Ambarella, Inc. (AMBA) 2027 Q2 法說會逐字稿

Thank you for standing by, and welcome to the Ambarella's second quarter fiscal year 2027 earnings call. (Operator Instructions) As a reminder, today's program is being recorded.

感謝您稍候，歡迎參加 Ambarella 2027 會計年度第二季財報電話會議。(接線員指示) 提醒您，今日的會議將被錄音。

And now I'd like to introduce your host for today's program, Louis Gerhardy, Vice President, Corporate Development. Please go ahead, sir.

現在我想介紹今日會議的主持人：企業發展副總裁 Louis Gerhardy。先生，請開始。

Thank you, Jonathan, and good afternoon. Thank you for joining our second quarter fiscal year 2027 financial results conference call. On the call with me today is Dr. Fermi Wang, President and CEO; and John Young, CFO. The primary purpose of today's call is to provide you with information regarding the results for our second quarter of fiscal year 2027.

謝謝你，Jonathan，大家下午好。感謝各位參加我們 2027 會計年度第二季財務結果電話會議。今天與我一同出席的有總裁暨執行長 Fermi Wang 博士，以及財務長 John Young。今日會議的主要目的，是向各位提供我們 2027 會計年度第二季業績相關資訊。

The discussion today and the responses to your questions will contain forward-looking statements regarding our projected financial results, financial prospects, market growth and demand for our solutions, among other things. These statements are based on currently available information and subject to risks, uncertainties and assumptions. Should any of these risks or uncertainties materialize or should our assumptions prove to be incorrect, our actual results could differ materially from these forward-looking statements. We're under no obligation to update these statements. These risks, uncertainties and assumptions as well as other information on potential risk factors that could affect our financial results are more fully described in the documents we file with the SEC.

今天的討論以及對各位提問的回覆，將包含前瞻性陳述，內容涉及我們預期的財務結果、財務前景、市場成長以及對我們解決方案的需求等。這些陳述係基於目前可得資訊，並受風險、不確定性與假設影響。若其中任何風險或不確定性成真，或我們的假設被證明不正確，我們的實際結果可能與這些前瞻性陳述存在重大差異。我們沒有義務更新這些陳述。這些風險、不確定性與假設，以及其他可能影響我們財務結果的潛在風險因素之資訊，已在我們向美國證券交易委員會（SEC）提交的文件中更完整地說明。

Access to our second quarter fiscal year 2027 results press release, transcripts, historical results, SEC filings and a replay of today's call can be found on the Investor Relations page of our website. The content of today's call as well as the materials posted on our website are Ambarella's property and cannot be reproduced or transcribed without our prior written consent.

我們 2027 會計年度第二季業績新聞稿、逐字稿、歷史結果、SEC 申報文件以及今日會議的重播，皆可於本公司網站的投資人關係頁面取得。今日會議內容以及我們網站上張貼的資料均為 Ambarella 之財產，未經我們事先書面同意，不得複製或轉錄。

Before starting the call, we hope to see you at one of the following investor events that we have scheduled in our third quarter. First, on September 8, we'll host a DNB Bus Tour at our offices in Santa Clara. September 9, we'll be at Citi's 2026 Global TMT Conference in New York. September 15, we'll participate in Piper Sandler's Growth Frontiers Conference in Nashville. September 16, we will host Sanford Bernstein's 8th Annual West Coast Semiconductor Bus Tour. And during the week of October 4, we will have a European NDR with cities to be determined. Also available to investors during the third fiscal quarter will be our booth and presentations at the AI Infrastructure Summit in Santa Clara on September 15 to 17. We hope to see you there where we will lead the Physical AI track with a number of edge AI and robotics demos in our exhibit area.

在開始會議之前，我們希望能在第三季已排定的下列投資人活動之一與各位見面。首先，9 月 8 日我們將在聖塔克拉拉（Santa Clara）辦公室舉辦 DNB Bus Tour。9 月 9 日，我們將出席於紐約舉行的花旗 2026 全球 TMT 大會。9 月 15 日，我們將參加於納許維爾（Nashville）舉行的 Piper Sandler Growth Frontiers 大會。9 月 16 日，我們將主辦 Sanford Bernstein 第 8 屆年度西岸半導體 Bus Tour。此外，在 10 月 4 日當週，我們將進行歐洲 NDR，城市尚待確定。第三會計季度期間，投資人亦可參觀我們於 9 月 15 日至 17 日在聖塔克拉拉舉行的 AI Infrastructure Summit 的攤位與簡報。我們期待在現場與各位相見；我們將在展區以多項邊緣 AI 與機器人示範，領銜「Physical AI」主題軌。

Fermi is now going to provide a business update for the quarter. John will review the financial results and outlook, and then the three of us are available for your questions. Fermi?

接下來 Fermi 將提供本季的業務更新。John 將回顧財務結果與展望，之後我們三位將開放回答各位的問題。Fermi？

Thank you, Louis, and good afternoon. Thank you for joining our call today. Driven by a new record level of edge AI revenue, we reported fiscal Q2 revenue slightly above the midpoint of our guidance with non-GAAP EPS of $0.18, and with guidance for seasonal fiscal Q3. By product, we are in the midst of a very steep revenue ramp with our 5-nanometer CV75 and CV72 AI SoCs. And by market, we had sequential growth in both IoT and Auto with automotive revenue driven by commercial vehicles.

謝謝你，Louis，大家下午好。感謝各位今天加入我們的電話會議。在邊緣 AI 營收創下新高的帶動下，我們公布的會計年度第二季營收略高於財測區間中點，非 GAAP 每股盈餘為 0.18 美元，並提供符合季節性的會計年度第三季指引。以產品別來看，我們 5 奈米 CV75 與 CV72 AI SoC 正處於非常陡峭的營收爬坡期。以市場別來看，IoT 與車用皆呈現季對季成長，其中車用營收由商用車帶動。

The market is increasingly recognizing the strategic value of edge AI as well as our edge AI and Physical AI platform leadership. We continue to make significant progress with the expansion of our edge AI platform leadership, including new go-to-market strategies and engineering and market development for a number of new higher-value AI SoCs, some of which extend our reach into entirely new markets.

市場正日益認可邊緣 AI 的策略價值，以及我們在邊緣 AI 與 Physical AI 平台的領導地位。我們持續在擴大邊緣 AI 平台領導力方面取得顯著進展，包括新的市場進入策略（go-to-market strategies），以及針對多款更高價值的新 AI SoC 進行工程與市場開發，其中部分產品將把我們的觸角延伸至全新的市場。

We remain optimistic about the long-term secular growth opportunities in the edge AI market and our R&D priorities are aligned with both the Physical AI markets that represent a vast majority of our total revenue today as well as the robotic and edge infrastructure markets that are in the early stages of developing. Altogether, our technology, product and new go-to-market combined with the significant secular growth in edge AI are increasing our five-year serviceable market forecast today.

我們對邊緣 AI 市場長期的結構性成長機會仍保持樂觀，而我們的研發優先事項同時對齊：一方面是目前占我們總營收絕大多數的 Physical AI 市場；另一方面是仍處於早期發展階段的機器人與邊緣基礎設施市場。綜合而言，我們的技術、產品與新的市場進入策略，再加上邊緣 AI 顯著的結構性成長，正在提高我們目前對未來五年可服務市場（serviceable market）的預測。

Before I review our new market forecast, I would like to step back and discuss the market environment we are in. Demand signals for the application of edge AI remains strong. At the same time, it is obvious that memory vendors and the entire supply chains are prioritizing AI data center demand, which is resulting in rising supply chain costs for everyone.

