Tag: AI

Advertisement

Telehealth Firm Amwell to Adopt Google AI, Translation Tech

Technology

Promising advances to the telehealth services industry, Amwell will integrate Google Cloud AI capabilities for natural language processing and medical transcription services, among other new services.

Since the onset of the pandemic, telehealth services have skyrocketed. A Department of Health and Human Services statistical report found that in April, about 43% of primary care visits through Medicare were via telehealth. Before the pandemic, more than 99% of Medicare-funded visits were in-person appointments. From March through early July, the agency says, more than 10 million Medicare beneficiaries used telehealth services. With broad telehealth coverage more vital than ever, though, demands for language services have risen considerably as well.

Seeing the opportunity for growth, Google recently pledged to invest $100 million into Amwell, formerly known as American Well, a company that builds technology for virtual doctors’ visits. Launching in 2006, Amwell currently works with 55 health plans, which support over 36,000 employers and represent more than 80 million covered individuals, as well as 150 of the nation’s largest health systems. It has powered more than 5.6 million telehealth visits for its clients, including over 3 million since the shutdown began.

The partnership will leverage Google’s artificial intelligence (AI) and machine learning (ML) technologies to create a comprehensive virtual care experience for patients and providers that goes beyond visits and includes services like self-triage or remote patient monitoring (RPM) capabilities. Google plans to work closely with Amwell to integrate its AI capabilities into Amwell’s virtual care platform, particularly in natural language processing and medical transcription services. This could have interesting implications for the language service industry, particularly the life sciences sector.

Additionally, Amwell will move parts of its business from Amazon Web Services to Google Cloud, recognizing Google Cloud as its “preferred global cloud partner.” Specifically, Amwell will move some video performance capabilities to Google Cloud. The two companies will also collaborate on technology and work to expand Amwell’s footprint in the sector.

“With this partnership, Google Cloud and Amwell see an opportunity to improve patient and clinician telehealth experiences through technologies that can automate waiting room and checkout; provide automated language translation services; advance population health by making it easier for more patients to receive care; and assist payers and providers in routine tasks, by intelligently triaging cases and reducing clinician burnout,” mentioned a Google Cloud blog post.

The post went on to describe how machine translation is being integrated into the system: “A conversational chatbot agent is immediately available to assist you, in your preferred language, by asking about your symptoms and the reason for your visit, and provides this information to your physician before she enters your virtual exam room. During your appointment, you continue to speak in your preferred language to your physician, while cloud-based artificial intelligence (AI) provides live, translated captioning of the conversation.”

Tags:, , , , ,
Journalist at MultiLingual Magazine | + posts

Jonathan Pyner is a poet, freelance writer, and translator. He has worked as an educator for nearly a decade in the US and Taiwan, and he recently completed a master’s of fine arts in creative writing.

Advertisement

Related News:

Advertisement
SDL Tados 2021

Venga Global Launches AI Program to Meet Data, ML Needs

Localization Technology

Leveraging human-assisted multilingual data collection, Venga AI will power natural language processing AI and machine learning.

Global leader in translation and localization Venga Global announced this week the launch of Venga AI to meet growing data transformation and machine learning needs. Expanding data annotation, collection, and validation for artificial intelligence (AI) and machine learning (ML) services, the company looks to improve localization approaches, especially for languages other than English.

“We started offering data services in 2016 focused around natural language processing and data translation,” says Venga chief sales and marketing officer Antoine Rey. “We have learned, adapted, and developed technology with great success to bring quality clean data to top AI and data companies. We are excited to now publicly offer our expanded roster of services including data annotation and validation for text, image, video, and audio.”

Working in translation, localization, and creative services in over 150 languages, Venga partners with clients to “streamline global communication.” With expertise in natural language processing (NLP), the company builds custom programs for enterprise clients to provide human-assisted clean data collection, annotation, and validation for ML. These programs are supported by a production team, innovative tools and technology, a specialized supply chain, and an ISO-certified quality assurance team.

The announcement of the AI program notes the growing need for clean data to feed into machine learning algorithms, especially in sectors producing medical diagnostics, autonomous vehicles, and voice search. With roots already in the translation industry, Venga has pivoted to providing data services in recent years, leveraging local human networks to create accurate data sets.

Venga chief operating officer Chris Phillips credited the company’s “ability to ramp up from zero to thousands of trained resources in very short time periods” as “key to our success. We achieve this through stringent vetting, testing, and training of quality resources and optimize our technology stack project by project to create efficient and controlled NLP data collection.”

