

That has always worked well for our customers and for our database business.

這對於我們的客戶和我們的資料庫業務來說一直很有效。

We believe our cloud partnerships with AWS and Microsoft and Google will turbocharge the growth of our database business for years to come.

我們相信，我們與 AWS、微軟和谷歌的雲端合作夥伴關係將在未來幾年推動我們資料庫業務的成長。

Back to you.

回到你身邊。

Thank you, Larry.

謝謝你，拉里。

Sarah, if you could please poll the audience for questions.

莎拉，如果可以的話請向觀眾提問。

(Operator Instructions) John DiFucci, Guggenheim Securities.

（操作員指令）John DiFucci，古根漢證券公司。

Larry and Safra, there's a lot of good stuff here, but I'd like to ask a question on margins.

Larry 和 Safra，這裡有很多好東西，但我想問一個關於利潤的問題。

You keep putting up strong cloud numbers, especially the OCI numbers that look -- when you give the guidance and you look at what you have to do to hit them, That look really difficult to do, to say the least.

你不斷提供強大的雲端數據，尤其是 OCI 數據，當你提供指導並考慮必須採取哪些措施才能達到目標時，至少可以說，這看起來確實很難做到。

We also assume that upside to RPO, and you pointed out, Safra, the sequential increase.

我們也假設 RPO 有上升空間，Safra，您指出了環比增長。

I think the last time there was sequential increase is because you bought Cerner and they just added RPO because of that.

我認為上次連續增長是因為你買了 Cerner，他們因此增加了 RPO。

I assume a big part of that OCI too.

我認為 OCI 也佔很大一部分。

You mentioned it's cloud, three cores of it.

你提到它是雲，它的三個核心。

So that indicates there's more to come, right?

所以這表明還有更多的事情要做，對嗎？

So given the mix of business continuing to lean into that lower margin OCI, and I know you have that's changing over time, but it's still lower margin today.

因此，考慮到業務組合繼續傾向於較低利潤率的 OCI，我知道這種情況隨著時間的推移而發生變化，但今天的利潤率仍然較低。

How should we think of overall margins versus profit for the entire company going forward?

我們該如何看待整個公司未來的整體利潤率與利潤？

Okay.

好的。

Let me start with this and maybe then Larry can add on.

讓我從這個開始，也許拉里可以補充。

So first of all, I want to remind you that, that -- remember that third leg of the stool I mentioned, which is our database and autonomous database, that is also part of OCI.

首先，我想提醒大家，記住我提到的第三條腿，這是我們的資料庫和自治資料庫，也是 OCI 的一部分。

And that is beginning to really expand.

而且這種情況正在開始真正擴大。

And our MultiCloud agreements, again, will help OCI gross margins so that you know gross margins even this quarter as percentage increased, regardless of the fact that we have a lot more OCI, and so our business is really only now starting to get real scale.

我們的多雲協議將再次幫助 OCI 毛利率，這樣您就可以知道本季的毛利率百分比有所增加，儘管我們擁有更多的 OCI，因此我們的業務實際上現在才開始真正規模化。

And we have built OCI in a way and Larry can really expand on it, where it is extremely automated.

我們以某種方式建立了 OCI，Larry 可以真正對其進行擴展，它是高度自動化的。

The management of it is very automated.

它的管理非常自動化。

And our whole rollout as it grows, we make more money.

隨著我們的整個推廣的發展，我們賺了更多的錢。

And as much as percentages are great, and again, our operating margin percentages continue to increase. and OCI includes not only base storage and compute and GPUs, but it also includes a lot of other capabilities, including the database, which have excellent margins, too.

儘管百分比很高，但我們的營業利潤率再次持續增加。 OCI 不僅包括基礎儲存、運算和 GPU，還包括許多其他功能，包括資料庫，這些功能也具有出色的利潤。

And of course, as you mentioned, our SaaS business, again, an excellent and at scale business, even that business benefits from our expansion in OCI.

當然，正如您所提到的，我們的 SaaS 業務同樣是一項出色且規模化的業務，甚至該業務也受益於我們在 OCI 的擴張。

And once again, even at its high margins continued to improve this past quarter.

即使利潤率很高，上個季度仍持續改善。

Larry, I don't know if you want to

拉里，我不知道你是否願意

I'd like to.

我想。

I'd like to.

我想。

So let's start with SaaS.

那麼讓我們從 SaaS 開始。

As we go to autonomous database, we get tremendous efficiencies.

當我們使用自治資料庫時，我們獲得了巨大的效率。

We're moving Fusion and NetSuite to Autonomous database as we speak.

正如我們所說，我們正在將 Fusion 和 NetSuite 遷移到自治資料庫。

We've decided everything needs to move to autonomous for two reasons really.

我們決定一切都需要轉向自動化，這實際上有兩個原因。

First reason, when you have a completely autonomous database, there is no -- the DBA, the database administrator is a robot.

第一個原因，當你擁有一個完全自治的資料庫時，就不再需要DBA、資料庫管理員了。

There is no human labor associated with managing the Oracle Autonomous Database.

管理 Oracle 自治資料庫不需要任何人工。

Now okay, that's obviously a cost savings.

現在好吧，這顯然可以節省成本。

But more importantly, with no human labor, there's no human error.

但更重要的是，沒有人工勞動，就不存在人為錯誤。

It's a huge security advantage we have over our competitors.

與競爭對手相比，我們擁有巨大的安全優勢。

We don't -- there's no mistakes to be made.

我們不會——不會犯任何錯誤。

There's no human labor.

沒有人力。

It's all automated.

一切都是自動化的。

And the potential -- when you have everything completely automated, and it's also truly elastic.

還有潛力——當一切都完全自動化，而且它也真正具有彈性時。

I'm not going to go into exactly what that means.