在我回顧我們新的市場預測之前，我想先退一步談談我們所處的市場環境。邊緣 AI 應用的需求訊號仍然強勁。同時也很明顯，記憶體供應商以及整體供應鏈正優先滿足 AI 資料中心需求，導致所有人的供應鏈成本上升。

Surging memory price and the scarcity of supply are impacting the entire industry. Related to this, we are providing significant assistance to customers who are attempting to create a wide variety of workarounds to the memory situation. Ambarella itself is also facing rising supply chain costs, and we plan to pass this cost to our customers to maintain our long-term gross margin target of 59% to 62%.

記憶體價格飆升以及供應稀缺正在影響整個產業。與此相關，我們正為嘗試針對記憶體情勢制定各種替代方案（workarounds）的客戶提供大量協助。Ambarella 本身也面臨供應鏈成本上升，我們計畫將此成本轉嫁給客戶，以維持我們長期 59% 至 62% 的毛利率目標。

Returning to our rolling five-year serviceable market update, I would like to remind you of our methodology. Our SAM for any given year is based on the products we expect to have available for production in that year, overlaid on the total available market projections from a number of third-party research firms. So our five-year SAM captures any revenue-generating products announced or unannounced on our road map in the next five years. Our prior five-year rolling SAM was announced in May 2025 and projected a five-year fiscal year '26 to fiscal year '31 compounded annual growth rate of about 18%, with Auto representing a slightly higher proportion of the terminal year. Our new five-year rolling SAM from $8.5 billion in fiscal year 2027 to $22.9 billion in fiscal year '32 represents a CAGR of about 20% with IoT markets now representing about 70% of the terminal year.

回到我們滾動式五年可服務市場更新，我想提醒各位我們的方法論。我們在任一年度的 SAM，是以我們預期該年度可供量產的產品為基礎，並疊加多家第三方研究機構對整體可用市場的預測。因此，我們的五年 SAM 涵蓋未來五年產品路線圖中，所有已公布或未公布、可帶來營收的產品。我們先前的五年滾動 SAM 於 2025 年 5 月公布，並預估 2026 會計年度至 2031 會計年度的五年複合年成長率（CAGR）約為 18%，且在終端年度中車用占比略高。我們新的五年滾動 SAM，從 2027 會計年度的 85 億美元成長至 2032 會計年度的 229 億美元，代表 CAGR 約為 20%，且 IoT 市場在終端年度的占比目前約為 70%。

While there are several factors behind the strong growth and the underlying mix change, I will focus on the most important change. In the last year, it has become clear that operational efficiency or the ability of our enterprise to generate more revenue and/or to reduce expenses is likely to be a key driver of our emerging edge infrastructure business. Operational efficiency at the edge refer to the use of open weight and distilled models running on on-premise inferencing hardware in contrast to the large frontier models that run in the cloud. Benefits of this approach include reduced latency, data protection, privacy, lower bandwidth costs and high reliability.

雖然強勁成長與背後的組合變化有多項因素，我將聚焦於最重要的變化。在過去一年中，已明顯可見「營運效率」——亦即企業創造更多營收及／或降低費用的能力——很可能成為我們新興邊緣基礎設施業務的關鍵驅動力。邊緣端的營運效率，指的是使用在地端（on-premise）推論硬體上運行的開放權重與蒸餾模型，對比在雲端運行的大型前沿模型（frontier models）。此作法的優點包括降低延遲、資料保護與隱私、更低的頻寬成本，以及高可靠性。

Target markets include security, retail, lodging, logistics, healthcare and more. The on-premise operational efficiency use case has emerged with growing expectations for sustainable high-volume inferencing and increasingly for agentic AI and Physical AI application that can perceive, reason and ultimately act in the physical world. The key question has become who can help the enterprise lower the cost per useful AI inferencing outcome? This is where Ambarella's superior performance per watt portfolio kicks in, providing the efficient edge intelligence needed to enable this next-generation agentic and Physical AI workload at scale.

目標市場包括安防、零售、旅宿、物流、醫療保健等。隨著市場對可持續的高吞吐量推論需求日增，並且愈來愈期待能感知、推理並最終在物理世界中採取行動的代理式 AI（agentic AI）與 Physical AI 應用，在地端營運效率的使用情境已然浮現。關鍵問題已變成：誰能協助企業降低「每一個有用的 AI 推論結果」的成本？這正是 Ambarella 以每瓦效能（performance per watt）見長的產品組合發揮作用之處，提供所需的高效率邊緣智慧，使下一代代理式與 Physical AI 工作負載得以規模化落地。

With this perspective, in the last year, we have several new products in development targeting on-premise hardware or what is commonly called edge infrastructure. As you know, we already have our N1-655 AI SoC in the market, and we have additional unannounced AI SoCs in development. We also are implementing a stand-alone AI accelerator product line targeting the edge infrastructure market. Together, this new edge infrastructure products, both AI SoCs and stand-alone AI accelerators represent the single most important reason for the upward revisions in our SAM.

從這個角度來看，在過去一年中，我們有數項新產品正在開發中，目標鎖定本地端硬體（on-premise hardware），或一般所稱的邊緣基礎設施（edge infrastructure）。如各位所知，我們的 N1-655 AI SoC 已經在市場上，並且還有其他尚未公布的 AI SoC 正在開發中。我們也正在推動一條獨立式 AI 加速器（stand-alone AI accelerator）產品線，鎖定邊緣基礎設施市場。綜合而言，這些新的邊緣基礎設施產品（包含 AI SoC 與獨立式 AI 加速器）是我們上修 SAM 的最重要單一原因。

Before I introduce our first stand-alone AI accelerator, allow me to be clear about our terminology. We define edge AI SoC as one integrating all of the accelerated computing functions into a single chip, camera perception, AI accelerators, CPUs, encoding and so on. We define an AI accelerator as an AI processor that is not camera specific and targets a wide variety of digital or physical modalities. We believe this type of multi-modality is critical for edge infrastructure applications that target operational efficiency.

在我介紹我們第一款獨立式 AI 加速器之前，先讓我清楚說明我們的術語。我們將邊緣 AI SoC 定義為：把所有加速運算功能整合到單一晶片中，包括相機感知、AI 加速器、CPU、編碼等。我們將 AI 加速器定義為：一種不特定於相機、可支援多種數位或實體模態（modalities）的 AI 處理器。我們相信，這種多模態能力對於以營運效率為目標的邊緣基礎設施應用至關重要。

While not formally announced, I would like to preview one of the new AI accelerators that will anchor this new product category for us with another well-defined, well-performed product already behind it. We refer to this new AI accelerator as X7. This SoC is sampling now and expected to land initial design wins in edge infrastructure applications where it can serve as an AI coprocessor for host processors such as ARM or x86.

雖然尚未正式發布，我想先預告其中一款新的 AI 加速器；它將成為我們這個新產品類別的核心，並且其後還有另一款已經定義清楚、表現優異的產品作為支撐。我們將這款新的 AI 加速器稱為 X7。這顆 SoC 目前正在送樣（sampling），預期將在邊緣基礎設施應用中取得初期設計導入（design wins），可作為 ARM 或 x86 等主處理器的 AI 協同處理器（coprocessor）。

Together with our new product thrust, expanded market reach and the SAM, we expect our revenue growth to be supported with two incremental go-to-market strategies. First is the multistep establishment of indirect sales channel and the second is a semi-custom chip strategy, both of which will augment our existing direct sales efforts.

