Revolutionizing Multifunction Devices: Harnessing Edge AI for Real-Time Language Translation

Imagine a world where language barriers cease to exist. A world where communication flows effortlessly, regardless of the languages spoken. Thanks to the advancements in edge artificial intelligence (AI), this vision is becoming a reality. In this article, we will explore the exciting realm of edge AI for real-time language translation in multifunction devices, and how it is revolutionizing the way we communicate and collaborate.

Language has long been a barrier to global connectivity, hindering business interactions, travel experiences, and cultural exchanges. However, with the advent of edge AI, language translation is no longer confined to dedicated translation apps or human interpreters. Multifunction devices, such as smartphones, tablets, and smart speakers, are now equipped with powerful AI algorithms that can instantly translate spoken or written words from one language to another in real-time. This breakthrough technology is eliminating the need for external translation services and enabling seamless communication between individuals who speak different languages.

Key Takeaway 1: Edge AI enables real-time language translation in multifunction devices

Edge AI, a technology that brings artificial intelligence capabilities to the edge of the network, has revolutionized real-time language translation in multifunction devices. By processing data directly on the device, without relying on cloud computing, Edge AI enables fast and accurate language translation, making multifunction devices more versatile and user-friendly.

Key Takeaway 2: Improved efficiency and privacy with Edge AI

With Edge AI, language translation happens locally on the device, eliminating the need to send data to the cloud for processing. This not only improves efficiency by reducing latency but also enhances privacy by keeping sensitive information within the device. Users can now confidently translate documents or have conversations without worrying about data breaches or slow response times.

Key Takeaway 3: Enhanced user experience and productivity

Edge AI-powered language translation in multifunction devices offers an enhanced user experience and increased productivity. Users can now translate documents, emails, or web pages instantly, without the need for external translation tools or services. This feature is particularly beneficial for businesses operating in multilingual environments, enabling seamless communication and collaboration across language barriers.

Key Takeaway 4: Versatility for various industries and use cases

The integration of Edge AI in multifunction devices opens up a wide range of applications across industries. From healthcare and hospitality to education and travel, real-time language translation can significantly improve communication and accessibility. Multifunction devices equipped with Edge AI can now serve as language assistants, facilitating interactions between individuals who speak different languages.

Key Takeaway 5: Future prospects and advancements

The use of Edge AI for real-time language translation in multifunction devices is still evolving, with ongoing research and development. As technology continues to advance, we can expect even more accurate and efficient translation capabilities. Additionally, the integration of natural language processing and machine learning algorithms into multifunction devices holds the potential for more intelligent and context-aware language translation in the future.

Controversial Aspect 1: Accuracy and Reliability

One of the most controversial aspects of Edge AI for real-time language translation in multifunction devices is the accuracy and reliability of the translations produced. While this technology has undoubtedly made significant advancements in recent years, it is not without its flaws.

Some critics argue that the translations generated by Edge AI may not always be as accurate as those produced by human translators. They claim that the nuances and complexities of language can be challenging for AI algorithms to capture accurately, leading to mistranslations or misinterpretations. This is particularly true for languages with intricate grammar rules or idiomatic expressions.

On the other hand, proponents of Edge AI argue that the technology has come a long way and can now provide translations that are close to human-level accuracy. They point to the advancements in natural language processing and machine learning algorithms, which have improved the quality of translations over time. They also highlight the convenience and speed that Edge AI offers, making it a valuable tool for communication in real-time scenarios.

It is essential to consider both perspectives when evaluating the accuracy and reliability of Edge AI for language translation. While it may not be perfect, the technology has made significant strides and can be a useful tool for quick and straightforward translations. However, for more complex or critical translations, human expertise may still be necessary to ensure accuracy.

Controversial Aspect 2: Privacy and Data Security

Another controversial aspect of Edge AI for real-time language translation is the concern over privacy and data security. Multifunction devices equipped with Edge AI technology often rely on cloud-based services to process and analyze the data. This raises concerns about the storage and handling of sensitive information.

Critics argue that the use of cloud services for language translation poses a risk to user privacy. They worry that personal conversations or confidential information could be intercepted or accessed by unauthorized individuals. Additionally, there are concerns about the potential misuse of data by the companies providing the translation services, such as selling user data to third parties for targeted advertising or other purposes.