我不打算詳細解釋這意味著什麼。

But it means that you've got a running that certainly needs 500 microprocessors, you get those 500 for the 3 minutes you need it, and then you return them to the pool.

但這意味著您的運作肯定需要 500 個微處理器，您可以在需要的 3 分鐘內獲得這 500 個微處理器，然後將它們放回池中。

So that's very different than how other databases work, which they may call -- the cloud itself may be elastic in places, but their databases are typically not elastic.

因此，這與其他資料庫的工作方式非常不同，他們可能稱之為雲端本身在某些地方可能是有彈性的，但他們的資料庫通常沒有彈性。

Autonomous is.

自治是。

So we use a lot less hardware.

所以我們使用的硬體少很多。

It's a lot faster.

速度快多了。

It's a lot more efficient.

效率高很多。

It's fully automated, no human labor, much more secure.

它是完全自動化的，無需人工，而且更安全。

And the margins for the autonomous database business is much higher or much higher than the traditional Oracle business.

而且自治資料庫業務的利潤率比傳統Oracle業務高很多或高很多。

And I think those margins are -- I mean, they're stunningly high.

我認為這些利潤率高得驚人。

Around the same margins as a which are also stunningly hard margin because SaaS runs primarily on that autonomous database.

與 SaaS 的利潤率大致相同，這也是令人震驚的硬利潤率，因為 SaaS 主要在自治資料庫上運行。

So we use hardware very efficiently.

所以我們非常有效地使用硬體。

We use labor sparingly because labor is a security risk.

我們很少使用勞動力，因為勞動力有安全風險。

When people are actually doing things manually as the security risk, and it slows down our ability to expand.

當人們實際上手動做事時，就會存在安全風險，並且會減慢我們的擴展能力。

Every Oracle data center from the largest to the smallest are identical and features and functions, they only vary by scale.

每個 Oracle 資料中心從最大到最小的特性和功能都是相同的，只是規模不同。

That means we have one suite of automation software that automates all of this.

這意味著我們擁有一套自動化軟體，可以自動執行所有這些操作。

Nobody else does this.

沒有其他人這樣做。

No one has that level of automation, that level of autonomy.

沒有人擁有那種程度的自動化、那種程度的自主權。

It allows us to get much better margins, in our database business and our SaaS business and the rest of our cloud business.

它使我們能夠在資料庫業務、SaaS 業務以及其他雲端業務中獲得更好的利潤。

Our clouds are more automated, so we have very low labor costs.

我們的雲端更加自動化，因此我們的勞動成本非常低。

Our networks are much more efficient, the RDMA networks run so much faster.

我們的網路效率更高，RDMA 網路運行速度更快。

If you run twice as fast, our costs go down by half.

如果你跑得快一倍，我們的成本就會降低一半。

And our networks are much faster than the other clouds.

我們的網路比其他雲端快得多。

So we think our potential as we scale our potential to deliver much better margins they're currently delivering are very real.

因此，我們認為，當我們擴大潛力以提供更好的利潤時，我們的潛力是非常真實的。

So is it safe for me to assume that then the upside you keep putting up and you hopefully will continue to do, will add it and that profit will actually increase as a percentage of the margins will also increase over time?

那麼，我是否可以安全地假設，您不斷提出的好處，並且您希望繼續這樣做，將會增加它，並且利潤實際上會增加，因為利潤率的百分比也會隨著時間的推移而增加？

I believe so.

我相信是這樣。

And I believe, for example, I mean I think you'd find different points of view from different engineers as we move Fusion to Autonomous Database.

我相信，例如，我的意思是，當我們將融合轉移到自治資料庫時，您會發現不同工程師的不同觀點。

I think the cost savings -- our cost -- our cloud cost savings will be around 50%.

我認為成本節約——我們的成本——我們的雲端成本節約將在 50% 左右。

That's what I believe.

這就是我所相信的。

Now it might be 40%, it might be 35%, but there will be huge cost savings from where we are now, and that's across the entire base of Fusion customers.

現在可能是 40%，也可能是 35%，但從我們現在的情況來看，將會節省大量成本，而且這涉及整個 Fusion 客戶群。

So that's just one example of how we're using faster networks, faster databases, more automation to make our products more secure.

這只是我們如何使用更快的網路、更快的資料庫和更多自動化來使我們的產品更安全的例子之一。

And I keep emphasizing the security is really the primary goal.

我一直強調安全確實是首要目標。

But as a second order effect, we also end up spending a lot less money to run those data centers.

但作為二階效應，我們最終也減少了運行這些資料中心的資金。

Your next question comes from the line of Mark Murphy with JPMorgan.

你的下一個問題來自摩根大通的馬克墨菲。

Congrats on the great performance.

恭喜您精彩的表演。

Larry, how do you envision the market transitioning from the AI training phase to the AI inferencing phase?

Larry，您如何看待市場從人工智慧訓練階段過渡到人工智慧推理階段？

There's some debate out there on whether we have an imbalance or a bubble on the front end of the curve because training is compute intensive and then perhaps it recalibrates differently somehow for the inferencing stage, which might be less intensive?

關於曲線前端是否存在不平衡或泡沫存在一些爭論，因為訓練是計算密集型的，然後它可能會以某種方式針對推理階段進行不同的重新校準，而推理階段可能不那麼密集？

Or do you see the potential for high growth kind of all the way through both of these phases?

或者您認為這兩個階段都有高速成長的潛力？

Well, a lot of people think that, Mark, I send a kid to college and then I'm done.

嗯，很多人認為，馬克，我送一個孩子上大學，然後我就完了。

They're training ever.

他們一直在訓練。

I got 4 years of training, and then I can put the kid to work and they'll be doing inferencing.

我接受了四年的培訓，然後我可以讓孩子們工作，他們會進行推理。

And that's not true.