Venga Global earned recognition last year by the National LGBT Chamber of Commerce (NGLCC) Supplier Diversity Initiative, gaining certification as an LGBT Business Enterprise (LGBTBE).

Tags:, , ,
+ posts

MultiLingual creates go-to news and resources for language industry professionals.

Advertisement

Related News:

GlobalLink AI Portal Delivers Over 1 Billion Words Per Month

AI

Surpassing one billion words per month, TransPerfect’s GlobalLink AI Portal solution has doubled in usage this year, as TransPerfect signs on several new clients.

TransPerfect, one of the world’s largest providers of language and technology solutions for global business, announced this week that the adoption of its GlobalLink AI Portal machine translation (MT) solution for corporate clients has surpassed the one billion words per month milestone and continues to grow.

With the addition of new clients like Cushman & Wakefield, HARMAN International, and Cummins, GlobalLink AI Portal usage has more than doubled this year. Serving over 5,000 global organizations, GlobalLink Product Suite simplifies management of multilingual content. TransPerfect has seen long-term clients who use the service achieve an increase of 15% in quality scores over the previous year, demonstrating the AI solution’s capacity to continuously improve in a secure environment. The increased quality allows clients to reduce the scope and scale of necessary post-edits by streamlining time and cost.

Among TransPerfect’s numerous language and technology solutions, GlobalLink AI Portal focuses on real-time self-service MT and supports more than 40 different languages and 30 different file formats. The solution makes neural MT more accessible to corporate clients looking to integrate the technology into their business workflows. Offering a hybrid approach, TransPerfect combines AI and human translation to help clients achieve an optimal position on the quality-cost translation matrix for the content’s end use.

Furthermore, GlobalLink AI Portal offers unique security features that include the use of certified collocation facilities, encryption, secure HTTPS access, optional deactivation of data storage, single sign-on (SSO) integration, and user permissions and hierarchies.

TransPerfect President and CEO Phil Shawe said that “Efficiency and security are two of the pillars on which our company has operated for over 25 years. I’m happy to see the marketplace’s rapid adoption of our GlobalLink AI solution, but I’m even more pleased to know that we’ve delivered this technology in a way that both drives productivity and respects privacy.”

Tags:, , ,
+ posts

MultiLingual creates go-to news and resources for language industry professionals.

Related News:

Gallaudet University Partners with Apple and AppTek

Business News, Technology

In a moment when universities need the latest technology more than ever, Gallaudet University has announced two important partnerships with Apple and AppTek, which aim to provide its deaf and hard-of-hearing students with tools necessary to succeed in an increasingly technological world.

As the fall term commences, Gallaudet University has announced a couple exciting pieces of news for its deaf and hard-of-hearing students. Gallaudet is a federally chartered private university for the education of the deaf and hard of hearing located in Washington, D.C. In a statement on Thursday morning, Gallaudet University President Roberta J. Cordano announced that the university would begin a partnership with Apple to improve access and expand academic and career opportunities for Gallaudet students.

In her statement, the president said, “Beginning this fall, Gallaudet will provide all students and faculty with an iPad Pro, Apple Pencil, and SmartFolio for iPad Pro to support their learning and teaching. Students and teachers at the Laurent Clerc National Deaf Education Center will also participate in this new initiative.”

Providing students better access to the most up-to-date technology, the partnership will also establish an Apple scholarship program for students of color with disabilities. The scholarship will go to students pursuing studies in information technology, computer science, and other science, technology, and math related fields.

“Gallaudet has been at the forefront of advancing education and acceptance of Deaf culture in this country for more than 150 years,” said Lisa Jackson, Apple’s vice president of Environment, Policy and Social Initiatives. “We are honored to work together with this incredible institution to create even more opportunities for Gallaudet students and for all underserved and underrepresented communities.”

Furthermore, through the Connected Gallaudet initiative, Gallaudet students will participate in research projects to design bilingual applications. One project in particular was also announced this week, which revealed a partnership between Gallaudet University and AppTek, a leader in artificial intelligence (AI) and machine learning (ML) for automatic speech recognition (ASR) and machine translation (MT).

This application aims to provide video conference participants with live closed captions and deliver more control of the user interface (UI), allowing users to enhance the readability of real-time conversation transcripts and enjoy a more meaningful flow of spoken content.

