領先同行瑞薩OSC晶振專用于人工智能，瑞薩文藝復興我們的長期發展戰略是如何將公司定位為一家全方位的全球技術解決方案提供商，致力于為用戶提供高品質的SPXO晶振產品，瑞薩公司在美國、歐洲和中國都有廣泛的業務。由于收購了Intersil、IDT、Dialog Semiconductor和Celeno，我們現在擁有了豐富的設計能力市場領先的嵌入式處理器專業知識擁有四項核心模擬和混合信號能力:傳感器和傳感器信號調理, 連通性，驅動和動力管理.

在每一種情況下，這些公司及其工程師和科學家都為我們的關鍵增長目標做出了重大貢獻，2019年至2021年期間，總收入的CAGR增長了17.7%，同期營業利潤率增長了16.9%。也許最能說明問題的事實是，在2020年至2022年期間，我們的基礎設施和工業業務分別增長了33%和37%，而我們的物聯網(IoT)部門在CAGR的增長驚人地達到了79%(有機增長37%)。

工業物聯網(IIoT)市場以如此迅猛的速度擴張并不令人驚訝。對于renesas瑞薩晶振來說，它標志著一個機會，通過實現幾乎同時成熟的三個關鍵技術領域的融合，加速我們的客戶和生態系統合作伙伴的采用:物聯網、5G連接和人工智能(AI)。我們稱之為人工智能物聯網，或AIoT，這一趨勢正在推動我們收集、存儲、處理、分發、保護和增強數據的方式發生轉變，以便將其轉化為我們可以學習的可操作情報。

這種巨大的變化需要從集中式的基于云的架構轉向分布式的基于邊緣的設計，而這些產品之中隨處都需要應用高品質的有源晶振產品，同時，這種設計使用微處理器和微處理器等微小的機器學習(ML)節點來定義端點，加速數學模型并提高深度神經網絡的性能。

雖然許多人可能會將人工智能與機器人助手等未來的消費應用聯系起來，但事實是，當物聯網端點節點創建以85%的CAGR (2017-2025)爆炸式增長時，工業領域將感受到很大一部分初步影響，根據IDC的數據，產生了幾乎令人難以置信的73 zetabytes的數據。從應用的角度來看，這些增長線將在預測性維護、快速缺陷檢測、生物識別和資產跟蹤等領域開辟新的市場和收入渠道。

這就是我們2022年最新、最重要的收購之一——Reality AI的原因。該公司在開發工業領域的算法方面尤其強大，這有助于實現我們的長期愿景，即將高級信號處理和數學建模與人工智能相結合，以構建我們可以在嵌入式處理器上實現的機器學習模型——從16位到64位。

Reality AI收購是實現我們AIoT愿景的重要組成部分，今年還包括對Syntiant和Arduino等公司的投資，這些公司正在將我們的觸角延伸到更復雜的用例，以及與Tiny ML財團的白金贊助。領先同行瑞薩OSC晶振專用于人工智能.

In each case, these companies and their engineers and scientists are contributing significantly to our key growth objectives, with overall revenue increasing at a CAGR of 17.7% between 2019 and 2021 and operating margin growing 16.9% over the same period. Perhaps most telling is the fact that, between 2020 and 2022, our infrastructure and industrial businesses grew by 33% and 37%, respectively, while our internet of things (IoT) segment saw an astounding 79% jump (37% organically) in CAGR.

That the industrial IoT (IIoT) marketplace is expanding at such a torrid pace is not surprising. For Renesas it signals an opportunity to accelerate adoption among our customers and ecosystem partners by enabling the convergence of three key technology areas that are maturing at roughly the same time: IoT, 5G connectivity and artificial intelligence (AI). We call this AI IoT, or AIoT, and the trend is driving a shift in how we collect, store, process, distribute, secure and power data in order to turn it into actionable intelligence we can learn from.

Such a sea change entails a move away from centralized, cloud-based architectures to distributed, edge-based designs that use tiny machine learning (ML) nodes like MCUs and MPUs to define the endpoint, accelerate mathematical models and improve the performance of deep neural networks.

While many people might associate AI with futuristic consumer applications like robotic assistants, the fact is that much of the initial impact will be felt in the industrial space where when IoT endpoint node creation is exploding at an 85% CAGR (2017-2025), yielding an almost unfathomable 73 zetabytes of data, according to IDC. From an applications perspective, these growth lines will open new markets and revenue channels in areas such as predictive maintenance, rapid defect detection, biometric recognition and asset tracking to name just a few.

That’s what led us to one of our most recent and significant 2022 acquisitions – Reality AI. The company is especially strong in developing algorithms for the industrial space, which is helping to fulfill our long-term vision of combining advanced signal processing and mathematical modeling with AI to build machine learning models that we can implement on our embedded processors – from 16 to 64 bits.

The Reality AI acquisition is an important component of realizing our AIoT vision, which this year also included investments in companies like Syntiant and Arduino that are extending our reach into more complex use cases, as well as a platinum sponsorship with the Tiny ML Consortium.

For Renesas, those strategic investments are part of a long-term, three-pronged approach to enabling AIoT, which includes access to world-class MCU and MPU devices and a commitment to the broader AIoT ecosystem, where we have more than 200 technology partners. Together with 5G and other forms of wireless connectivity, such as WiFi 6/6E/7 and near-field communications (NFC), we are enabling a fully distributed AIoT network that will revolutionize how the industrial workplace is managed by bringing constant, on-device learning and decision making to the factory floor.