ModelNova Revolutionizes AI Application Development for Small Devices
ModelNova Revolutionizes AI Application Development for Small Devices
SILICON VALLEY, Calif. , June 24, 2024 /PRNewswire/ -- From the TinyML Summit in Milan Italy, embedUR systems Inc., a leader in embedded systems and Edge AI, and a TinyML sponsor partner, is thrilled to announce the launch of ModelNova, a groundbreaking software hub catering for Edge AI solutions.
來自意大利米蘭TinyML峯會的嵌入式系統和邊緣人工智能領導者、TinyML贊助夥伴embedUR systems Inc感到非常高興地宣佈推出ModelNova，一款爲邊緣人工智能解決方案而設計的創新軟件平台。
ModelNova is a model zoo for pre-trained AI models, optimized for different software frameworks and a variety of low-power hardware platforms with and without native AI acceleration. This innovative platform streamlines Edge AI product development, enabling rapid prototyping and deployment of intelligent applications on edge devices, in a fraction of the time it used to take to develop Edge AI solutions from scratch.
ModelNova是一個模型動物園，針對不同的軟件框架和各種低功耗硬件平台優化的預訓練人工智能模型。這一創新平台簡化了邊緣人工智能產品的開發，從而在邊緣設備上快速構建智能應用程序原型並部署，時間縮短到了從零開始開發邊緣人工智能解決方案所需時間的一小部分。
ModelNova addresses a significant challenge faced by developers: the complexity of selecting, creating, training, porting, and optimizing AI models for different hardware platforms, especially low-power IoT devices.
ModelNova解決了開發人員面臨的一個重要問題：選擇、創建、訓練、移植和優化針對不同硬件平台的人工智能模型的複雜性，特別是低功耗物聯網設備。
This is a critical process, upon-which the success of a project largely depends. It requires extensive expertise in low-level firmware, plus a deep understanding of the silicon they are trying to optimize for, which is a rare skill set.
這是一個關鍵的過程，對項目的成功有很大的影響。它需要豐富的低級固件知識和對他們試圖進行優化的硅的深入了解，這是一種罕見的技能集。
ModelNova bridges this gap by offering a diverse collection of pre-trained models for AI Vision, Speech, Sound and more, which have already been fine-tuned to run on multiple combinations of hardware and software architectures.
ModelNova通過提供多樣化的針對AI Vision、Speech、Sound等的預訓練模型，這些模型已經針對多種硬件和軟件架構進行了調整，彌合了這一差距。
Most AI models begin as academic research and open source implementations trained with a particular dataset not ready for real end product development. Leveraging our unique expertise in AI and embedded software device integration to maximize performance and minimize power usage, we have adapted the models for use in real-world applications.
大多數人工智能模型都始於學術研究和開源實現，並針對特定數據集進行訓練，而不是準備用於實際的最終產品開發。利用我們在人工智能和嵌入式軟件設備集成方面的獨特專業知識，最大程度地提高了性能，並將模型調整爲可用於實際應用。
"Our platform removes the barriers to entry for AI prototyping and development on low-powered devices, enabling engineers to focus on innovation rather than the intricacies of hardware integration and optimization", says John Marconi, VP Technology at embedUR
embedUR的技術副總裁John Marconi表示：“我們的平台消除了低功耗設備上人工智能原型設計和開發的入門障礙，使工程師能夠專注於創新而不是硬件集成和優化的複雜性。”
Developers will be able to download models known to run on hardware similar to what they have in mind to use, and quickly evaluate the feasibility of their application. This dramatically reduces the time required to build proof of concepts and validate the hardware for Edge AI applications, allowing developers to move from idea to proof of concept in days not months.
開發人員將能夠下載已知在他們考慮使用的硬件上運行的模型，並快速評估其應用的可行性；這大大減少了構建概念驗證所需的時間，並驗證邊緣人工智能應用程序的硬件，使開發人員能夠在幾天而非數月的時間內從想法到驗證概念。
"With its focus on models for resource-constrained devices, ModelNova can accelerate the developer journey for IoT Edge AI, and showcases what can be enabled on Synaptics' Astra AI-Native devices", said Vikram Gupta, Senior Vice President and General Manager of IoT Processors, Chief Product Officer, Synaptics
Synaptics的IoT處理器高級副總裁兼首席產品官Vikram Gupta表示：“鑑於ModelNova專注於資源受限設備的模型，可以加速IoT Edge AI的開發者旅程，並展示了在Synaptics的Astra AI-Native設備上所能實現的功能。”
Key Benefits of ModelNova:
ModelNova的關鍵優勢：
Rapid Prototyping: Developers can download pre-trained models for functions similar to those needed by their application and see how well they run on different platforms of choice.
快速原型製作：開發人員可以下載類似於其應用所需功能的預訓練模型，並查看其在不同的平台上運行得有多好。
Streamlined Development: Developers only need to adapt or retrain existing models to perform new functions, which is a lot less work than creating the model, in the first place.
簡化開發：開發人員只需要調整或重新訓練現有模型以執行新功能，這比從頭開始創建模型要容易得多。
Access to Edge AI Expertise: As integrators of these models to the different platforms they run on, embedUR is available to assist with model optimization, training for application use-cases, and integration to target hardware to accelerate productization.
訪問邊緣人工智能專業知識：作爲將這些模型整合到不同平台上的集成商，embedUR可以協助進行模型優化、應用用例培訓和與目標硬件的集成，以加速產品化。
"This is an exciting resource for the developer community, unlocking new possibilities for developing edge AI solutions at a much faster pace," said Pete Bernard, Executive Director of the TinyML Foundation.
TinyML基金會的執行董事Pete Bernard表示：“這是開發者社區的一個激動人心的資源，能夠以更快的速度開發邊緣人工智能解決方案，開啓新的市場機遇。”
Silicon vendors and platform creators who are building new AI-native hardware are encouraged to reach out to embedUR to have ModelNova's library of models ported to and optimized on their new devices.
鼓勵正在構建新的人工智能原生硬件的硅供應商和平台創建者聯繫embedUR，以將ModelNova的模型庫移植和優化到他們的新設備上。
ModelNova enables businesses in all sectors from healthcare to agriculture to explore new market opportunities with minimal upfront investment and risk.
ModelNova可使各個領域的企業，從醫療保健到農業，以最小的前期投資和風險探索新的市場機會。
Join ModelNova.ai today, and start validating your Edge AI designs in days instead of months.
加入ModelNova.ai，不必花費數月時間即可開始驗證您的邊緣人工智能設計。
About embedUR systems Inc.:
關於embedUR systems公司：
Headquartered in Fremont, California, embedUR systems is a leader in embedded systems and wireless technologies, specializing in Wi-Fi, IoT, and TinyML. We are enabling the Intelligent Edge one device at a time. We help businesses develop Edge AI solutions and get to market fast.
總部位於加利福尼亞州弗裏蒙特市的embedUR systems公司是嵌入式系統和無線技術領域的領導者，專業從事Wi-Fi、物聯網和TinyML等技術。我們正在逐個設備地實現智能邊緣。我們幫助企業開發邊緣人工智能解決方案，並快速進入市場。
By launching ModelNova, embedUR is set to revolutionize the way AI applications are developed and deployed on low-powered devices, empowering engineers to innovate faster and more efficiently than ever before.
通過推出ModelNova，embedUR將徹底改變低功耗設備上開發和部署人工智能應用的方式，使工程師比以往更快、更高效地進行創新。
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譯文內容由第三人軟體翻譯。