配合我們新的產品推進、擴大的市場觸及範圍以及 SAM，我們預期營收成長將由兩項新增的市場進入（go-to-market）策略所支撐。第一是多步驟建立間接銷售通路，第二是半客製化晶片策略；兩者都將強化我們既有的直銷努力。

As a reminder, virtually all our revenue is generated by our direct sales teams. And today, I'm excited to announce two material partnership agreements to develop our indirect sales channel. Combined, these two partnership plan to drive a significant amount of incremental revenue over the next seven years through customers who have largely been unserved by us so far. First, today, we announced Ambarella's strategy partner with CapGemini designed to help enterprise adopt edge AI and Physical AI solution faster by reducing the complexity of moving from evaluation to scalable deployment.

提醒各位，我們幾乎所有營收都是由直銷團隊所創造。而今天，我很高興宣布兩項具實質意義的合作夥伴協議，以發展我們的間接銷售通路。合計而言，這兩項合作計畫預期在未來七年，透過迄今我們大多尚未服務到的客戶，帶來可觀的新增營收。首先，今天我們宣布 Ambarella 與策略夥伴 CapGemini 的合作，旨在透過降低從評估到可規模化部署的複雜度，協助企業更快採用邊緣 AI 與 Physical AI 解決方案。

By combining Ambarella's power-efficient AI software and platforms with CapGemini's global engineering, system integration and industry expertise, the partnership aims to help customers improve operational efficiency, enhance real-time decision-making and deploy intelligent system and in physical world environment with greater speed, scalability and confidence.

透過結合 Ambarella 具高能效的 AI 軟體與平台，以及 CapGemini 的全球工程能力、系統整合與產業專業，該合作旨在協助客戶提升營運效率、強化即時決策，並以更高的速度、可擴展性與信心，在實體世界環境中部署智慧系統。

In our second partnership to develop our indirect channel, today, we also announced a seven-year agreement with Macnica, a leading global technical distributor. Macnica will support both Ambarella's Physical AI and the new edge infrastructure products by developing and supporting an independent software vendor ecosystem, including onboarding, technical integration support and joint go-to-market progress. With this ecosystem in place, Ambarella solution can be offered as individual component or as a complete bundle for multiple edge AI vertical markets, including video analytics, smart city, edge computing platforms, robotics, industrial IoT, intelligent transportation systems, retail analytics, security and surveillance.

在我們發展間接通路的第二項合作中，今天我們也宣布與全球領先的技術型通路商 Macnica 簽署一項為期七年的協議。Macnica 將透過建立並支援獨立軟體供應商（ISV）生態系，來支援 Ambarella 的 Physical AI 與新的邊緣基礎設施產品，包括導入（onboarding）、技術整合支援以及共同市場推進（joint go-to-market）進展。在此生態系到位後，Ambarella 的解決方案可作為單一元件提供，或以完整套裝形式提供給多個邊緣 AI 垂直市場，包括影片分析、智慧城市、邊緣運算平台、機器人、工業物聯網（industrial IoT）、智慧運輸系統、零售分析、安全與監控。

I want to emphasize the importance of the indirect channel to serve small and midsized customers and highly fragmented market like robotics. However, the indirect channel is also critical to support our more complex AI SoC targeting the edge infrastructure where a broad network of partners is vital for our long-term success. Meaningful revenue is expected in two to three years and will grow as we introduce new products for the market. Our second incremental go-to-market is our semi-custom opportunity, which can enable us to gain more share in existing market and reach into new markets.

我想強調，間接通路對於服務中小型客戶以及像機器人這類高度分散的市場非常重要。然而，間接通路同樣也是支援我們更複雜、鎖定邊緣基礎設施的 AI SoC 的關鍵；在這裡，廣泛的合作夥伴網路對我們的長期成功至關重要。我們預期在兩到三年內會出現具意義的營收，並將隨著我們為市場推出新產品而成長。我們第二項新增的市場進入策略是半客製化機會，這能讓我們在既有市場取得更多市占，並延伸至新市場。

We have our first semi-custom project underway, the 2-nanometer CV8 SoC, which is expected to generate first production revenue in fiscal 2028. And we are in discussion with other companies for additional semi-custom chip projects. Our representative customer engagement this quarter once again demonstrates Ambarella's expanding traction across a broad set of applications, robotics, automotive, security, trail cameras and smart video intercoms. With a CV72-based quadruped robot validates Ambarella's high resolution, high multi-camera edge AI capabilities in robotics. A major S&P 100 communication equipment company announced an AI-based enterprise video intercom, further extending our reach in the emerging access control market.

我們的第一個半客製化專案已在進行中，即 2 奈米 CV8 SoC，預期將於 2028 會計年度帶來首筆量產營收。我們也正與其他公司洽談更多半客製化晶片專案。本季具代表性的客戶互動再次展現 Ambarella 在廣泛應用上的牽引力持續擴大，包括機器人、車用、安全、狩獵相機（trail cameras）以及智慧影像對講機。一款基於 CV72 的四足機器人驗證了 Ambarella 在機器人領域的高解析度、多相機邊緣 AI 能力。一家主要的 S&P 100 通訊設備公司發布了基於 AI 的企業級影像對講機，進一步擴展我們在新興門禁控制市場的觸及範圍。

We landed another win with Moultrie for AI trail cameras and win with Canon, Suprema, IDS and Sepro further strengthen our AI monitoring pipeline with CV75, CV72, CV5 wins using our own AI ISP software. Through Tier 1s, we had two in-cabin vehicle wins with Tier 1s in China, one for driver monitors and one -- the other for more complex camera monitor system used in Audi and the VW vehicles. The breadth of these wins and the wide variety of corresponding AI workloads highlight the programmability and the flexibility in both our AI SoCs and our Cooper Developer Platform. This ease of use is facilitating the onboarding and expansion of our indirect sales channels. Very few competitors can offer this type of proven platform with more than 50 million edge AI SoCs shipped.

我們也取得 Moultrie 的 AI 狩獵相機（trail cameras）新案，並與 Canon、Suprema、IDS 與 Sepro 的勝出，透過採用我們自有的 AI ISP 軟體，帶來 CV75、CV72、CV5 的設計導入，進一步強化我們的 AI 監控案源管線。透過 Tier 1，我們在中國取得兩個車內（in-cabin）專案勝出：一個用於駕駛監控，另一個則是更複雜的相機監視系統（camera monitor system），應用於 Audi 與 VW 車款。這些勝出的廣度以及對應 AI 工作負載的多樣性，凸顯我們的 AI SoC 與 Cooper 開發者平台（Cooper Developer Platform）在可程式化與彈性方面的優勢。這種易用性正在促進我們間接銷售通路的導入與擴張。能提供這類經過驗證的平台、且已出貨超過 5,000 萬顆邊緣 AI SoC 的競爭對手非常少。

In conclusion, I remain very excited about the overall growth opportunity of the edge AI market and our company-specific growth drivers put us in a unique position to benefit. Ambarella is expanding beyond low-power AI SoC to deliver the complete foundation for Physical AI, and we are becoming a full stack Physical AI platform provider.

總結來說，我仍對邊緣 AI 市場的整體成長機會感到非常振奮，而我們公司特有的成長驅動因素，使我們處於能夠受益的獨特位置。Ambarella 正從低功耗 AI SoC 擴展，提供 Physical AI 的完整基礎，並且我們正成為全棧（full stack）的 Physical AI 平台供應商。

With that, I will now turn it to John.

接下來，我把時間交給 John。

Thank you, Fermi. I'll now review the financial highlights for the second quarter fiscal year 2027 ending July 31, 2026. I will also provide a financial outlook for our third quarter of fiscal year 2027 ending October 31, 2026. I'll be discussing non-GAAP results and ask that you refer to today's press release for a detailed reconciliation of GAAP to non-GAAP results. For non-GAAP reporting, we have eliminated stock-based compensation and acquisition-related expenses adjusted for the impact of taxes.