Proponents of Edge AI acknowledge these concerns but argue that measures can be taken to mitigate the risks. They advocate for strong encryption protocols and secure data storage practices to protect user privacy. They also emphasize the importance of transparency and user consent when it comes to data collection and usage.

Ultimately, the debate around privacy and data security in Edge AI for language translation comes down to finding a balance between convenience and protection. While there are legitimate concerns, advancements in encryption and security protocols can help address these issues and ensure user data is handled responsibly.

Controversial Aspect 3: Impact on Human Translators

The rise of Edge AI for real-time language translation has raised concerns about its potential impact on human translators. As this technology becomes more advanced and widely adopted, some fear that it could replace human translators altogether, leading to job losses and a devaluation of the profession.

Critics argue that relying solely on AI for translation undermines the human element of language and the cultural nuances that human translators bring to their work. They believe that AI cannot fully capture the intricacies and subtleties of language, particularly when it comes to translating literary or creative works.

On the other hand, proponents of Edge AI argue that it is not meant to replace human translators but rather to complement their work. They believe that AI can handle routine and repetitive translation tasks, freeing up human translators to focus on more complex and creative aspects of their work. They also point out that Edge AI can be a valuable tool for non-professional translators, enabling them to communicate effectively in foreign languages.

It is crucial to strike a balance between the use of Edge AI and the role of human translators. While AI can provide quick and efficient translations, human expertise is still necessary for more nuanced and context-dependent translations. The integration of Edge AI into the translation workflow can enhance productivity and accessibility, but it should not replace the invaluable skills and cultural understanding that human translators bring.

1. The Rise of Edge AI in Multifunction Devices

Edge AI, or artificial intelligence at the edge, is revolutionizing the capabilities of multifunction devices. Traditionally, language translation required sending data to the cloud for processing, resulting in latency and privacy concerns. However, with the advent of edge AI, language translation can now be performed directly on the device itself, enabling real-time translations without the need for an internet connection.

Edge AI leverages the power of machine learning algorithms and neural networks to process and analyze data locally on the device. This eliminates the need for round-trip communication with the cloud, reducing latency and ensuring faster response times. Multifunction devices equipped with edge AI can now provide seamless language translation capabilities, making them invaluable tools for international businesses, travelers, and language learners.

2. How Edge AI Enables Real-Time Language Translation

Edge AI enables real-time language translation in multifunction devices by leveraging deep learning models specifically trained for language processing tasks. These models are pre-loaded onto the device, allowing it to process and translate text or speech in real-time.

For text translation, edge AI algorithms analyze the input text, identify the language, and generate an accurate translation. This can be particularly useful for translating documents, emails, or web pages on the fly.

For speech translation, edge AI algorithms convert spoken words into text, analyze the text, and generate a translation. This allows users to have real-time conversations with individuals who speak different languages, without the need for an interpreter or an internet connection.

3. Benefits of Edge AI for Language Translation

The adoption of edge AI for language translation in multifunction devices brings several benefits:

Real-time translation:Edge AI enables instant translations, eliminating the need for delays associated with cloud-based processing.

Privacy:With edge AI, all language translation processing happens locally on the device, ensuring that sensitive information remains secure and private.

Offline capabilities:Edge AI allows language translation to be performed even without an internet connection, making it ideal for travelers or areas with limited connectivity.

Improved user experience:Real-time language translation on multifunction devices enhances user experience by providing seamless communication across language barriers.

4. Case Studies: Edge AI in Multifunction Devices

Several companies have already embraced edge AI for language translation in multifunction devices, showcasing the technology’s potential:

Company X:Company X integrated edge AI into their multifunction printers, allowing users to scan and translate documents in real-time. This feature has significantly improved productivity for international teams and facilitated communication with global partners.

Company Y:Company Y developed a portable language translation device equipped with edge AI. Users can speak into the device, and it instantly translates their speech into the desired language. This has been a game-changer for travelers, enabling them to communicate effortlessly in foreign countries.

5. Overcoming Challenges in Edge AI Language Translation

While edge AI for language translation offers immense potential, there are some challenges to overcome:

Accuracy:Achieving high accuracy in language translation is crucial. Edge AI models need to be trained on diverse datasets to handle different languages, dialects, and contexts.

Resource limitations:Multifunction devices have limited processing power and memory. Optimizing edge AI algorithms to run efficiently on these devices is essential.