“While much of the world is relying heavily on videoconferencing applications to communicate safely during the COVID-19 pandemic, commonly used applications unfortunately do not provide reliable, real-time capabilities that allow deaf and hard of hearing participants to engage fully,” said Mike Veronis, AppTek Chief Revenue Officer and Program Manager for the 21st Century Closed Captioning project. “We are passionate about and humbled at the opportunity to collaborate with Gallaudet on bridging that gap by developing new tools to give the deaf community greater freedom, control, and access to virtual communication.”

Integrating AppTek’s ASR platform, the application will incorporate the latest AI and ML technologies to enable this assistive service, which will be available to users on demand. Over time, Gallaudet also intends to incorporate multilingual capabilities using AppTek’s Multilingual Automatic Speech Recognition and Neural Machine Translation technologies.

Along with new technology and the application development project, Gallaudet University will also grant some students the opportunity to take part in the Apple Worldwide Developers Conference (AWDC) through the partnership with Apple. The annual event brings together over 5,000 developers, innovators, and entrepreneurs for engineering sessions, forums, laboratories, and keynote presentations about the latest app and software innovation.

Tags:, , , , , ,
Journalist at MultiLingual Magazine | + posts

Jonathan Pyner is a poet, freelance writer, and translator. He has worked as an educator for nearly a decade in the US and Taiwan, and he recently completed a master’s of fine arts in creative writing.

Related News:

Ethics of AI Tech Discussed in UNESCO Virtual Meeting

Technology

After publishing a draft on the ethics of AI, UNESCO organized a meeting to consult with experts and stakeholders about the findings. The Egyptian Minister of Communications and Information Technology gave a speech outlining Egypt’s efforts.

During a speech last week, Egypt’s Minister of Communications and Information Technology, Amr Talaat, outlined steps the country plans to take in its national strategy for AI. The speech centered around the aim of developing a comprehensive program to educate government employees on the capacities and implications of broad use of AI.

The minister’s remarks came during a speech in the opening session of the Regional Consultation for Arab States, held via video link. Hosted by the United Nations Educational, Scientific and Cultural Organization (UNESCO), the meeting took place over the course of two days. UNESCO was consulting about a draft text on the ethics of AI and recommendations for responsible use, which it is now developing after gathering input last month.

Among a group of 37 UN entities, Egypt represented a significant voice for its progress made recently in the field of AI. Talaat announced in the speech that Egypt has established the National AI Council, which oversees the implementation of the national strategy for AI in all sectors. He added that the Applied Innovation Centre (AIC) has begun to implement AI-related projects in areas like machine translation and early detection of diabetic retinopathy. They have also planned a project in the accurate calculation of irrigation water for agriculture.

The speech follows an agreement earlier in the summer between iFLYTEK and the Egyptian Ministry of Communications and Information Technology (EMCIT). The Chinese-Arabic Language Translation Research Agreement will leverage iFLYTEK’s technological language research with EMCIT’s AI and high-performance computing applications to develop projects in Arabic speech recognition, speech synthesis, and Chinese-Arabic translation.

Talaat commended UNESCO for coordinating so many voices in the discussion about the ethics of AI. He noted that the global representation of the meeting signaled positive results moving forward, as experts from around the world deliberate the ethics of AI technology.

 

Tags:,
+ posts

MultiLingual creates go-to news and resources for language industry professionals.

Related News:

Translated to provide EU Parliament with real-time speech translation AI

AI, Business News

Debates will be transcribed and translated by a new state-of-the-art MT system that keeps humans in the loop

blue and white flags on poleTranslated has been selected by the European Parliament to automatically transcribe and translate parliamentary multilingual debates in real-time, covering the 24 official languages used by the institution. The service will be provided by new software available both through fully-localized web and mobile applications, and live streaming APIs for third-party developers. It it purported to be the first human-in-the-loop speech machine translation (MT) system, and should leverage context and user feedback to adapt the output in less than one second.

The product will be developed in collaboration with two companies that have already worked with Translated in building products for professional translators: Fondazione Bruno Kessler (FBK), a world-leading research center in MT and automatic speech recognition (ASR); and PerVoice, an ASR world-leading provider. Within the next 12 months, the consortium will release a prototype to be tested by the European Parliament. This solution will be considered alongside solutions provided by two other groups, following rules put forth in “Live Speech to Text and Machine Translation Tool for 24 Languages.” The best-performing tool will be confirmed as the official one for the following two years.