但這不是真的。

This race goes on forever, to build a better and better neural network.

這場競賽將永遠持續下去，以建立一個越來越好的神經網路。

And the cost of that training gets to be astronomical.

而這種培訓的成本將是天文數字。

When I talk about building gigawatt or multi-gigawatt data centers, I mean these AI models, these frontier models are going to -- the entry price for a real frontier model from someone who wants to compete in that area is about $100 billion.

當我談論建立千兆瓦或多千兆瓦資料中心時，我的意思是這些人工智慧模型，這些前沿模型將——對於想要在該領域競爭的人來說，真正的前沿模型的入門價格約1000 億美元。

Let me repeat, around $100 billion.

讓我重複一遍，大約1000億美元。

That's over the next 4, 5 years for anyone who wants to play in that game.

對於任何想玩這款遊戲的人來說，這都是未來 4、5 年的事。

That's a lot of money.

那是很多錢。

And it doesn't get easier.

而且事情也沒有變得更容易。

So there are not going to be a lot of those.

所以這樣的數量不會很多。

I mean we -- this is not the place the list who can actually build one of these frontier models.

我的意思是我們——這不是可以真正建立這些前沿模型之一的清單。

But in addition to that, there are going to be a lot of very, very specialized models.

但除此之外，還會有很多非常非常專業的模型。

I can tell you things that I'm personally involved in, which are using computers to look at, biopsies of slides or CAT scans to discover cancer.

我可以告訴你我個人參與的事情，即使用電腦觀察、切片活檢或 CAT 掃描來發現癌症。

Also, there are also blood tests were for discovery and cancer.

此外，還有用於發現和癌症的血液檢查。

Those tend to be very specialized models.

這些往往是非常專業的模型。

Those tend not necessarily use the foundational the rocks and the ChatGPTs, and the Gemini, they tend to be highly specialized models.

這些不一定使用岩石和 ChatGPT 的基礎，而 Gemini，它們往往是高度專業化的模型。

Trained on image recognition on certain data, I mean, literally millions of biopsy slides, for example, and not much other training data is helpful.

我的意思是，例如，對某些資料進行影像辨識訓練，實際上是數百萬張活檢幻燈片，而沒有太多其他訓練資料有幫助。

.

。

So that goes on, and we'll see more and more applications look at that.

這樣下去，我們將看到越來越多的應用程式關注這一點。

So I wouldn't -- if your horizon is over the next 5 years, maybe even the next 10 years, I wouldn't worry about, hey, we've now trained all the models we need and all we need to do is inferencing.

所以我不會——如果你的視野是未來 5 年，甚至是未來 10 年，我不會擔心，嘿，我們現在已經訓練了我們需要的所有模型，我們需要做的就是推理。

I think this is an ongoing battle for technical supremacy that will be fought by a handful of companies and maybe one nation state over the next 5 years at least, but probably more like 10.

我認為這是一場持續不斷的技術霸權之戰，至少在未來 5 年（但可能更可能是 10 年）內，少數公司甚至可能是一個民族國家將參與其中。

So this business is just growing larger and larger and larger.

所以這個業務正在變得越來越大。

There's no slowdown or shift coming.

不會出現任何放緩或轉變。

Let me say something that's going to sound really bizarre.

讓我說一些聽起來很奇怪的事情。

Well, I probably -- you'd probably say, well, he says bizarre things all the time.

好吧，我可能——你可能會說，好吧，他總是說一些奇怪的話。

So why is he announcing this one?

那他為什麼要宣布這項消息呢？

Let's be really bizarre.

讓我們變得非常奇怪。

So we're in the middle of designing a data center that's north of the gigawatt that has -- but we found the location and the power place we look at it, they've already got building permits for 3 nuclear reactors.

因此，我們正在設計一個位於千兆瓦以北的資料中心，但我們找到了我們查看的位置和電力場所，他們已經獲得了 3 個核反應器的建造許可。

These are the small modular nuclear reactors to power the data center.

這些是為資料中心供電的小型模組化核反應器。

This is how crazy it's getting.

這就是它變得多麼瘋狂。

This is what's going on.

這就是正在發生的事情。

Your next question comes from the line of Raimo Lenschow with Barclays.

你的下一個問題來自巴克萊銀行的 Raimo Lenschow。

Just a question more on the database side on the agreements that you just announced today or that you have in place and now added with AWS.

只是關於資料庫方面的一個問題，涉及您今天剛剛宣布的協議，或者您已經與 AWS 簽訂的協議，現在又添加了該協議。

So now do we have all the hyperscaler agreements in play.

現在我們已經擁有了所有的超大規模協議。

How do you think about that migration movements from database workloads that are at the moment running on-premise or on cloud customer to the public cloud?

您如何看待從目前在本地或雲端客戶上運行的資料庫工作負載到公有雲的遷移？

I mean how should we think about that momentum?

我的意思是我們該如何看待這種勢頭？

You think going to excel -- No, you go ahead, Larry.

你認為自己會出類拔萃——不，你繼續吧，拉里。

No, no, no.

不，不，不。

I think you're right.

我認為你是對的。

Well, there's 2 things.

嗯，有兩件事。

Public cloud is very interesting and it's very important.

公有雲非常有趣，也非常重要。

I mean I mean Oracle became very successful in the database is just a long time ago because one of our watch words was portability.

我的意思是，Oracle 很久以前就在資料庫領域取得了非常成功，因為我們的口號之一是可移植性。

We ran an IBM main frames.

我們運行 IBM 大型主機。

We ran on Microsoft PCs.

我們在 Microsoft PC 上運行。

We ran on Hewlett Packard machines.

我們在惠普機器上運行。

And if you remember them, digital equipment machines and all sorts of computers, we ran everywhere.