Continuous learning:Language translation models need to be regularly updated to incorporate new vocabulary, idioms, and evolving language patterns.

6. The Future of Edge AI in Multifunction Devices

The future of edge AI in multifunction devices looks promising. As technology advances, we can expect even more sophisticated language translation capabilities:

Improved accuracy:Ongoing research in natural language processing and machine learning will lead to more accurate translations, reducing errors and improving user experience.

Expanded language support:Edge AI models will continue to evolve, offering support for a wider range of languages, dialects, and regional variations.

Integration with other applications:Edge AI language translation capabilities will likely be integrated with other applications, such as voice assistants, making multifunction devices even more versatile.

Enhanced user interfaces:User interfaces on multifunction devices will become more intuitive, allowing users to easily access and utilize language translation features.

The Emergence of Real-Time Language Translation

Real-time language translation has always been a coveted technology, as it has the potential to break down barriers and facilitate communication between people from different linguistic backgrounds. The earliest attempts at language translation can be traced back to the mid-20th century when researchers began exploring machine translation using computers.

Initially, these early translation systems relied on rule-based approaches, where linguistic rules and dictionaries were programmed into the computer to translate text from one language to another. However, these systems had limited success due to the complexity and nuances of human language, leading to inaccurate translations.

The Rise of Artificial Intelligence

The advent of artificial intelligence (AI) in the 1950s and 1960s brought a new wave of optimism for real-time language translation. Researchers started exploring the use of AI techniques, such as natural language processing and machine learning, to improve translation accuracy.

Machine learning algorithms, particularly neural networks, gained popularity in the 1980s and 1990s for their ability to learn patterns and improve translation quality over time. However, these early AI-based translation systems were computationally expensive and required powerful hardware to run.

The Evolution of Edge Computing

As computing technology advanced, the concept of edge computing emerged in the late 1990s. Edge computing refers to the practice of processing data closer to the source or the “edge” of the network, rather than relying on a centralized cloud infrastructure. This approach reduces latency and allows for faster processing of data.

In the context of language translation, edge computing became a game-changer. Instead of relying on remote servers for processing, edge AI enabled the deployment of translation algorithms directly on the devices themselves, such as smartphones, tablets, and multifunction devices.

Edge AI for Real-Time Language Translation

With the rise of edge AI, real-time language translation in multifunction devices became a reality. These devices, equipped with powerful processors and AI capabilities, can now perform language translation on the spot, without the need for an internet connection or external servers.

Edge AI for real-time language translation offers several advantages. Firstly, it eliminates the need for constant internet connectivity, making it ideal for situations where internet access is limited or unreliable. Secondly, it ensures data privacy and security, as sensitive information does not need to be transmitted to external servers for processing.

Furthermore, edge AI enables faster translation speeds, as the processing is done locally on the device. This is particularly beneficial in scenarios where immediate translation is required, such as during business meetings, conferences, or travel.

The Current State of Edge AI for Real-Time Language Translation

Today, edge AI for real-time language translation has reached a remarkable level of accuracy and usability. Advanced neural network models, such as transformer models, have significantly improved translation quality, capturing the nuances and context of different languages.

Moreover, the availability of powerful hardware, such as dedicated AI chips, has further enhanced the performance of edge AI translation devices. These devices can now handle complex translation tasks in real-time, providing a seamless and natural translation experience.

Furthermore, edge AI translation devices have become more accessible and affordable, with many consumer electronics manufacturers integrating translation capabilities into their products. This has made real-time language translation a mainstream feature, empowering individuals and businesses to communicate effortlessly across language barriers.

The evolution of edge AI for real-time language translation in multifunction devices has transformed the way we communicate. From early attempts at machine translation to the emergence of AI and edge computing, this technology has come a long way. With its current state of accuracy, speed, and accessibility, edge AI for real-time language translation has the potential to bridge linguistic gaps and foster global communication like never before.

Case Study 1: Google Pixel Buds

One of the most prominent examples of edge AI for real-time language translation in multifunction devices is the Google Pixel Buds. These wireless earbuds, developed by Google, incorporate advanced AI algorithms that enable seamless translation between languages in real-time.

The Pixel Buds leverage Google’s powerful machine learning capabilities to process and translate spoken words on the device itself, without the need for an internet connection. This edge AI approach ensures privacy and eliminates the latency associated with cloud-based translation services.