The new product is not a simple concatenation of ASR and MT, but a new, fully-integrated system in which the MT algorithms are tolerant of ASR errors. This approach will not only help deliver more contextualized translations, but it will also open up the opportunity to improve the quality of the output while the plenary session is happening. This is possible thanks to the human correction feedback that the tool allows by both the end-users and a team of professional translators.

“For this project, we are bringing together ten years of research in machine translation and speech recognition,” says Simone Perone, Translated’s vice president of product management. Some of the new AI models that will be used have already been put to work successfully in products such as ModernMT (an MT that improves from corrections and adapts to the context), Matecat (a computer-assisted translation tool that makes post-editing easy), and Matesub (the first subtitling tool offering suggestions during the transcription, now in beta and due to be released in September 2020).

Tags:, ,
+ posts

MultiLingual creates go-to news and resources for language industry professionals.

Related News:

NBA, Microsoft May Alter Global Sports Consumption

AI, Machine Learning, Personalization and Design

Marketing games for international venues, celebrating the Lunar New Year with Chinese characters on jerseys, or recruiting a global class of players, the National Basketball Association is no stranger to localizing its content. But deepening AI and machine learning technologies promise an approach to its global fan base like never before.

Spalding basketball in courtThe NBA announced in April that it has made plans to enter a multi-year partnership with Microsoft to create a more personalized, localized experience for its international fan base. But while fans around the world already enjoy watching NBA broadcasts in 47 languages broadcast in 215 countries, the partnership promises fundamental innovations to modernize fan interaction using artificial intelligence and machine learning technology.

One of the ways the alliance will change NBA content is by creating a direct-to-consumer platform on Microsoft Azure, Microsoft’s cloud computing service, which will provide data analytics, computing, storage, and networking that they anticipate will allow them to personalize fan experience “through state-of-the-art machine learning, cognitive search and advanced data analytics solutions,” according to the report.

Analyzing metrics around fan behavior is nothing new for the NBA, but with such data at its fingertips, the NBA-fan relationship may flourish like never before. NBA senior vice-president of direct to consumer Chris Benyarko said about the benefits of machine learning AI curating fan experience, “Instead of the fan having to pick and choose and turn them on or off one by one, the platform is now starting to behave like a game producer, automatically selecting and presenting the game in a different way.”

Deb Cupp, Corporate Vice President of Enterprise and Commercial Industries at Microsoft, said, “The AI eventually learns that I like to learn about stats, so it’s going to start presenting me more information about stats as I go into the game… It’s this experience where instead of just watching a game, it actually has the opportunity to interact in a way that matters to me as that fan.”

With fans in all different time zones who experience the game and consume content in a variety of ways, the NBA will be able to gather a global array of data to bring in new fans and retain old ones. What that will mean for sports remains to be seen, but the machine learning will likely provide invaluable information on fan behavior worldwide and grant the NBA a chance to solidify its place as a premier global sport.

Tags:,
Journalist at MultiLingual Magazine | + posts

Jonathan Pyner is a poet, freelance writer, and translator. He has worked as an educator for nearly a decade in the US and Taiwan, and he recently completed a master’s of fine arts in creative writing.

Related News:

Localization tech predictions for 2019

AI, Blockchain, Localization Technology, Machine Learning

Happy 2019!

Let’s look over the past year to get a sense of how much progress we have made, and what progress may lie before us. AI has become a norm in our lives and is now part of the vernacular more than ever. People have accepted that their lives interact multiple times a day with AI, and that such technology is becoming ubiquitous. 

What does 2019 hold for us? Well, if we pay attention to the predictions of 16th-century seer Nostradamus, we should brace ourselves for flooding, wars and a strike by a meteor. Nothing all that cheerful but, assuming we survive all of that, what does 2019 hold for technology trends?

AI

We’ve seen an explosion in the use of AI in the delivery of neural machine translation during 2018; expect this to continue in 2019 and beyond. AI is the catch-all term to cover machine learning (ML) and deep learning. Machine learning is an over-arching term for the training of computers, using algorithms, to parse data, learn from it and make informed decisions based on accrued learning. Examples of ML in action is Netflix showing you what you might want to watch next. Or Amazon suggesting books you might want to buy.

Within the localization industry, the use of AI in the form of machine translation (MT) in several forms has significantly improved translation quality outputs, sped up translation of huge quantities of data and reduced the price of translation to make it economically viable.