謝謝你，Fermi。我現在將回顧截至 2026 年 7 月 31 日止、2027 會計年度第二季的財務重點。我也將提供截至 2026 年 10 月 31 日止、2027 會計年度第三季的財務展望。我將討論非 GAAP 結果，並請各位參考今天的新聞稿，以取得 GAAP 與非 GAAP 結果之間的詳細調節表。就非 GAAP 報導而言，我們已剔除以股票為基礎的薪酬與併購相關費用，並就稅負影響進行調整。

In addition, this quarter, as described in our Q1 fiscal 2027 10-Q filing as a subsequent event, we recognized a $9 million reduction in our GAAP research and development expense due to the cancellation of a customer's development project. We do not expect any impact on our non-GAAP outlook from this development. For fiscal Q2, revenue was $108.1 million, slightly above the midpoint of our prior guidance range of $105 million to $111 million, up 7.7% from the prior quarter and up 13.2% year-over-year.

此外，本季如同我們 2027 會計年度第一季 10-Q 申報中作為期後事項（subsequent event）所述，由於一位客戶取消其開發專案，我們在 GAAP 研發費用中認列了 900 萬美元的減少。我們預期此一發展不會對我們的非 GAAP 展望造成任何影響。在 2027 會計年度第二季，營收為 1.081 億美元，略高於先前財測區間 1.05 億至 1.11 億美元的中點；較前一季成長 7.7%，較去年同期成長 13.2%。

Automotive revenue established a new revenue record on continued strength as the commercial vehicle adoption of AI remains strong, and Auto revenue slightly outpaced the growth in our IoT business, where our enterprise-driven businesses outperformed our consumer-led businesses.

汽車業務營收在商用車採用 AI 持續強勁的帶動下再創新高；同時，汽車營收的成長略高於我們 IoT 業務的成長，其中以企業驅動型業務的表現優於消費者導向型業務。

Non-GAAP gross margin for fiscal Q2 was 59.3%, below the midpoint of our prior guidance range of 59% to 60.5%. Non-GAAP operating expense in Q2 was $57.4 million, slightly below the midpoint of our prior guidance range of $56 million to $59. Q2 net interest and other income was $1.8 million. Q2 non-GAAP tax provision was approximately $344,000. We reported Q2 non-GAAP net profit of $8.2 million or $0.18 per diluted share.

2027 會計年度第二季的非 GAAP 毛利率為 59.3%，低於我們先前指引區間 59% 至 60.5% 的中點。第二季非 GAAP 營業費用為 5,740 萬美元，略低於我們先前指引區間 5,600 萬至 5,900 萬美元的中點。第二季淨利息及其他收入為 180 萬美元。第二季非 GAAP 所得稅提列約為 34.4 萬美元。我們第二季非 GAAP 淨利為 820 萬美元，或稀釋後每股 0.18 美元。

Now I'll turn to our balance sheet and cash flow. Fiscal Q2 cash and marketable securities were $272.3 million, decreasing $5.5 million from the prior quarter, but increasing $11.1 million from the same quarter a year ago. The sequential decrease in cash and marketable securities was primarily due to higher payments for IP licenses. Receivables days sales outstanding decreased from 35 to 32 days. While inventory dollars declined 4% sequentially, the days of inventory increased from 145 days to 157 days.

接下來我將說明我們的資產負債表與現金流。2027 會計年度第二季的現金及有價證券為 2.723 億美元，較前一季減少 550 萬美元，但較去年同期增加 1,110 萬美元。現金及有價證券的季減主要是因為 IP 授權費用支付增加。應收帳款週轉天數（DSO）由 35 天降至 32 天。雖然存貨金額較前一季下降 4%，但存貨天數由 145 天增加至 157 天。

Operating cash outflow was $260,000 for the quarter. Capital expenditures for tangible and intangible assets were $6.8 million for the quarter. Free cash outflow was $7.1 million for the quarter. During the second quarter of fiscal year 2027, we did not repurchase shares of our stock.

本季營運現金流出為 26 萬美元。本季有形與無形資產的資本支出為 680 萬美元。本季自由現金流出為 710 萬美元。在 2027 會計年度第二季期間，我們未回購公司股票。

During the second fiscal quarter, Ambarella's Board of Directors authorized a new $50 million repurchase program valid through June 30, 2027. The repurchase program does not obligate the company to acquire any particular amount of ordinary shares and it may be suspended at any time at the company's discretion. WT Microelectronics, a logistics partner in Taiwan that ships to multiple customers in Asia, was 60.2% of revenue for the second quarter. Hakuto, a logistics and distribution partner in Japan, was 11% of revenue in the quarter.

在第二個會計季度期間，Ambarella 董事會核准一項新的 5,000 萬美元回購計畫，有效期限至 2027 年 6 月 30 日。該回購計畫不要求公司必須買回任何特定數量的普通股，且公司可自行決定於任何時間暫停。台灣的物流合作夥伴 WT Microelectronics（為亞洲多家客戶出貨）在第二季占營收 60.2%。日本的物流與通路合作夥伴 Hakuto 在本季占營收 11%。

I'll now discuss the outlook for the third quarter of fiscal year 2027. We are anticipating favorable seasonality in our fiscal third quarter with revenue in the range of $115 million to $124 million or $119.5 million at the midpoint. At the midpoint, we expect our growth to be led by Physical AI demand from the IoT market. We expect fiscal Q3 non-GAAP gross margin to be in the range of 59% to 60%. We expect non-GAAP OpEx in the third quarter to be in the range of $56.5 million to $59.5 million. We estimate net interest and other income to be approximately $1.9 million, our non-GAAP tax expense to be approximately $700,000. And our diluted share count is expected to be approximately 44.9 million shares.

接下來我將說明 2027 會計年度第三季的展望。我們預期第三季將有有利的季節性因素，營收預估介於 1.15 億至 1.24 億美元之間，中點為 1.195 億美元。以中點來看，我們預期成長將由 IoT 市場的 Physical AI 需求所帶動。我們預期第三季非 GAAP 毛利率介於 59% 至 60%。我們預期第三季非 GAAP 營業費用（OpEx）介於 5,650 萬至 5,950 萬美元。我們估計淨利息及其他收入約為 190 萬美元，非 GAAP 所得稅費用約為 70 萬美元。我們預期稀釋後流通股數約為 4,490 萬股。

Thank you for joining our call today. And with that, I'll turn the call over to the operator for questions.

感謝各位今天參與我們的電話會議。接下來我將把電話交給接線員進行提問。

(Operator Instructions) Christopher Rolland, Susquehanna.

(接線員指示) Susquehanna 的 Christopher Rolland。

This is Dylan Ollivier on for Christopher Rolland. So it's nice to see your road map sort of expanding, and I know that you announced this X7 accelerator. I was hoping to hear a little bit more about this new chip. Is this a chip that you can bundle with your existing N1 portfolio? Or does this address a different part of the stack?

我是代替 Christopher Rolland 的 Dylan Ollivier。很高興看到你們的產品路線圖似乎正在擴展，我也知道你們宣布了這款 X7 加速器。我想多了解一些這顆新晶片。這是一顆可以與你們現有的 N1 產品組合一起搭配銷售的晶片嗎？還是它是針對堆疊中的不同層級？

So yes, Chris, for the X7, this is -- chip is an accelerator, which can be bundled with any host, including our own chip. So in fact, that some of our customers using a certain part number and when they feel they need to have more AI performance for certain workloads, the X7 give them a flexibility to upgrade the product without redesign the board. So this accelerator definitely is a way to design that. But in addition to supporting our own SoCs, but any other CPU like ARM or Intel chip, Intel CPUs that we can also bundle X7 with that as an AI accelerator.