Users simply need to activate the translation feature on their Pixel Buds and speak in their native language. The earbuds pick up the audio, process it using AI algorithms, and provide instant translation in the desired language directly into the user’s ears. This allows for smooth and natural conversations between individuals who speak different languages.

The success of the Google Pixel Buds lies in their ability to deliver accurate and real-time translations, making them an invaluable tool for travelers, international business professionals, and anyone seeking to overcome language barriers.

Case Study 2: Microsoft Translator App

Another compelling case study in the realm of edge AI for real-time language translation is the Microsoft Translator App. This mobile application harnesses the power of edge computing to provide on-the-go language translation without the need for an internet connection.

The Microsoft Translator App utilizes a combination of deep learning and neural network models to deliver high-quality translations in real-time. By leveraging edge AI, the app can perform complex language processing tasks directly on the user’s device, ensuring fast and reliable translations even in areas with limited or no internet connectivity.

One of the key features of the Microsoft Translator App is its ability to translate speech in real-time. Users can speak into their device’s microphone, and the app will instantly convert their words into the desired language, both in written form and through audio playback. This allows for seamless communication between individuals who don’t share a common language.

The success of the Microsoft Translator App lies in its versatility and ease of use. It has been widely adopted by travelers, international organizations, and individuals working in multicultural environments, enabling them to communicate effectively and break down language barriers.

Case Study 3: iFlytek Translator

The iFlytek Translator is a prime example of how edge AI can revolutionize real-time language translation in multifunction devices. Developed by iFlytek, a leading Chinese AI company, this handheld translator device combines cutting-edge AI technologies with a user-friendly interface to deliver accurate and instant translations.

The iFlytek Translator is equipped with a powerful AI chip that enables it to perform complex language processing tasks on the device itself. This eliminates the need for an internet connection and ensures that translations are delivered in real-time without any delays or privacy concerns.

Users can simply speak into the device, and it will instantly translate their words into the desired language. The iFlytek Translator supports a wide range of languages, making it a valuable tool for international travelers, business professionals, and individuals seeking to communicate across language barriers.

What sets the iFlytek Translator apart is its ability to accurately capture and translate spoken language, even in noisy environments. The device utilizes advanced noise-canceling algorithms and AI-based speech recognition technology to ensure that translations are clear and accurate, regardless of the surrounding noise levels.

The iFlytek Translator has gained significant popularity in China and is increasingly being adopted by international users. Its success lies in its ability to deliver real-time translations with high accuracy and its user-friendly design, making it an indispensable tool for global communication.

In recent years, the field of artificial intelligence (AI) has made significant advancements, particularly in the area of natural language processing. This has paved the way for the development of real-time language translation systems that can be integrated into multifunction devices, such as smartphones and tablets. One of the key technologies driving these systems is edge AI, which allows for on-device processing and analysis without the need for constant internet connectivity. In this article, we will explore the technical aspects of edge AI for real-time language translation in multifunction devices.

Edge AI and its Benefits

Edge AI refers to the deployment of AI algorithms and models directly on the edge devices, rather than relying on cloud-based processing. This approach offers several advantages for real-time language translation in multifunction devices:

  • Low Latency: By performing the translation on the device itself, edge AI eliminates the need for data to be sent to remote servers and processed there. This significantly reduces the latency, allowing for near-instantaneous translation results.
  • Privacy and Security: With edge AI, sensitive data, such as conversations or documents, can remain on the device without being transmitted over the internet. This provides an additional layer of privacy and security, as the data is not exposed to potential breaches or unauthorized access.
  • Offline Capabilities: Edge AI enables language translation even in situations where internet connectivity is limited or unavailable. This is particularly useful for travelers or individuals in remote locations who may not have access to a stable internet connection.

Neural Machine Translation (NMT) Models

Neural Machine Translation (NMT) models form the backbone of real-time language translation systems. These models are trained using large amounts of bilingual text data and are capable of learning the complex patterns and semantics of different languages. NMT models consist of an encoder-decoder architecture, where the encoder processes the source language and generates a hidden representation, which is then decoded to produce the translated output in the target language.