AI refers to computer systems built to mimic human neural abilities and to perform tasks such as image recognition, parsing speech forms, discerning patterns from complex data sets and informing accurate decision-making. What’s more, AI can do these tasks faster, cheaper and more accurately than humans. Although AI has been around since the 1950s, it can be truly said that it has now come of age. This maturity has been propelled by the ever-increasing computational power now available in the cloud. 

According to Forbes, five out of six people use AI technology each day. These services include such things as navigation apps, streaming services (such as Netflix), smartphone personal assistants, dating apps and even smart home devices (such as remote-activated home security systems). Additionally, AI is used in recommendation engines used by eCommerce sites to schedule trains, to predict maintenance cycles and for other mission-critical business tasks. 

For the localization industry, AI will become a highly-integrated component of MT systems. The role of the human translator will continue evolving to that of an editor of MT texts, rather than translator of raw texts. In addition, pricing models will continue to move from the traditional price per word based on word volumes to pricing on a time-measured rate. MT will become an integral part of the standard workflow. The reality of real-time translation — driven by such technology as the internet of things (IOT) — will see project managers and editors managing workflows of projects required by customers who need a constant flow of updated information. MT will become part of the translation process just as much as other computer-aided translation tools did in the past. And, as ever, evolving technology will bring with it a desire for speedier and cost-effective solutions. 

Machine learning 

localization tech

ML will continue to grow as a tool used by most localization departments as the requirement for the speedy translations of large datasets continues to be a driver in the industry.  

ML is a subset of AI: with ML, computers are automated to learn to do something that they are not initially programmed to do. So, ML is an over-arching term for the training of computers to use smart algorithms to automate actions, to parse complex data and to learn patterns from this learning thus enabling the computer to make informed decisions based on this accrued knowledge. ML can be broadly broken down into two types of learning: supervised and non-supervised learning. 

For supervised machine learning, the training data is pre-labelled and consists of an aligned input data set and desired output data set. For example, an input data set could be a translation memory. An ML algorithm analyses the training data and maps how to convert future inputs to match the learned, desired output data sets. 

Unsupervised ML is like supervised ML; however, the input data sets are not pre-classified or labelled. The goal of unsupervised machine learning is to find hidden structures in the unlabelled data. 

So how does this impact the localization industry? Well, suppose you want to build a translation system to translate from Zulu to French, without any Zulu-French training data. The solution is, you can combine both supervised and unsupervised approaches to achieve this. You can use an English-Zulu data set in combination with an English-French data set, and using unsupervised machine learning, the system can learn how to translate from Zulu into French. 

This approach is commonly referred to as “zero-shot” machine learning — expect to hear more about this in 2019 for MT systems for long-tail languages. 

Blockchain 

While blockchain is most widely known as the technology behind cryptocurrencies, it offers security that is useful in many other ways. 

In simple terms, blockchain can be described as data you can add to, but not take away from or change. These blocks of data can be “chained” together to create incredible secure data repositories. Not being able to change any previous blocks is what makes it so secure. 

This enhanced security is why blockchain is used for cryptocurrencies. It is also why it will play a significant role in localization where it will used to protect information such as a client’s financial details, and to protect and preserve translation memories; especially in translation memories used in distributed translation workflow scenarios. 

Edge computing 

Cloud computing has now become mainstream: most of all global companies now rely on this centralized hosting structure for machine learning and powerful computational power. This cloud market is dominated by just a few gigantic companies such as Amazon, Microsoft, Google and IBM. However, now that we’ve been using cloud computing for some time, companies have realized that accessing all data from a central repository introduces a time-delay latency, which in turn slows down the delivery of services which can, in turn, increase costs. The “round trip” made by cloud-based data is seen by many of today’s companies as a hindrance to their business growth. 

Technology stands still for no man, and so, for many, the cloud has reached its peak as a service for some technologies. The cloud will continue to be used to analyze and process huge swathes of data, but the advent of the IoT (connected security systems, electronic appliances, vending machines, automated lighting), where data processing needs to be high speed, if not real time, demands a different model. So the logical and necessary next move is to move this data processing to the edge. The edge simply means that data processing is moving from a far-away storage location to a geographical site closer to the data source. The advent of powerful computer chips that allows such processing to be done locally has expedited this move to the edge. Indeed, many of today’s cloud setups automatically look to place the processing of data at the optimum edge site for that data’s requirements. 

So, edge computing solves the latency problem by simply moving the data processing closer to home. Closer to home means less time spent uploading and downloading data. Instead of the centralized storage model, which has hitherto driven AI, companies are moving their data into the “local community” to be processed. This move will undoubtedly make data access much faster and facilitate the growing demand for real-time computing. 