如果你還記得的話，數位設備機器和各種計算機，我們到處跑。

And that was very important to our customers could run the Oracle database in any environment.

這對於我們的客戶可以在任何環境中運行 Oracle 資料庫來說非常重要。

And it's obviously -- and we had to find a way to actually make the best versions of our database, the Exadata, excess scale versions of our database available in other people's clouds.

顯然，我們必須找到一種方法來真正使我們的資料庫（Exadata）的最佳版本，以及我們資料庫的超大規模版本在其他人的雲端中可用。

And what we're able to do is basically get OCI smolt that we could embed an OCI data center within Microsoft Azure or an OCI data center within Google or AWS or wherever we had to put.

我們能夠做的基本上是讓 OCI smolt 能夠在 Microsoft Azure 中嵌入 OCI 資料中心，或在 Google 或 AWS 中或我們必須放置的任何地方嵌入 OCI 資料中心。

It could be fully autonomous, where we could use Exadata and excess clusters.

它可以是完全自主的，我們可以使用 Exadata 和多餘的叢集。

We actually were able to do that.

我們實際上能夠做到這一點。

It was not technically easy, but we did it.

這在技術上並不容易，但我們做到了。

In doing that and miniaturizing our Oracle data servers, one is I mentioned earlier that all of our data centers are the same except in scale.

在這樣做和小型化我們的 Oracle 資料伺服器時，我之前提到過，除了規模之外，我們所有的資料中心都是相同的。

The biggest one is 800 gigawatts right now, bordering getting close to [ 800 ] megawatts, excuse me, we're getting close to 1 gigawatt.

目前最大的是 800 吉瓦，接近 [ 800 ] 兆瓦，對不起，我們正在接近 1 吉瓦。

The smallest are about 150 kilowatts, and we're going to get down to 50 kilowatts.

最小的約為 150 千瓦，我們將降至 50 千瓦。

What that means is we'll have a lot of companies, medium large-sized companies that will decide to have an Oracle private cloud.

這意味著我們將有許多公司、大中型公司決定擁有 Oracle 私有雲。

I mean it's still -- there's no difference between our private cloud and the public cloud.

我的意思是，我們的私有雲和公有雲之間沒有區別。

They are identical.

它們是相同的。

They're absolutely identical.

它們完全一樣。

And a bunch of people have Oracle -- have a private cloud, a bunch of industrial companies, has Oracle private clouds, for example, to run their workloads.

一群人擁有 Oracle——擁有私有雲，一群工業公司擁有 Oracle 私有雲，例如，來運行他們的工作負載。

But they're becoming so inexpensive that anyone can decide, okay, I want to move to the cloud.

但它們變得如此便宜，以至於任何人都可以決定，好吧，我想遷移到雲端。

I want all the advantages in the cloud, but I want to make sure that I'm the only one in the cloud.

我想要雲端中的所有優勢，但我想確保我是雲端中唯一的。

I don't want any neighbors or I want only approved neighbors.

我不需要任何鄰居，或我只想要經過批准的鄰居。

I don't want someone with a credit card moving in.

我不希望有信用卡的人搬進來。

I'm just paranoid about security where I've got government regulations I have to adhere to.

我只是對安全感到偏執，因為我必須遵守政府法規。

So we think that obviously, moving with Oracle database available in AWS, Microsoft and Google is incredibly important.

因此，我們認為顯然，使用 AWS、微軟和谷歌中提供的 Oracle 資料庫非常重要。

And Safra said it.

薩弗拉也這麼說了。

I mean it will absolutely accelerate database growth in the public cloud.

我的意思是，它絕對會加速公有雲中資料庫的成長。

But we expect that private clouds will greatly outnumber public clouds as companies decide they don't want it.

但我們預期私有雲的數量將大大超過公有雲，因為公司決定不再需要它。

They want the Oracle Cloud behind their firewall in their data center with no neighbors.

他們希望 Oracle 雲端位於資料中心的防火牆後面，沒有鄰居。

And we -- because we've gotten our data center -- our data centers are so automated and they're scalable, and they're all identical in terms of function, we're organized.

而我們——因為我們已經有了自己的資料中心——我們的資料中心是如此自動化，而且是可擴展的，而且它們在功能方面都是相同的，我們是有組織的。

So we can -- actually, we have 162 data centers now.

所以我們可以——實際上，我們現在有 162 個資料中心。

I expect we will have 1,000 or 2,000 or more data centers.

我預計我們將擁有 1,000 個或 2,000 個甚至更多的資料中心。

[Audio Gap]

[音頻間隙]

It's hard for me to predict whether the private clouds or the public cloud which is going to be bigger?

我很難預測私有雲和公有雲哪個會比較大？

I don't know.

我不知道。

The good news is we win either way.

好消息是我們無論如何都會贏。

Your next question comes from the line of Mark Moerdler with Bernstein.

你的下一個問題來自馬克·莫德勒（Mark Moerdler）和伯恩斯坦（Bernstein）的對話。

Congratulations on the quarter.

恭喜本季。

Very impressive both the quarter and the guide.

該季度和指南都非常令人印象深刻。

We've seen a lot of focus on the model training side, but less on applications and inferencing in the rest.

我們看到人們對模型訓練的關注很多，但對其他方面的應用和推理的關注較少。

You guys have a lot of expertise in the market and in the industry.

你們在市場和行業方面擁有豐富的專業知識。

You already have traditional AI sprinkled throughout all the Oracle products and capabilities.

您已經在所有 Oracle 產品和功能中融入了傳統人工智慧。

But where do you see the monetizable value of GenAI on the app side?

但你從哪裡看到 GenAI 在應用程式端的變現價值呢？

How long do you think it's going to take for GenAI to be a meaningful revenue, not just for Oracle, but software in general, on the app side, not on the training side?