Edge AI allows for the deployment of NMT models directly on the multifunction devices, enabling real-time translation without relying on cloud-based servers. This requires the models to be optimized for efficient execution on limited computational resources, such as those found in smartphones or tablets. Techniques like model compression, quantization, and pruning are employed to reduce the model size and computational requirements while maintaining translation accuracy.

Speech Recognition and Natural Language Understanding

In addition to NMT models, real-time language translation systems often incorporate speech recognition and natural language understanding (NLU) components. These components enable the translation of spoken language and enhance the overall user experience.

Speech recognition converts spoken words into text, which can then be processed by the NMT model for translation. Edge AI allows for on-device speech recognition, eliminating the need for audio data to be sent to cloud-based servers for processing. This reduces latency and ensures privacy, as the audio data remains on the device.

Natural language understanding is responsible for analyzing the context and intent of the input text, allowing for more accurate and context-aware translations. Edge AI enables the deployment of NLU models directly on the multifunction devices, enhancing the translation quality and user experience without relying on cloud-based processing.

Continuous Learning and Adaptation

To ensure the accuracy and relevance of real-time language translation, continuous learning and adaptation are crucial. Edge AI facilitates this by allowing the models to be updated and improved directly on the multifunction devices.

One approach to continuous learning is federated learning, where updates to the models are performed locally on the devices and then aggregated to improve the global model. This distributed learning approach ensures privacy and reduces the need for data to be sent to central servers for training.

Furthermore, edge AI enables the collection of user feedback and preferences, which can be used to personalize the translation experience. This feedback can be incorporated into the models to adapt to individual user needs and improve translation accuracy over time.

Edge AI has revolutionized real-time language translation in multifunction devices by enabling on-device processing, low latency, privacy, and offline capabilities. Through the deployment of NMT models, speech recognition, natural language understanding, and continuous learning techniques, these systems provide users with seamless and accurate translation experiences. As edge AI continues to advance, we can expect even more sophisticated language translation capabilities in the future.

FAQs

1. What is Edge AI?

Edge AI refers to the deployment of artificial intelligence algorithms and models on edge devices such as smartphones, tablets, or multifunction devices, enabling them to perform AI-related tasks locally without relying on cloud-based processing.

2. How does Edge AI work in real-time language translation?

In real-time language translation, Edge AI utilizes machine learning algorithms to process and analyze language data directly on the multifunction device. These algorithms are trained to recognize and translate different languages, allowing the device to provide instant translations without the need for an internet connection or cloud-based translation services.

3. What are the benefits of using Edge AI for real-time language translation?

Using Edge AI for real-time language translation offers several advantages, including:

  • Fast and immediate translations without internet dependency
  • Enhanced privacy and data security as translations are performed locally
  • Reduced latency and improved user experience
  • Cost savings by eliminating the need for cloud-based translation services

4. Can Edge AI translations match the accuracy of cloud-based translation services?

While cloud-based translation services may have access to vast amounts of data and computing power, Edge AI translations have made significant advancements in accuracy. With the help of machine learning algorithms and neural networks, Edge AI can achieve high levels of translation accuracy, especially for common phrases and sentences.

5. What languages are supported by Edge AI for real-time translation?

The languages supported by Edge AI for real-time translation depend on the specific language models and algorithms implemented on the multifunction device. However, popular languages such as English, Spanish, French, German, Chinese, Japanese, and many others are commonly supported.

6. Can Edge AI translations be customized for specific industries or domains?

Yes, Edge AI translations can be customized for specific industries or domains. By training the language models with specialized data related to a particular industry or domain, the accuracy and relevance of translations can be improved for specific use cases. For example, medical terminology can be incorporated into the language model for accurate translations in healthcare settings.

7. Are there any limitations to using Edge AI for real-time language translation?

While Edge AI offers numerous benefits, there are a few limitations to consider:

  • Limited processing power and memory on edge devices may restrict the complexity and accuracy of translations compared to cloud-based services.
  • Edge AI translations may struggle with translating rare or less commonly spoken languages due to limited training data.
  • Updates and improvements to language models may require firmware or software updates on the multifunction devices.

8. Can Edge AI translations be combined with cloud-based services for improved accuracy?

Yes, it is possible to combine Edge AI translations with cloud-based services for improved accuracy. This hybrid approach allows the device to perform initial translations locally using Edge AI, and then send the translated text to a cloud-based service for further refinement or to handle complex translation requests. This combination can provide the benefits of both local processing and access to extensive cloud resources.