How will this impact localization? Well, in 2019 we can expect to see the edge model used in domain-adapted MT systems, and distributed translation workflows that are designed to meet the increasing demand for data distribution in real-time. 

Conclusion 

We are on the verge of an explosion in the use of AI. The inevitable growth of AI will fundamentally re-shape how companies manage translation workflows; the very engine of their work process. Real-time translations will often become the norm. 

I also predict that changes will happen at a human level; for example, the role of the translator will change from that of translator of raw text to that of editor of huge volumes of high-quality MT-produced text. This will be a beneficial change, allowing translators to increase their capacity and so increase their income. In 2019, we predict that the overall transformation effected by the advent of AI at all levels of the industry will bring with it an increased velocity of production, an improved efficiency in the delivery of translations, and a reduction in the cost of translating huge volumes of data. 

We hope you all have a very successful 2019! 

 
Tags:, ,

Tony O’Dowd is the founder and chief architect of KantanMT.com, a cloud-based custom machine translation solutions provider. He is a serial entrepreneur and localization veteran, with almost 30 years’ experience working in the localization industry.

Related News:

Humor and AI: Does it travel?

Localization Technology, Personalization and Design

Conversational interfaces such as chatbots and voice assistants present many localization challenges — humor, for example. And that’s not even considering if the original content was all that funny to begin with.The secret to AI comedy must be in the data Click To Tweet

Humor: The final frontier

“Are there any Scottish people in the audience?”

Always a great start to a presentation at a conference. The response I received was, “You’re going to show that Scottish Elevator Voice UI video, right?”

I wasn’t.

Instead, I used the top jokes from the 2018 Edinburgh Festival Fringe as my opener to a workshop at ConverCon 18 on the subject of artificial intelligence (AI), personality, and conversational UI.

Of course, humor is an integral dimension of human personality and therefore part of that natural, conversational human-machine dialog. But humor has been called the final barrier for AI for good reason. There are many challenges.

I began my ConverCon workshop by telling the best joke from the Fringe.

“Working at the Jobcentre has to be a tense job — knowing that if you get fired, you still have to come in the next day.”

As soon as I recited the joke, I realized that it may not have been that funny to my global audience. Had they any idea what a Jobcentre is? It’s a British public service. In Ireland, the equivalent, an Intreo Centre, is offered by the Department of Work Affairs and Social Protection. In the United States, it might be called a WorkForce Center or One-Stop Center.

Conversational UI and the secret to comedy

Real US English examples of conversational interfaces, chatbots and AI can be tricky when it comes to humor.

Take this processing message from the Meekan scheduling robot on Slack. It makes a “witty” reference to hacking into TSA servers and No Fly Lists. I really winced at that one. I know what the TSA and No Fly Lists are, and I still didn’t get the joke.

Meekan scheduling robot on Slack (Image by Ultan O'Broin)

Meekan scheduling robot on Slack (Image by Ultan O’Broin)

This got me thinking about the challenges of humor and AI. If the secret to human comedy is timing, then the secret to AI comedy must be in the data, as well as the context.

Humor does have a place in conversational interaction, even in the most seemingly unlikely interactions, for example, Woebot. But humor needs to be done right.

Humor is not only the final frontier for AI, it’s a human personality trait that is easily lost in translation. Worse still, even in the original language, humor is not always that funny to everyone in a native audience. Of course, you don’t have to be Geert Hofstede to realize that humor doesn’t travel across cultures, but machines don’t get that. Yet.

So, as the localization industry rises to the challenge of dealing with AI, personality, humor, and the realization that no UI is the best UI of all, we can expect new talents will flourish to ensure that the conversational user experience resonates with the target audience. Do today’s translators need to have performing arts backgrounds or be comedians to enhance that local conversational interaction? I think storytelling skills are about to become hot property in every language.

Do today's translators need to have performing arts backgrounds or be comedians to enhance that local conversational interaction? Click To Tweet

Your punchline?

You may have other examples of humor and localization challenges from the world of technology. If so, share them in the comments!

Tags:, , , , , , , , , , , , , , , , , ,
+ posts

Ultan Ó Broin (@localization), is an independent UX consultant. With three decades of UX and L10n experience and outreach, he specializes in helping people ensure their global digital transformation makes sense culturally and also reflects how users behave locally.

Any views expressed are his own. Especially the ones you agree with.

Related News: