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It is a set of tools to help developers run TensorFlow models on mobile, embedded, and IoT devices. It enables on-device machine learning inference with low latency and a small binary size.
256
aziende
Abbiamo dati su 256 aziende che usano Tensorflow Lite. La nostra lista di clienti Tensorflow Lite è disponibile per il download ed è arricchita con specifiche vitali dell'azienda, incluse classificazione industriale, dimensioni organizzative, posizione geografica, round di finanziamenti e cifre di ricavi, tra gli altri.
Azienda | Paese | Settore | Dipendenti | Entrate |
---|---|---|---|---|
Affectiva | Stati Uniti | Embedded Software Products | 57 | $5M |
PhotoRoom | Francia | It Services And It Consulting | 94 | $2M |
Arm | Regno Unito | Semiconductor Manufacturing | 8.9K | |
Cadence Design Systems | Stati Uniti | Software Development | 9.7K | $3.4B |
Brainly | Polonia | Software Development | 820 | $14M |
NXP Semiconductors | Paesi Bassi | Semiconductor Manufacturing | 22K | |
![]() Plain Concepts | Spagna | It Services And It Consulting | 439 | $286K |
![]() Roku | Stati Uniti | Software Development | 3.8K | |
SiDi | Brasile | Retail | 870 | |
Super GeoAI Technology Inc. | Stati Uniti | It Services And It Consulting | 2 | |
Osmo | Stati Uniti | Software Development | 69 | $2.3M |
Silicon Austria Labs | Austria | Research Services | 260 | $37M |
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Tensorflow Lite è utilizzata in 30 paesi
Ci sono 76 alternative a Tensorflow Lite
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Tensorflow Lite is a technology developed by Google for machine learning applications, particularly optimized for mobile and edge devices. It is a lightweight version of the popular Tensorflow framework, designed to run machine learning models on mobile and IoT devices with lower computational resources. Tensorflow Lite enables developers to deploy machine learning models on edge devices, allowing for faster and more efficient inferencing without relying on cloud services.
Tensorflow Lite falls under the category of Machine Learning Tools, offering a specialized solution for deploying machine learning models on resource-constrained devices. It provides a framework for developers to implement efficient machine learning algorithms on a wide range of devices, from smartphones to embedded systems. By utilizing Tensorflow Lite, developers can harness the power of machine learning directly on edge devices, enabling real-time inference and processing of data without the need for continuous network connectivity.
The history of Tensorflow Lite dates back to 2017 when Google introduced the technology as an extension of the original Tensorflow framework. The motivation behind developing Tensorflow Lite was to address the growing demand for running machine learning models on mobile and edge devices efficiently. By optimizing the computational performance and memory footprint, Google aimed to make machine learning more accessible and practical for a broader range of applications. Since its inception, Tensorflow Lite has evolved to become a leading solution for deploying machine learning models on edge devices.
In terms of current market share, Tensorflow Lite has gained significant traction within the Machine Learning Tools category. Its efficient performance on resource-constrained devices has made it a preferred choice for developers looking to implement machine learning models on edge devices. With the increasing adoption of edge computing and IoT applications, the market share of Tensorflow Lite is expected to grow further in the future as more industries leverage the power of machine learning at the edge.
Tensorflow Lite is a popular choice among companies in the Machine Learning Tools category due to its efficiency and versatility in deploying machine learning models on mobile and edge devices. Its lightweight nature makes it ideal for applications where resources are limited, allowing companies to leverage the power of machine learning on devices with lower processing capabilities.
Tensorflow Lite is optimized for mobile and edge devices, providing faster inference times and lower latency compared to traditional machine learning frameworks. This ensures smooth and responsive user experiences, making it ideal for real-time applications like image and speech recognition.
One of the key advantages of Tensorflow Lite is its low memory footprint and computational requirements. This allows companies to deploy complex machine learning models on resource-constrained devices without compromising performance, making it a cost-effective solution for edge computing scenarios.
Tensorflow Lite seamlessly integrates with existing Tensorflow models, enabling companies to easily convert and deploy their models for mobile and edge applications. Its compatibility with popular programming languages and platforms simplifies the development process, making it a preferred choice for developers looking to scale their machine learning projects efficiently.
Tensorflow Lite is a popular machine learning tool used by various companies to deploy machine learning models on mobile and edge devices. Some well-known companies that leverage Tensorflow Lite in their operations include Google, Pinterest, and Alibaba. Below are case studies showcasing how these companies utilize Tensorflow Lite to enhance their products and services:
Google: Google uses Tensorflow Lite to optimize and deploy machine learning models on mobile devices. By leveraging Tensorflow Lite's lightweight and efficient architecture, Google has been able to integrate advanced machine learning capabilities into its mobile applications, such as voice recognition and image classification. Google started using Tensorflow Lite in 2017 and continues to expand its usage across various product lines.
Pinterest: Pinterest utilizes Tensorflow Lite to improve its visual search capabilities within the Pinterest app. With Tensorflow Lite's high-performance inference engine, Pinterest can quickly analyze and match images uploaded by users to relevant visual content on the platform. This enhances the overall user experience by providing more accurate and relevant search results. Pinterest integrated Tensorflow Lite into its app in 2018, leading to a significant improvement in search accuracy and speed.
Alibaba: Alibaba incorporates Tensorflow Lite into its e-commerce platform to enhance product recommendations and personalized shopping experiences for users. By leveraging Tensorflow Lite's real-time inference capabilities, Alibaba can analyze user behavior data and deliver tailored product suggestions in milliseconds. This has significantly increased user engagement and conversion rates on the platform. Alibaba adopted Tensorflow Lite in 2019, contributing to a more personalized and efficient shopping journey for its customers.
These case studies demonstrate the diverse applications of Tensorflow Lite across different industry sectors, showcasing how companies leverage this powerful machine learning tool to drive innovation and improve customer experiences.
Puoi accedere a un elenco aggiornato di aziende che utilizzano Tensorflow Lite visitando TheirStack.com. La nostra piattaforma fornisce un database completo di aziende che utilizzano varie tecnologie e strumenti interni.
Fino ad ora, abbiamo dati su 256 aziende che utilizzano Tensorflow Lite.
Tensorflow Lite è utilizzato da una vasta gamma di organizzazioni in vari settori, inclusi "Embedded Software Products", "It Services And It Consulting", "Semiconductor Manufacturing", "Software Development", "Software Development", "Semiconductor Manufacturing", "It Services And It Consulting", "Software Development", "Retail", "It Services And It Consulting". Per un elenco completo di tutti i settori che utilizzano Tensorflow Lite, si prega di visitare TheirStack.com.
Alcune delle aziende che utilizzano Tensorflow Lite includono Affectiva, PhotoRoom, Arm, Cadence Design Systems, Brainly, NXP Semiconductors, Plain Concepts, Roku, SiDi, Super GeoAI Technology Inc. e molte altre. Puoi trovare un elenco completo di 256 aziende che utilizzano Tensorflow Lite su TheirStack.com.
Secondo i nostri dati, Tensorflow Lite è più popolare in Stati Uniti (81 companies), Regno Unito (20 companies), Francia (16 companies), India (12 companies), Germania (9 companies), Spagna (9 companies), Giappone (5 companies), Svizzera (4 companies), Australia (3 companies), Brasile (3 companies). Tuttavia, è utilizzato da aziende in tutto il mondo.
Puoi trovare aziende che utilizzano Tensorflow Lite cercandolo su TheirStack.com. Tracciamo le offerte di lavoro di milioni di aziende e le utilizziamo per scoprire quali tecnologie e strumenti interni stanno utilizzando.