9. Are there any privacy concerns with Edge AI language translation?

Edge AI language translation addresses privacy concerns by performing translations locally on the device, eliminating the need to send sensitive data to cloud servers. This ensures that user conversations or confidential information remains secure and private. However, it is essential to review the privacy policy of the device manufacturer to understand how data is handled and stored.

10. How can businesses benefit from Edge AI for real-time language translation in multifunction devices?

Businesses can benefit from Edge AI for real-time language translation in multifunction devices in several ways:

  • Improved communication with international clients or customers
  • Enhanced productivity by eliminating language barriers in meetings or conferences
  • Cost savings by reducing the need for external translation services
  • Increased customer satisfaction through personalized translations for specific industries or domains

1. Stay Updated with the Latest Edge AI Technology

Edge AI technology is constantly evolving, so it’s essential to stay updated with the latest advancements. Follow reputable tech websites, subscribe to newsletters, and join online communities to keep yourself informed about the latest developments in Edge AI for real-time language translation.

2. Choose the Right Multifunction Device

When selecting a multifunction device for real-time language translation, consider factors such as processing power, memory, and compatibility with AI frameworks. Look for devices that specifically mention support for Edge AI and language translation to ensure optimal performance.

3. Optimize Network Connectivity

Edge AI relies on network connectivity to access cloud-based language translation models. Ensure that your device has a stable and fast internet connection to minimize latency and provide a seamless translation experience.

4. Prioritize Privacy and Security

Real-time language translation often involves transmitting sensitive information. Ensure that the multifunction device you choose prioritizes privacy and security. Look for features like end-to-end encryption and data anonymization to protect your personal data.

5. Customize Language Translation Settings

Most multifunction devices with Edge AI capabilities allow users to customize language translation settings. Take advantage of this feature to personalize your translation experience. Adjust parameters like language preferences, translation accuracy, and even specific vocabulary to enhance the accuracy of translations.

6. Practice Pronunciation and Intonation

While Edge AI technology can provide accurate translations, it’s still important to practice pronunciation and intonation when speaking in a foreign language. This will help the device better understand your speech and improve the overall translation quality.

7. Explore Additional Language Learning Resources

Using Edge AI for real-time language translation can be a great tool for language learning. Supplement your translation experience by exploring additional language learning resources such as language learning apps, online courses, or language exchange platforms.

8. Collaborate with Native Speakers

If you have access to native speakers of the language you’re learning, collaborate with them while using your multifunction device. This will not only help you practice speaking but also provide an opportunity to receive feedback on your translations and improve your language skills.

9. Experiment with Different Scenarios

Edge AI for real-time language translation can be useful in various scenarios. Experiment with different situations where translation is required, such as traveling, business meetings, or social interactions. This will help you become familiar with the device’s capabilities and adapt to different contexts.

10. Provide Feedback to Device Manufacturers

If you encounter any issues or have suggestions for improvement while using Edge AI for real-time language translation, provide feedback to the device manufacturers. Your input can help them enhance their products and provide a better user experience for everyone.

Conclusion

The integration of Edge AI for real-time language translation in multifunction devices has the potential to revolutionize communication and enhance productivity in various settings. By leveraging the power of artificial intelligence and machine learning algorithms, these devices can now accurately translate spoken or written language in real-time, eliminating the need for external translation services or language barriers.

One key advantage of Edge AI is its ability to process data locally on the device, reducing the dependency on cloud-based services and ensuring faster response times. This is particularly important for real-time language translation, where delays can hinder effective communication. Additionally, the use of Edge AI enables data privacy and security, as sensitive information is not transmitted over the internet.

Furthermore, the implementation of Edge AI for language translation in multifunction devices opens up new possibilities for businesses and individuals alike. It allows for seamless communication in international collaborations, improves customer service in multilingual environments, and facilitates travel and tourism by breaking down language barriers. The convenience and efficiency offered by these devices make them a valuable tool in today’s globalized world.

As technology continues to advance, we can expect further improvements in the accuracy and capabilities of Edge AI for real-time language translation. With ongoing research and development, these devices have the potential to become even more sophisticated, providing seamless and natural language translation experiences. The future of communication is indeed promising, thanks to the integration of Edge AI in multifunction devices.