是的，Chris，關於 X7，這顆晶片是一款加速器，可以與任何主機搭配，包括我們自家的晶片。事實上，我們有些客戶使用某個料號時，當他們覺得特定工作負載需要更高的 AI 效能，X7 讓他們能在不重新設計電路板的情況下，彈性升級產品。因此這個加速器確實就是為此而設計的方式。此外，除了支援我們自家的 SoC 之外，也可搭配其他 CPU，例如 ARM 或 Intel 晶片、Intel CPU，將 X7 作為 AI 加速器一起搭配。

Great. I appreciate this. And for my second question, I wanted to ask about sort of the Physical AI and humanoid opportunity. Is this responsible at all for this increase in SAM? Are there any new engagements or new designs that you can point us to?

很好。謝謝你的說明。第二個問題我想問的是 Physical AI 與人形機器人的機會。這是否是你們 SAM 增加的原因之一？是否有任何新的合作案或新設計可以分享？

Yes. So definitely, that's a big part of that. And last -- in the last earnings call, we talked about 15 design wins for the robots, including for roughly $100 million. Although we didn't give you another breakdown, but I can say that we add more design wins to that pipeline and a higher revenue target. So from that point of view, we continue to make progress. But in addition to robots, I also think that edge infrastructure and also enterprise security as well as portable video are all the reasons that we are increasing our SAM number.

是的。這絕對是其中很大的一部分。在上一次財報電話會議中，我們提到機器人方面有 15 個設計導入（design wins），合計約 1 億美元。雖然我們沒有再提供更細的拆分，但我可以說，我們在該管線中新增了更多設計導入，且目標營收也更高。因此從這個角度來看，我們持續取得進展。此外，除了機器人之外，我也認為邊緣基礎設施、企業安防以及可攜式影像，都是我們提高 SAM 數字的原因。

Yes, Dylan, we did -- Fermi mentioned a quadruped robotic dog with the CV72 chip this quarter. So continue to add on to the robotics wins we've described before.

是的，Dylan，Fermi 本季確實提到一款採用 CV72 晶片的四足機器狗。因此我們持續在先前描述的機器人設計導入上再添新案。

Joe Moore, Morgan Stanley.

Morgan Stanley 的 Joe Moore。

I wonder, first, in terms of the broader ecosystem, you talked about some of the challenges in memory. What is that meaning for your business? Do you think -- is there a risk of pull forwards or things like that because people are trying to get ahead of memory price increases? Is there pressure on you? Just what are you seeing from that memory impact from your customers?

我想先問，從更廣泛的生態系角度來看，你們提到記憶體方面的一些挑戰。這對你們的業務意味著什麼？你們認為——是否存在提前拉貨（pull forwards）之類的風險，因為大家想趕在記憶體價格上漲前先備貨？你們是否承受壓力？就客戶端的記憶體影響而言，你們觀察到什麼？

Right. So we continue to monitor this situation very closely, by talking to customers all the time. So for Q3, we are comfortable with our -- the guidance we provide today. In Q4, we continue to talk to customers to make sure our customer will have -- we can secure enough memory for a Q4 business. That's definitely the uncertainty that we are dealing with.

是的。我們持續透過與客戶保持密切溝通，來非常密切地監控這個情況。因此對於第三季，我們對今天提供的指引感到有把握。至於第四季，我們會持續與客戶溝通，以確保我們的客戶——我們能為第四季業務確保足夠的記憶體供應。這確實是我們正在面對的不確定性。

Okay. That's helpful. And then in terms of opening up to a broader ecosystem, distribution partners, things like that, I think you made the comment about -- that would take a couple of years to inflect. I guess I would sort of think that those customers would act a lot more quickly and would -- that pipeline could build a lot more quickly than what you had seen previously in automotive. Just what do you -- what was the comment that I maybe misunderstand there? And then what is the timeline to start to see traction from that kind of broader ecosystem?

好的。這很有幫助。接著談到擴展到更廣泛的生態系、通路夥伴等，我記得你們提到——這可能需要幾年才會出現拐點。我原本會認為這些客戶的行動會快得多，而且——相較於你們先前在汽車領域看到的情況，這條管線應該能更快建立。我是不是誤解了你剛才的說法？另外，從這類更廣泛生態系開始看到進展的時間表是什麼？

Right. So when I say two to three years, we talk about meaningful revenues. And I agree with you that we -- in fact, we already start seeing a small amount of design wins, which can generate revenue next year. But when we talk about meaningful revenue that will have an impact to our revenue forecast, I think that will take two to three years. In fact, when we talk to both CapGemini and Macnica, we kind of -- in fact, the range of revenue we are expecting from this collaboration is $0.5 billion with each one of them. So from that point of view, we're definitely looking forward to gradually ramp up the revenue for the next couple of years and start seeing meaningful revenue behind that.

沒錯。所以當我說兩到三年時，我們談的是具規模、具意義的營收。而且我同意你的看法：我們——事實上，我們已經開始看到少量的設計導入（design wins），這些可能在明年帶來營收。但當我們談到會對我們營收預測產生影響的具意義營收時，我認為那需要兩到三年。事實上，當我們與 CapGemini 和 Macnica 兩方洽談時，我們預期這項合作帶來的營收區間，大約是各自 5 億美元。因此，從這個角度來看，我們確實期待在未來幾年逐步拉升營收，並開始看到背後的具意義營收。

Tore Svanberg, Stifel.

Tore Svanberg，Stifel。

Congratulations on the Macnica and CapGemini partnerships. I'm curious on those for me. What are some of the early use cases that those two partners are going to be helping you with? Maybe you can call it some markets or applications. And how should I think about that in the context of your Cooper platform? Are they going to be working with you on Cooper? Are they going to be providing some of their own software? Just curious how that's going to play out?

恭喜與 Macnica 和 CapGemini 的合作夥伴關係。我對這兩個合作有些好奇。這兩家夥伴在早期會協助你們推動哪些使用案例？也許可以說是一些市場或應用。以及在你們的 Cooper 平台脈絡下，我應該如何理解？他們會和你們一起在 Cooper 上合作嗎？他們會提供一些自家的軟體嗎？只是好奇這會如何發展？

Right. So -- let me answer the second question first. Yes, both of them will use Cooper. In fact, that's a key driver for them to select to work with us because they see a very mature software platform they can immediately tackle on and start building around it, generating infrastructure for their own product line. So that our mature AI SoC as well as a mature Cooper software platform is the probably most critical engineering aspect that we offer to our partners.

好的。那——我先回答第二個問題。是的，他們兩家都會使用 Cooper。事實上，這是他們選擇與我們合作的一個關鍵驅動因素，因為他們看到一個非常成熟的軟體平台，可以立刻上手並開始在其上建構，為他們自己的產品線打造基礎架構並產生價值。因此，我們成熟的 AI SoC，以及成熟的 Cooper 軟體平台，可能是我們提供給合作夥伴最關鍵的工程面要素。

Go back to the potential market that we are talking about. In fact, there are multiple of them. And in fact, when I talk to Macnica, CEO in that meeting, they are highlighting that they have already started winning design wins with our solution on drones, on retail channels and also manufacturing. So that is definitely -- you can see that it's really a large market that. But -- however, most of the design win is small and segmented at beginning, but can ramp up to -- if they can ramp up to large volume of business, that will take time. But we already start seeing our partners start talking about different applications.