您認為 GenAI 需要多長時間才能成為有意義的收入，不僅對於 Oracle，而且對於整個軟體，在應用程式方面，而不是在培訓方面？

Well, let me -- I'm sorry, I'm monopolizing these answers.

好吧，讓我——抱歉，我壟斷了這些答案。

I apologize.

我道歉。

But let me start with health care from everything from us helping doctors diagnose different diseases.

但讓我從醫療保健開始，我們幫助醫生診斷不同的疾病。

When someone goes in to get a sonogram, and I've seen the nurses and the technicians and the doctors actually measure the baby skull and measure the baby's spinal cord to see how -- It's utterly ridiculous.

當有人進去做超音波檢查時，我看到護士、技術人員和醫生實際上測量了嬰兒的頭骨並測量了嬰兒的脊髓，看看情況如何——這完全是荒謬的。

The computer should do all of that.

計算機應該完成所有這些工作。

And if there's an umbilical wrapped around the fetus the computers should discover all of that, and now it should all be recorded.

如果胎兒周圍有臍帶，電腦應該會發現所有這些，現在所有這些都應該被記錄下來。

The doctor could get assistance from a computer doing all of this stuff.

醫生可以從電腦上獲得幫助來完成所有這些事情。

Looking at the plaque and coronary arteries, all should be done that way.

查看斑塊和冠狀動脈，一切都應該這樣做。

Already, we've delivered when a doctor business gets ready to vision to the patient, we prepare a summary for the doctor.

我們已經做到了，當醫生業務準備好向患者展示願景時，我們會為醫生準備一份摘要。

We use AI to look at the electronic health records the latest labs that might've been just a few hours ago.

我們使用人工智慧來查看可能就在幾個小時前的最新實驗室的電子健康記錄。

And let the doctor know whether there's stability or disease progression or whatever the doctor needs to know prior to the consultation with the patient.

在與患者會診之前，讓醫生知道病情是否穩定或進展，或醫生需要知道的任何資訊。

That summary is created by AI, human readable summary.

該摘要是由人工智慧創建的、人類可讀的摘要。

Then AI listens to the consultation to between the doctor and the patient.

然後AI聽取醫生和患者之間的諮詢。

This is already delivered.

這已經交付了。

This is already out there.

這已經存在了。

They'll deliver the listen to the consultation of doctors with the patient.

他們會向病人傳達醫師的諮詢意見。

If the doctor orders a prescription, the AI checks to make sure the prescription is accurate and enters the prescription.

如果醫生開了處方，人工智慧會檢查以確保處方準確並輸入處方。

The AI updates the electronic health records.

人工智慧更新電子健康記錄。

The AI transcribes and distributes the doctors' orders, all from listening to the conversation.

人工智慧透過聆聽對話來轉錄和分發醫生的醫囑。

The doctor then gets a draft at the end of the conversation that the doctor can quickly review and approve.

然後，醫生在談話結束時得到一份草稿，醫生可以快速審查和批准。

And then the prescriptions are filled and the orders are executed and the electronic health records are updated.

然後配藥、執行訂單並更新電子健康記錄。

We're already doing all of that.

我們已經在做這一切了。

But I can go on in health care needs so many things from reading of X-rays to just the user interface.

但我可以繼續討論醫療保健方面的需求，從 X 光的讀取到使用者介面。

Our user interface is so different than Epic.

我們的使用者介面與 Epic 非常不同。

I was at Stanford with my son at one time and to 3 people, 3 different positions to actually be able to find his X-rays.

有一次我和我兒子在史丹佛大學，三個人，三個不同的位置，才真正能夠找到他的 X 光片。

This is how you find the X-rays for Larry Ellison.

這就是找到拉里·埃里森的 X 光片的方法。

You say, Oracle, please show me Larry Ellison's latest X-ray.

你說，甲骨文，請給我看拉里·埃里森最新的 X 光片。

It's a voice interface.

這是一個語音介面。

You just ask for them.

你只需要求他們。

How do you log on?

你如何登入？

Well, you look at the computer and it recognizes your face.

好吧，你看著電腦，它會辨識你的臉。

It recognizes your voice, that knows you're the doctor and you're authorized to look at that, all the authorization is done with AI.

它辨識你的聲音，知道你是醫生，你有權利查看，所有授權都是透過人工智慧完成的。

When are we going to start monetizing it?

我們什麼時候開始將其貨幣化？

Well, all of Cerner is the monetization.

好吧，Cerner 的一切都是為了貨幣化。

The fact that we can dramatically expand our health business is because it's based on AI.

我們之所以能夠大幅擴展我們的健康業務，是因為它是基於人工智慧。

It is -- AI is just -- I don't know how to describe it.

人工智慧只是——我不知道如何描述它。

I mean the best way to describe it.

我的意思是描述它的最好方式。

It's not something you sell separately.

這不是您單獨出售的東西。

It's the diagnostic system.

這是診斷系統。

It's the electronic health record system.

這就是電子健康記錄系統。

It is -- the pharmacy system, this prescription system, the user authentication, the log-in system, it's all AI.

它是——藥房系統、處方系統、使用者身份驗證、登入系統，都是人工智慧。

And I know people think it's a separate thing that, "Oh my God."

我知道人們認為「天哪」是一件獨立的事情。

And I hear a bunch of applications come say, "Oh, we've now got AI agents for separately.

我聽到很多應用程式說：「哦，我們現在有了單獨的人工智慧代理。

I mean -- it's -- our applications are going to be primarily AI applications, everything.

我的意思是——我們的應用程式將主要是人工智慧應用程序，一切。

How do you turn separately for everything

怎麼把所有事情都分開

[Audio Gap]

[音頻間隙]

SP1 Your next question comes from the line of Derrick Wood with TD Cowen.