回到我們談到的潛在市場。事實上，有好幾個。而且，當我在那次會議與 Macnica 的 CEO 交流時，他們強調他們已經開始用我們的解決方案在無人機、零售通路以及製造業拿到設計導入（design wins）。所以這確實——你可以看到這是一個非常大的市場。不過——然而，多數設計導入在一開始都較小且較分散，但若要拉升到——若要拉升到大規模的業務量，需要時間。但我們已經開始看到合作夥伴在談論不同的應用。

Tore, it's Louis. They can work together as well. As Fermi said, Macnica can serve small to midsized markets that oftentimes are very fragmented. But really for CapGemini, it's large enterprise customers, and you can look at who they've talked about before. Those are the type of customers we'd really go after with them. So they're very complementary to each other.

Tore，我是 Louis。他們也可以彼此合作。如 Fermi 所說，Macnica 可以服務中小型市場，而這些市場往往非常分散。但對 CapGemini 而言，主要是大型企業客戶，你也可以看看他們過去提到過的客戶。那就是我們會和他們一起真正鎖定的客戶類型。所以他們彼此非常互補。

Very good. And as my follow-up, on the edge infrastructure market, this is obviously a completely new area. It sounds like that's the sort of biggest contributor to your increased SAM. I'm just curious, who's going to be some of your partners there? I mean, are these going to be your end customers sort of building their own infrastructure? Or is there going to be like an intermediary company that's building it? Is it going to be the traditional server guys? Yes, just curious how that's all going to play out?

很好。接著我的追問是，關於邊緣基礎設施市場，這顯然是一個全新的領域。聽起來這是你們 SAM 增加的最大貢獻來源。我只是好奇，你們在那裡會有哪些合作夥伴？我的意思是，會是你們的終端客戶自行建置他們自己的基礎設施嗎？還是會有像中介公司在建置？會是傳統的伺服器廠商嗎？是的，只是好奇整體會如何發展？

Well, I think, obviously, we're going to continue to talk to some of the large customers directly. But at the same time, we're counting on CapGemini and Macnica help us to penetrate this because they're already in that market, they're already selling solution to the existing edge AI customer with their existing solution. So working with them will help us to ramp up our revenue much faster than just were talking to direct customer directly.

嗯，我想很明顯地，我們會持續直接與一些大型客戶洽談。但同時，我們也仰賴 CapGemini 和 Macnica 協助我們滲透這個市場，因為他們已經在那個市場裡，也已經用他們現有的解決方案向既有的邊緣 AI 客戶銷售方案。因此，與他們合作將能幫助我們更快拉升營收，而不是只靠我們直接與客戶逐一洽談。

Quinn Bolton, Needham & Company.

Quinn Bolton，Needham & Company。

I just wanted to ask just longer term on the -- sorry, Macnica and CapGemini partnerships. Does that change the long-term gross margin target? I assume that there's probably some allocation of revenue that would be attributed to those partners. And so I'm wondering if that has any gross margin implications as that indirect channel ramps?

我想問一個比較長期的問題——抱歉，關於 Macnica 和 CapGemini 的合作夥伴關係。這會改變你們長期的毛利率目標嗎？我假設可能會有一部分營收需要分配給這些合作夥伴。所以我想知道，隨著這個間接通路放量，是否會對毛利率產生影響？

Right. So today, I think our long-term gross margin is still 59% to 62%. We are definitely trying to continue to watch because this is just -- we just start ramping up this business. If there's any change, we'll definitely inform our investors. But today, for us, after we talk to CapGemini and Macnica, we don't feel there's any need to change that target today.

好的。所以目前，我認為我們的長期毛利率仍是 59% 到 62%。我們當然會持續觀察，因為這只是——我們才剛開始把這項業務拉升。如果有任何變化，我們一定會通知投資人。但就目前而言，在與 CapGemini 和 Macnica 討論之後，我們不覺得現在有需要調整這個目標。

Got it. And then I guess just a clarification on the $9 million charge for the project that was canceled. Was that a semi-custom project that was canceled? And does that have any impact on your expected revenue timeline for the semi-custom business?

了解。另外我想釐清一下，關於那個被取消專案的 900 萬美元費用。那是一個被取消的半客製（semi-custom）專案嗎？而這是否會影響你們對半客製業務的預期營收時程？

Yes. Thanks, Quinn. It is not one of the semi-custom opportunities that we were -- that we've talked about. It was a development project with I guess, you could say, an automotive customer, auto autonomy customer. And we've been negotiating the termination of that for quite some time. And in Q2, we finalized the agreement.

是的。謝謝你，Quinn。那不是我們——我們曾談到的半客製機會之一。那是一個開發專案，對象我想可以說是某個汽車客戶、汽車自動駕駛（autonomy）客戶。我們就該專案的終止協議談判已經有一段時間了。而在第二季，我們完成了協議。

Kevin Cassidy, Rosenblatt Securities.

Kevin Cassidy，Rosenblatt Securities。

Going back to the shortage on the memory side and you've got near-term visibility. But I'm wondering on the designs, I know a lot of your customers or the market out there is probably dominated by a GPU-based embedded product that uses much more DRAM than yours would. Are you seeing any additional interest because you're more efficient with DRAM content?

回到記憶體端的短缺，以及你們對短期的可見度。但我想問的是，在設計方面，我知道你們很多客戶或市場上，可能主要是以 GPU 為基礎的嵌入式產品為主，而那種產品使用的 DRAM 比你們多得多。你們是否因為在 DRAM 用量上更有效率，而看到額外的興趣或需求？

Well, yes, first of all, the memory situation is dire for everybody, but some of our competitor who has more money to buy more memories. But however, any customer who come to us for the edge AI or Physical AI, they probably only use GPU for their first-generation product, and they understand. So the memory cost is just one reason, but more importantly, it is power efficiency and other reason. But the memory cost definitely is a driver for people start considering what's the more efficient way to do the product. So I agree with you that some of the -- most -- in fact, almost all the customers who come to talk to us is because our power efficiency solution and the lower cost solution than what they're using.

嗯，是的，首先，記憶體的情況對所有人都很嚴峻，但我們有些競爭對手資金更充裕，能買到更多記憶體。不過，任何來找我們做邊緣 AI 或 Physical AI 的客戶，他們很可能在第一代產品只用 GPU，他們也理解這點。所以記憶體成本只是其中一個原因，但更重要的是功耗效率以及其他因素。但記憶體成本確實是一個驅動因素，讓大家開始思考用更有效率的方式來做產品。所以我同意你的看法：有些——大多數——事實上，幾乎所有來跟我們洽談的客戶，都是因為我們的功耗效率解決方案，以及相較於他們目前使用方案更低的成本。

Okay. And maybe along the same lines with the AI accelerator, you'd be competing against a GPU that uses a lot of memory also. What is the memory architecture inside your X7?

好的。而且可能同樣地，就 AI 加速器而言，你們也會與使用大量記憶體的 GPU 競爭。你們的 X7 內部的記憶體架構是什麼？

Well, in fact, that we need a much smaller footprint. For example, we only need 4 megabytes memory for the accelerator running large language model. So just give -- show you the -- and more importantly, the accelerator, the power envelope you have to fit in is anywhere between 4 to 5 watts in the current design win. So all of the power efficiency, memory size and also cost is really helping us to penetrate this market right now.

嗯，事實上，我們需要的占用空間要小得多。例如，我們的加速器在跑大型語言模型時只需要 4MB 記憶體。所以就給你——讓我說明一下——更重要的是，在目前拿下的設計導入案中，加速器必須符合的功耗範圍大約是 4 到 5 瓦。因此，功耗效率、記憶體容量以及成本，確實都在幫助我們目前打入這個市場。

Suji Desilva, ROTH Capital.