SP1 您的下一個問題來自 Derrick Wood 和 TD Cowen。

Congratulations.

恭喜。

Safra, Larry, you guys have had this big inflection in RPO growth over the last few quarters.

Safra、Larry，你們在過去幾季的 RPO 成長中出現了巨大的變化。

Could you update us on how you're feeling about supply availability and your ability to stand up data center infrastructure in a time-efficient manner in order to move from contract signing to consumption and convert backlog into revenue?

您能否向我們介紹一下您對供應可用性的看法，以及您是否有能力以高效的方式建立資料中心基礎設施，以便從合約簽署轉向消費並將積壓訂單轉化為收入？

And I guess, are you doing anything different today than, say, a year ago to try and help accelerate these time lines?

我想，您今天所做的事情是否與一年前不同，以嘗試幫助加快這些時間線？

Okay.

好的。

I'm going to start and Larry can finish.

我來開始，拉里來完成。

So we have enormous demand that is absolutely true.

所以我們有巨大的需求，這是絕對正確的。

And I will say that demand is still outstripping supply.

我要說的是，需求仍然超過供應。

But I can live with that because we are laying out a lot of supply.

但我可以忍受這一點，因為我們正在佈置大量供應。

As you can see, in the revenues and you're going to -- and you can see that in the guidance and my commitment for this next year, and we'll be talking about beyond on Thursday of Financial Analyst Day.

正如您所看到的，在收入中，您將在明年的指導和我的承諾中看到這一點，我們將在周四的金融分析師日討論更多內容。

We have made a number of changes, including what Larry mentioned earlier, which is the automation of the setting up and laying down our data centers.

我們做出了許多改變，包括拉里之前提到的，即設定和鋪設資料中心的自動化。

However, there are -- because demand is so large, we do have to get in different places.

然而，由於需求如此之大，我們確實必須進入不同的地方。

As I told you I don't know, a couple of quarters to grow.

正如我告訴你的，我不知道，還需要幾個季度的成長。

We made the decision instead of picking up small pieces to actually wait in some cases, to pick up larger locations.

我們做出了決定，而不是在某些情況下挑選小塊來實際等待，而是挑選更大的位置。

And that is really playing out very, very well for us.

這對我們來說確實非常非常好。

But we are really moving and growing in so many places because it's not only public cloud rollouts, but it is also private clouds, which are in immense demand, national security regions, immense demand.

但我們確實在許多地方取得了進展和成長，因為這不僅是公有雲的推出，還有私有雲的需求，國家安全領域的需求也很大。

And really, we are moving as fast as we can, and automation is the thing that has helped us lay this out.

事實上，我們正​​在盡可能快地前進，自動化幫助我們解決了這個問題。

And the fact that it is -- we have an everything everywhere means nothing is unique.

事實上，我們到處都有一切，這意味著沒有什麼是獨一無二的。

Everything is the same, and that cannot be set by our competitors, and that helps us in our rollout.

一切都是一樣的，這是我們的競爭對手無法設定的，這有助於我們的推出。

I just want to emphasize what Safra just said.

我只是想強調薩夫拉剛才所說的話。

Our private clouds are identical to our public clouds, except for the fact they might only have one tenant, and it might be in a building that you own.

我們的私有雲與公有雲相同，只是它們可能只有一個租戶，而且可能位於您擁有的一棟大樓中。

Besides that, they're identical.

除此之外，它們是相同的。

We own the hardware.

我們擁有硬體。

We measure the hardware for you.

我們為您測量硬體。

It just happens to be in a building you own, and you're the only one that can get in.

它恰好位於您擁有的建築物中，並且您是唯一可以進入的人。

So that's a very different situation than all of our competitors, and it's fully automated.

因此，這與我們所有競爭對手的情況非常不同，而且它是完全自動化的。

So we're prepared to manage thousands of data centers.

因此，我們準備好管理數千個資料中心。

By the way, I would compare that to Sterling, where he's got, I think, close to 7,000 satellites in the Starlink [ 800 ] How do you manage -- these satellites constantly maneuver.

順便說一句，我會將其與斯特林進行比較，我認為他在星鏈中擁有近 7,000 顆衛星 [800] 你如何管理 - 這些衛星不斷機動。

They don't -- they're not geosynchronous satellites.

它們不是地球同步衛星。

Their low earth orbiting satellites.

他們的近地軌道衛星。

So they're constantly flying around and changing location.

所以它們不斷地飛來飛去並改變位置。

How do you manage 7,000 spacecraft flying around?

如何管理7000艘四處飛行的太空船？

Well, let me tell you, computers, it's got to be fully automated or it's not going to work.

好吧，讓我告訴你，計算機，它必須是完全自動化的，否則它就不起作用。

You can't have thousands even hundreds, I would say, data centers you can't have, but you certainly can have thousands of data centers unless they're fully automated.

我想說，你不可能擁有數千甚至數百個資料中心，但你當然可以擁有數千個資料中心，除非它們是完全自動化的。

And the only way you can automate something is to make them all the same.

實現自動化的唯一方法就是使它們全部相同。

You can't automate 25 different things.

你無法將 25 件不同的事情自動化。

So that's one thing.

所以這是一回事。

The other thing I'll point out, and I think it's interesting about Oracle, that some of the most senior people in our management team are experts in building, buildings, building electric power plants and electric transmission systems.

我要指出的另一件事是，我認為甲骨文很有趣，我們管理團隊中的一些最資深的人是建築、建築、發電廠和輸電系統的專家。

Because building these data centers is just that.

因為建造這些資料中心就是這樣。

You can't just build a data center.

您不能僅僅建立一個資料中心。

You also have to account for the energy and the transmission of the energy from where it's generated to the data center.

您還必須考慮能源以及能源從產生地到資料中心的傳輸。

And of course, the most efficient way to do this is actually build the generation -- the power generation plant right next to the data center.

當然，最有效的方法實際上是在資料中心旁邊建造發電站。

So you transmit over the short -- over the shortest distance.

所以你可以透過最短的距離進行傳輸。

And we actually have very senior people who are very -- actually come from the utilities industry as strange as that sounds, that are expert in doing this and helping us build these gigantic projects.

我們實際上有非常資深的人員，他們實際上來自公用事業行業，儘管聽起來很奇怪，但他們是這方面的專家，並幫助我們建立這些巨大的項目。

Again, I'll Elon Musk.

再說一次，我會是伊隆馬斯克。

One of the hardest jobs he had in building Tesla was when he built the Austin plant, he had to build the largest building ever been built by human kind anywhere at any time.

他在建造特斯拉過程中最艱鉅的工作之一是建造奧斯汀工廠，他必須隨時隨地建造人類有史以來建造的最大的建築。

And then he want to know the largest building ever built.

然後他想知道有史以來最大的建築。

It certainly is not the Pentagon.

它肯定不是五角大廈。

It's not the NASA building for the space shuttle.

這不是美國太空總署太空梭大樓。

Largest building is the Tesla plant.

最大的建築是特斯拉工廠。

And so you have to be the contractor of that plant.

所以你必須是該工廠的承包商。

You have to be able to build those things and then fill it with robots that then build your cars.

你必須能夠建造這些東西，然後用機器人填滿它，然後建造你的汽車。

So you got to build the building, get the power, build all the automation systems, which is the hardest part about building the cloud or building automation system, build all the automation systems, so it works efficiently and reliably and cost effectively.

因此，您必須建造建築物，獲得電力，建造所有自動化系統，這是建造雲端或樓宇自動化系統最困難的部分，建造所有自動化系統，使其高效、可靠且具有成本效益地運作。

That is -- and we have some really interesting people here with a very different experience base than we had even 5 years ago.

也就是說，我們這裡有一些非常有趣的人，他們的經驗基礎與 5 年前截然不同。

Your final question comes from the line of Brad Zelnick of Deutsche Bank.

你的最後一個問題來自德意志銀行的 Brad Zelnick。

And I'll just start by saying I can't remember a Q1 ever being this exciting.

首先我要說的是，我不記得 Q1 曾經如此令人興奮。

Larry, we've talked about a lot of the reasons why you win in cloud infrastructure, especially by addressing areas of the market where your competitors can't even reach.

Larry，我們已經討論了您在雲端基礎設施領域獲勝的許多原因，特別是透過解決競爭對手甚至無法到達的市場領域。

But in light of many high-profile cyber incidents lately, can you talk about how being more secure, not just in being so highly automate as you've already discussed, but how is it being more secure, helping to win some of these very large OCI deals especially in the U.S. and other governments around the world?

但鑑於最近發生了許多備受矚目的網路事件，您能否談談如何變得更加安全，不僅僅是像您已經討論過的那樣高度自動化，而是如何變得更加安全，幫助贏得其中一些非常大型OCI 交易，尤其是在美國和世界其他國家政府的交易？

Well, I couldn't thank you more for the question because I have 2 things I'm talking about a Cloud World on Tuesday.

好吧，我非常感謝你提出這個問題，因為星期二我有兩件事要談論雲端世界。

One is multi-cloud and the other is security.

一是多雲，二是安全。

And let me announce right here, we're done with passwords.

讓我在這裡宣布，我們已經不再使用密碼了。

The idea is utterly ridiculous.

這個想法是完全荒謬的。

They're easily hacked.

他們很容易被駭客攻擊。

The more difficult they are to remember, the more likely you are to write them down, the more likely they are to be stollen.

它們越難記住，你就越有可能把它們寫下來，它們就越有可能被偷。

Everything done to make passwords better has made them worse.

為使密碼變得更好而所做的一切卻讓密碼變得更糟。

It's a terrible idea.

這是一個糟糕的主意。

So we're getting rid of passwords entirely.

因此，我們將完全擺脫密碼。

This is the way log on is going to work.

這就是登入的工作方式。

I'm going to type in larry.ellisonoracle.com, the computer is going to look at me and say, "Okay, Larry, we're done.

我要輸入 larry.ellisonoracle.com，計算機會看著我說：「好吧，拉里，我們完成了。

Why would I type in a Safra can recognize me.

為什麼我輸入Safra能認出我。

My kids can recognize me.

我的孩子能認出我。

You're telling me a computer can't recognize me in LogMeIn.

您告訴我計算機無法在 LogMeIn 中識別我。

This is ridiculous.

這太荒謬了。

So we're not -- no more passwords.

所以我們不再需要密碼。

Those have got to go.

那些必須離開。

There are other things we can do to secure network communications and -- we have this new technology actually goes live in our cloud this week called Zipper, it's called Zero Trust Packet Routing, that I'll be talking about.

我們還可以採取其他措施來保護網路通訊的安全，而且- 我們本週實際上在我們的雲端中啟用了這項名為Zipper 的新技術，它被稱為零信任資料包路由，我將討論這一點。

And it guarantees the -- while biometric authentication will guarantee that you are who you say you are when you log in.

它保證了——而生物識別身份驗證將保證您在登入時就是您所說的身份。

So we'll know so users -- fraudulent users will find it very difficult to infiltrate our systems with biometric authentication.

所以我們會知道，用戶——欺詐性用戶將發現很難透過生物識別身份驗證滲透我們的系統。

And by the way, there are keys on the keyboard that will look at your fingerprint.

順便說一句，鍵盤上的按鍵可以查看您的指紋。

It depends on how -- if you want face recognition plus fingerprints, all voluntary.