Suji Desilva，ROTH Capital。

just a clarification for me on the X7 chip. Is that competing really only with edge GPUs? Or is it other AI specialty chips? Or how should we think about the competitive landscape for this new offering?

我想釐清一下關於 X7 晶片。它主要只是在跟邊緣端 GPU 競爭嗎？還是也包括其他 AI 專用晶片？或者我們應該如何看待這個新產品的競爭態勢？

Right now, well, in addition to NVIDIA and Qualcomm having similar products in this market space, there are probably 50 start-up companies doing similar chips. So it's a crowded space. But however, at the end, it's really about the power efficiency because I just talked about to run a certain workload, you have to have a mature -- not only a power-efficient solution, but mature hardware and software, which I think we are one of the very few that can do that today.

目前來看，除了 NVIDIA 和 Qualcomm 在這個市場領域也有類似產品之外，可能還有大約 50 家新創公司在做類似的晶片。所以這是一個很擁擠的市場。但最終，關鍵其實在於功耗效率。因為我剛才提到，要跑某個特定工作負載，你不只需要高功耗效率的解決方案，還需要成熟的硬體與軟體；我認為我們是目前少數能做到這點的公司之一。

Okay. That's helpful for me. And then my other question is you're talking about customization now projects. I'm just wondering what's precipitated the demand from the customers or your push to provide customization? What's newer versus your standard product history now that's driving the need for that or your desire to do that?

好的。這對我很有幫助。那我另一個問題是，你們現在在談客製化專案。我想了解，是什麼促使客戶端出現這樣的需求，或是你們推動提供客製化的原因？相較於你們過去的標準產品歷史，現在有哪些新的因素在驅動這個需求，或驅動你們想做這件事？

I think you're talking about the optimization for the memory situation. Is that correct?

我想你是在說針對記憶體情況的最佳化。是這樣嗎？

Well, I think --

嗯，我想--

Semi-custom.

半客製。

Oh, semi-custom.

喔，半客製。

Semi-custom, I apologize. Yes.

半客製，不好意思。是的。

So -- yes. For semi-custom customers, in fact, we basically allow our customers give us a spec and we build on the spec. But however, when we negotiate spec with a customer, we need to make sure that we can sell the spec to somebody else. So we -- for the semi-custom chip, we pretty much build a purpose chip for the one customer, which they benefit from this. But at the same time, we can sell the chip to others that are not competing with the key customer. That's the business model and how it works on the engineering side.

所以——是的。對於半客製客戶，基本上我們允許客戶提供規格，我們依照該規格來開發。不過，當我們與客戶協商規格時，我們需要確保這個規格也能賣給其他客戶。因此，對於半客製晶片，我們幾乎是為單一客戶打造一顆特定用途的晶片，客戶能從中受益。但同時，我們也可以把這顆晶片賣給那些不會與該關鍵客戶競爭的其他客戶。這就是商業模式，以及在工程端如何運作。

But of course -- Suji, it's Louis. We'll try to offer as much of our own IP in those semi-custom chips as possible. For example, we have our own IP for the AI accelerator, the NPU for all the perception capabilities, including ISP, and the encoder, the CPUs, all of those functional blocks are available for a customer to develop a semi-custom or custom chip with.

當然——Suji，我是 Louis。我們會盡可能在這些半客製晶片中提供更多我們自有的 IP。例如，我們有自家的 AI 加速器 IP、用於各種感知能力的 NPU（包括 ISP）、以及編碼器、CPU 等等；所有這些功能模組都可供客戶用來開發半客製或客製晶片。

Liam Pharr, BofA.

Liam Pharr，BofA。

Is there a way to frame how much memory cost inflation you're absorbing this quarter, either in basis points or maybe what gross margin would have been without any memory cost inflation? And is the path back above 60% feasible while memory prices stay elevated? Or does that require pricing to come down?

有沒有辦法量化你們本季吸收了多少記憶體成本上漲的影響，例如用基點表示，或是如果沒有任何記憶體成本上漲，毛利率本來會是多少？另外，在記憶體價格仍維持高檔的情況下，回到 60% 以上的路徑是否可行？還是需要記憶體價格下來才行？

Right. So first of all, the memory price doesn't impact our gross margin. It really only have a potential to impact how many chips our customers can buy. So memory cost because we don't buy memory, and we don't resell memory. So the memory price has no impact to our gross margin.

好的。首先，記憶體價格不會影響我們的毛利率。它真正可能影響的是我們的客戶能買多少晶片。因為記憶體成本——我們不採購記憶體，也不轉售記憶體。所以記憶體價格對我們的毛利率沒有影響。

So that -- I think I hope that answers your question. But the real question for us is how that memory cost can -- because our customers need to increase the price, whether that will reduce the total volume they can sell and therefore, reduce the total ordering to us, that's something we need to continue to observe. In Q2 and Q3, we see a little impact on our revenue because of memory situation. We continue to watch for the Q4.

所以——我希望這回答了你的問題。但對我們而言真正的問題是，記憶體成本可能會——因為我們的客戶需要提高售價——這是否會降低他們能賣出的總量，進而減少他們對我們的總下單量；這是我們需要持續觀察的。在第二季和第三季，我們看到記憶體狀況對營收有一些影響。我們會持續觀察第四季。

And then I guess for my follow-up, Q3 is guided up 10.5% roughly sequential versus 13.5% last year. How much of this next quarter is normal seasonality versus underlying end demand strength? And given you flagged Q4 memory supply, obviously changing the demand picture, how should we think about Q4 seasonality and whether the full year 10% to 15% is still reasonable for the full -- for the guide?

那我追問一下，第三季指引大約季增 10.5%，相較去年是 13.5%。下季的成長有多少是正常季節性因素，有多少是終端需求的基本面強勁？另外，既然你們提到第四季記憶體供應會改變需求面貌，我們應該如何看待第四季的季節性，以及全年 10% 到 15% 的指引是否仍合理？

Right. So I think the outcome this year is still a little uncertain because of the memory constraint that you talk about. And like I said, we continue to talk to our customer for that to monitor how that impacts our performance in Q4. Barring for any memory impact to our revenue, I think that you should expect Q4 was a regular seasonality.

好的。我認為今年的結果仍有一些不確定性，因為你提到的記憶體限制。如我所說，我們會持續與客戶溝通，以監控這對我們第四季表現的影響。若不考慮任何記憶體對營收的影響，我認為你應該預期第四季會是正常的季節性表現。

Gus Richard, Northland.

Gus Richard，Northland。

Robotics architecture look an awful lot like an autonomous car in terms of what it needs to do. And I'm just wondering, you have a domain controller for autos and you have the CV products. Are you seeing any traction in the domain controllers? And -- and then any clarification on where you're seeing the strength? Is some of this coming out of China?

機器人的架構在需要完成的事情上，看起來非常像自動駕駛車。我想請教，你們在車用有域控制器，也有 CV 產品。你們在域控制器方面有看到任何進展嗎？另外也想釐清一下你們看到的強勁動能在哪裡？其中有一部分是來自中國嗎？

Right. First of all, you're 100% right that a lot of robot design system architecture looks just like autonomous driving car, which I totally agree. And however, I think the robotic market situation really reminds me autonomous driving seven years ago when that at that time, all of our automotive customers in trying to just using individual modules and put the solution together and start demoing and selling the first-generation product. I think this is how we are at with the current robots. We see a lot of customers are rushing out their first-generation product by putting individual components together to demo their capabilities.

好的。首先，你說得完全正確，很多機器人的設計系統架構看起來就像自動駕駛車，我完全同意。不過，我認為機器人市場的狀況讓我想起七年前的自動駕駛：當時我們的車用客戶都在嘗試只用各個獨立模組把解決方案拼起來，開始展示並銷售第一代產品。我認為目前機器人就是處在這個階段。我們看到很多客戶正急著把第一代產品推出來，透過把各個獨立元件組合起來展示其能力。

However, we do believe that integration path of the robotic will be very similar to what happened to the autonomous driving car. It is there will be people going to buy perception system, but down the road, people want to buy domain controller. We do see both opportunity today, but I would say majority of our customers today is asking for perception modules, perception solution. But on their road map, they want to have a way that can buy a domain controller in the long run. So I think we have a complete road map.

不過，我們確實相信機器人的整合路徑會非常類似自動駕駛車所走過的路。也就是說，會有人去買感知系統，但長期來看，人們會想買域控制器。我們今天兩者都看到機會，但我會說目前大多數客戶是在詢問感知模組、感知解決方案。但在他們的產品藍圖上，長期來看他們希望能有一種方式可以購買域控制器。所以我認為我們有完整的產品藍圖。

We can sell just perception system to a customer today. In fact, people want to buy brain -- domain controller like for the brain of the robots, we have the solution, too. But our plan is we're going to continue to develop solution for both so that we can cover the total space of robotics.

我們今天就可以把純感知系統賣給客戶。事實上，人們想買的是「大腦」——就像機器人大腦的領域控制器，我們也有解決方案。但我們的計畫是會持續同時開發這兩種解決方案，讓我們能涵蓋機器人領域的整體市場空間。

Got it. And then just if I think about, again, robots, cars are 2D and robots are 3D. And I'm just wondering, is one of the limitations of penetration training and can you help your customers train robots. Thinking about humanoid, but -- go ahead, sorry.

了解。然後如果我再想一下，機器人和汽車——汽車是 2D，而機器人是 3D。我只是想知道，滲透率的限制之一是否在於訓練，以及你們能否幫助客戶訓練機器人。我在想人形機器人，不過——你先說，抱歉。

Right. So in terms of training, it's really about how to collect data. One thing we help our customers is we build a platform for people to collect data easily. And also we provide a platform that can provide a service to help people to label those data automatically. So people can use our system to -- reference design to collect data.

對。所以就訓練而言，關鍵其實在於如何蒐集資料。我們幫助客戶的一件事是，我們建立了一個平台，讓大家能更容易蒐集資料。另外我們也提供一個平台，可提供服務來協助大家自動標註那些資料。因此人們可以使用我們的系統——參考設計——來蒐集資料。

In fact, some of the, I would say, the people doing mapping, generating the 3D mapping are using our system to collect data. And also, we are providing service to some of our automotive customers that we can -- using our tools to auto labeling all of the data they generate. Those are two things we can help to provide assistance on the training side.

事實上，有些我會說是在做建圖、生成 3D 地圖的人，正在使用我們的系統來蒐集資料。此外，我們也為部分車用客戶提供服務，我們可以——使用我們的工具——把他們產生的所有資料進行自動標註。這兩點就是我們在訓練端能提供協助的地方。

Martin Yang, Opp & Co.

Martin Yang，Opp & Co.。

Fermi, you sized the potential revenue from CapGemini and Macnica pretty similarly, but they face different variety of customers. Can you maybe talk about the methodology you arrived at those dollar figures? Is a similar methodology or a very different approach to size those potential markets?

Fermi，你對 CapGemini 和 Macnica 的潛在營收規模估得相當接近，但他們面對的客戶類型不同。你能否談談你是用什麼方法得出那些金額數字的？是採用相似的方法論，還是用非常不同的方式來估算那些潛在市場？

Yes. Go ahead.

是的。請說。

This is Muneyb just jumping in there. I think both Fermi and Louis were commenting earlier about how complementary they were, right? So I think, one, on the Macnica side, I think Louis has commented, it is large-scale, medium, large kind of customers we haven't addressed in the past. So think of them as a large volume play where we've typically directly engaged with high-volume customers. These will start aggregating a whole bunch of small, midsized customers that we did not have access to in the past. So it's a volume play, and I think Fermi already indicated that we're starting to see some small design wins come through with these distribution.

我是 Muneyb，我插一句。我想 Fermi 和 Louis 先前都提到它們是如何互補的，對吧？所以第一，在 Macnica 這邊，我想 Louis 已經提到，這是我們過去未曾觸及的中大型、以及大型客戶。所以可以把他們視為一個大規模的量體策略（volume play），而我們過去通常是直接與高出貨量客戶接觸。他們會開始彙聚一大批我們過去無法接觸到的小型與中型客戶。所以這是一個量體策略，而我想 Fermi 也已指出，我們開始看到透過這些通路帶來一些小型設計導入（design wins）。

And then if you think about CapGemini, it's more of a value play. And I think Louis indicated before, these are large enterprises and customers who will bring complex solutions, deploy at scale to enterprises. So the modeling is on both slightly different. One, distribution channels, reseller scaling with small design wins, so building up small volume. The other ones are large customers and logos, which have much larger opportunity deals, but complex opportunities. So on both sides, the modeling is done on value versus volume. And I think the earlier question was also, you should see different timelines on this.

再來如果你看 CapGemini，則更偏向價值策略（value play）。而我想 Louis 之前也提到，這些是大型企業與客戶，會帶來複雜的解決方案，並在企業端大規模部署。因此兩者的建模方式略有不同。一個是通路、經銷商，透過小型設計導入來擴張，逐步累積小量。另一個是大型客戶與品牌（logos），單筆機會更大，但屬於複雜的機會案。所以兩邊的建模是以價值對比量體來進行。而我想先前的問題也提到，你應該會看到兩者在時程上有所不同。

So we do expect faster timelines on the distribution side and more longer timelines on the more larger complex opportunities. But the modeling has been built out over seven years of how this will come to fruition. And of course, they are -- some of them new to our products. So initial ramp-up, market making, pilot opportunities is what we are allowing for. But we will keep you updated as we start winning some large deals and meaningful revenue, as Fermi pointed out, in future quarters.

因此我們確實預期通路端的時程會更快，而較大型、較複雜的機會案時程會更長。不過這個模型是以七年的時間跨度來建立，來看它將如何逐步實現。當然，其中有些對我們的產品而言是新的。所以我們也把初期爬坡、開拓市場、以及試點（pilot）機會納入考量。但隨著我們在未來幾季開始拿下大型案子並帶來具意義的營收（如 Fermi 所指出），我們會持續向各位更新。

Great. I have a follow-up on X7. Is that accelerator chip primarily targeted for as a channel product? Or there's no distinction between for channel or for direct?

很好。我有一個關於 X7 的追問。那顆加速器晶片主要是作為通路產品來鎖定嗎？還是通路與直銷之間沒有區別？

There's no distinguish. And in fact, that I'm expecting that both CapGemini and Macnica will do product rapid design for that and targeting different customers.

沒有區別。而且事實上，我預期 CapGemini 和 Macnica 都會針對它做產品快速設計，並鎖定不同的客戶。

This does conclude the question-and-answer session of today's program. I'd like to hand the program back to Dr. Fermi Wang for any further remarks.

以上為今日議程的問答環節結束。我想把議程交回給 Fermi Wang 博士，請他做進一步的結語。

And thank all of you for joining our call today, and I hope to see you and talk to you next time.

也感謝各位今天參與我們的電話會議，希望下次再見並再與各位交流。

Thank you, ladies and gentlemen, for your participation in today's conference. This does conclude the program. You may now disconnect. Good day.

感謝各位女士、先生參與今天的會議。本次議程到此結束。您現在可以掛線。祝各位有美好的一天。