這取決於如何——如果你想要臉部辨識加指紋，一切都是自願的。

You don't have to do it if you don't want to.

如果您不願意，則不必這樣做。

But certainly a whole bunch of people prefer biometric authentication.

但肯定有很多人更喜歡生物辨識認證。

That's why Google Pay is popular and Apple Pay is popular.

這就是為什麼 Google Pay 很受歡迎，Apple Pay 很受歡迎。

So it's from my convenience.

所以這是從我的方便出發。

I don't want to remember passwords.

我不想記住密碼。

Look at me and recognize me and log them in.

看著我並認出我並登入。

Don't ask me to type in some stupid 17 letter password, that someone can steal.

不要讓我輸入一些愚蠢的 17 個字母的密碼，以免有人竊取。

There is that.

有那個。

The Zero Trust packet routing actually authenticates you from the user all the way to the data.

零信任資料包路由實際上會對您從使用者一直到資料進行身份驗證。

And we've greatly simplified network security by separating it from network configuration.

我們透過將網路安全與網路配置分離來大幅簡化了網路安全。

That's another thing I'm going to talk about.

這是我要談的另一件事。

But by the way, let me go about automation.

但順便說一句，讓我談談自動化。

Automation is more of a security issue than it is an efficiency issue.

自動化更多的是安全問題，而不是一個效率問題。

Automated cars, self-driving cars will kill a lot fewer people every year than human drivers.

自動駕駛汽車、自動駕駛汽車每年造成的死亡人數將比人類駕駛少得多。

They don't get drunk.

他們不會喝醉。

They don't go 135 miles an hour.

他們的時速不會達到 135 英里。

Automation is a safety issue and a security issue.

自動化是安全問題，也是保障問題。

All -- almost all cyberattacks begin the same way with human error.

所有——幾乎所有網路攻擊都是以相同的方式從人為錯誤開始。

If there is no Oracle database administrator as there isn't with the autonomous database, the data -- the DBA cannot make a configuration mistake that exposes your data. you can't have a human being involved if you want to make your data secure.

如果沒有像自治資料庫那樣的 Oracle 資料庫管理員，那麼 DBA 就不會犯下導致資料外洩的配置錯誤。如果您想確保資料安全，就不能有人參與。

Autonomy is a huge portion of it.

自治是其中很大一部分。

And the fourth piece of security that I'll talk about is code generation.

我要討論的第四安全問題是程式碼產生。

When you generate a computer program rather than hand write it in Java, hey, we're the owners of Java or I don't know.

當您生成計算機程式而不是用 Java 手動編寫它時，嘿，我們是 Java 的所有者，或者我不知道。

Maybe this spring grid said, we're not the owners of Java.

也許這個春天網格說，我們不是Java的所有者。

I'm not sure.

我不知道。

I'm not sure what it even means.

我什至不確定它是什麼意思。

I'm not a lawyer.

我不是律師。

But if the computer generates the program rather than a human being writing it, the computer will not generate security vulnerabilities.

但如果電腦生成程式而不是人類編寫程序，則電腦將不會產生安全漏洞。

They will not generate something called state which means your application can't favor automatically in case your data center loses power or burns down or something like that.

它們不會產生稱為狀態的東西，這意味著如果您的資料中心斷電或燒毀或類似情況，您的應用程式無法自動支援。

Code generation is a huge portion of next-generation security.

程式碼產生是下一代安全性的重要組成部分。

Zero trust packet routing is another important one biometric authentication and automation are all are the 4 key attributes to winning the cyber war.

零信任資料包路由是另一個重要因素，生物辨識身分驗證和自動化都是贏得網路戰爭的 4 個關鍵屬性。

It's going to be our defensive robots against their robots, and we have to have better technology on the defensive side than they currently have on the offensive side because they are winning.

這將是我們的防守機器人對抗他們的機器人，我們在防守端必須擁有比他們目前在進攻端更好的技術，因為他們正在獲勝。

I mean every year, there are more -- there's more successful cyber attacks.

我的意思是，每年都會有更多、更成功的網路攻擊。

And you know what the FBI says when you're attacked, pay the ransom there's something we can do about it.

你知道當你受到攻擊時聯邦調查局會說什麼，支付贖金我們可以做些什麼。

Well, that's not very encouraging.

嗯，這不太令人鼓舞。

I have an idea.

我有一個主意。

Let's keep the ransom money, but implement next-generation technology that makes it much harder for cyber criminals.

讓我們保留贖金，但實施下一代技術，讓網路犯罪分子變得更加困難。

And by the way -- and it's not so bad with cyber criminals now compared to what state actors have the ability to do.

順便說一句，與國家行為者有能力做的事情相比，現在網路犯罪分子的情況並沒有那麼糟糕。

So we have to harden our computer systems.

所以我們必須強化我們的電腦系統。

We have to make them more secure.

我們必須讓它們更加安全。

The good news is there is a whole new generation of AI-based security systems like biometric authentication, like zero-trust packet routing that we can use to stop these attacks, but we have to actually deploy the technology.

好消息是，我們可以使用全新一代基於人工智慧的安全系統，例如生物識別身份驗證、零信任資料包路由來阻止這些攻擊，但我們必須實際部署該技術。

Thank you, Brad.

謝謝你，布拉德。

Thank you, Larry.

謝謝你，拉里。

A telephonic replay of this conference call will be available for 24 hours on our Investor Relations website.

我們的投資者關係網站將提供 24 小時電話會議的電話重播。

Thank you for joining us today.

感謝您今天加入我們。

And with that, I'll turn the call back to Sarah for closing.

然後，我會將電話轉回給莎拉以結束。

Thank you.

謝謝。

This concludes today's conference call.

今天的電話會議到此結束。

We thank you for joining.

我們感謝您的加入。

You may now disconnect your lines.

現在您可以斷開線路。