Technology

How to Effectively Localise and Manage Content at Scale for International Success

shubham.laygude — Mon, 14 Apr 2025 07:11:38 +0000

How to Effectively Localise and Manage Content at Scale for International Success shubham.laygude Mon, 04/14/2025 - 03:11

Webinars

Date: April 08th 2025

Session Details: Join us for an exclusive panel discussion featuring experts from ��ɫ, Contentful, and IDP Education as they delve into the strategies and technologies essential for managing multilingual content at scale. This insightful event will explore how automation and artificial intelligence play a critical role in streamlining content processes for enterprise brands.

Panelists:

Sunaina Ajwani Howells | Regional Strategic Alliances, APAC | ��ɫ
Paulina Belcik | Director, Strategic Accounts | ��ɫ
Emily McIvor | Head of Digital | IDP Education
Nivedhika Muthuswamy | Content Engineering Manager | IDP Education
Prashanthi Shankar | Senior Product Marketing Manager | Contentful

Technology

How the Manufacturing Industry Will Evolve in 2025

tanvi.channe — Wed, 26 Feb 2025 07:49:05 +0000

How the Manufacturing Industry Will Evolve in 2025 tanvi.channe Wed, 02/26/2025 - 02:49

Blog

Manufacturing is evolving faster than a factory conveyor belt, driven by cutting-edge technology, shifting supply chains, and a workforce transforming just as quickly as the industry itself. Today’s factories run on AI-driven insights, hyper-connected supply chains, and sustainability goals that would impress even the most die-hard environmentalists. As we enter 2025, the manufacturing industry is becoming smarter, faster, and more sustainable. So, what’s shaping the future? From AI-powered efficiency to workforce retention strategies that prioritize inclusivity, here’s a look at the manufacturing trends set to define the industry this year.

AI and Generative AI: Efficiency on Autopilot

Move over, old-school automation—AI is taking manufacturing efficiency to a whole new level. Forget the days of scrambling to fix broken machinery only after production grinds to a halt. AI-powered predictive maintenance spots problems before they happen, sending alerts like a hyper-attentive car dashboard light. Consider a heavy machinery manufacturer that embeds AI-driven sensors into its equipment. Instead of waiting for a conveyor belt to suddenly seize up mid-shift, the system detects micro-irregularities in vibration patterns and schedules maintenance before disaster strikes. The result? Reduced downtime, happier workers, and a maintenance crew that actually gets to drink their coffee while it’s still warm. And then there’s generative AI (GenAI)—the brainpower behind rapid product design and prototyping. Picture a global aerospace company using GenAI to draft thousands of possible designs for a lightweight aircraft component in a matter of hours. Engineers no longer have to painstakingly tweak CAD models for weeks—they select the best AI-generated options, saving time, money, and countless headaches. Speaking of fewer headaches, multilingual documentation using AI-powered translation tools helps to centralize technical documents for global teams, speeding up collaboration and time-to-market

AI Innovations Powering 2025 Manufacturing:

Predictive maintenance: AI identifies issues before they escalate, minimizing downtime and keeping production lines running smoothly.
Generative design: GenAI accelerates product development by generating and optimizing thousands of design iterations.
Multilingual documentation: AI-powered translation tools streamline global communication, ensuring consistent technical documentation across teams.

Smart Operations: Tech-Powered Production Lines

Gone are the days when factory workers relied on clipboards and gut instinct. Smart operations leverage robotics, IoT (Internet of Things) devices, and cloud-based platforms to create hyper-efficient production lines where everything is interconnected. Imagine walking into a state-of-the-art factory where digital twins—virtual replicas of physical operations—track every detail in real time. Sensors monitor temperature, humidity, and equipment status, optimizing performance before problems arise. A minor tweak in production? No need for costly trial and error—just test the change in the digital twin and roll out the best version. And then there are cobots (collaborative robots)—the friendly, non-threatening cousins of traditional factory robots. A car manufacturer uses cobots to assist workers with assembling parts and handling heavy lifting, while humans focus on precision tasks. These machines not only work tirelessly but also reduce repetitive strain injuries.

Smart Operations Strategies for 2025:

Robotic automation: Automated cobots help humans increase output while reducing workplace injuries.
Localized user interfaces: Advanced machinery with touchscreens allows operators in different countries to navigate in their native language and adapt to regional specifics—no more guesswork or accidental system resets.
Real-time data tracking: Smart factories adjust production instantly, rerouting materials before delays escalate to minimize supply chain disruptions.

Attracting & Retaining Talent in the Manufacturing Industry

While robots and AI are getting smarter, let’s not forget the real powerhouse behind manufacturing: people. With an aging workforce, a growing skills gap, and stiff competition from other industries, manufacturers face a massive talent shortage. In 2025, companies will need to rethink how they attract, train, and retain skilled workers. Competitive wages and benefits are just the start—companies must also invest in modern training programs, career development opportunities, and workplace cultures that make employees want to stay for the long haul. And in a global industry where factories span continents, ensuring multilingual communication is key to keeping a diverse workforce engaged and aligned. Consider a multinational automotive parts manufacturer that struggled with training its global workforce. Employees in different regions were getting conflicting instructions, causing inefficiencies and safety concerns. The solution? A multilingual e-learning platform that delivered training modules in every major language spoken across its workforce—ensuring everyone was on the same page, from warehouse workers in Mexico to engineers in Germany.

Talent Development Strategies for 2025:

AI-driven upskilling: AI-powered training modules adapt to workers' skill levels, offering personalized learning experiences.
Multilingual training programs: Companies partner with language service providers to develop e-learning modules that cater to diverse linguistic backgrounds, ensuring safety protocols and process training are consistently understood worldwide.
Culturally inclusive onboarding: Companies create training materials using translation and localization techniques that respect local customs and workplace expectations.

A global workforce demands seamless communication—from training manuals to safety protocols—and multilingual solutions are essential for keeping employees engaged and informed. After all, it’s difficult to expect high-quality output when half the workforce is left guessing at the meaning of their instructions.

Sustainability: The Green Factory Revolution

Sustainability in manufacturing isn’t just about looking good in an ESG report—it’s essential for staying profitable, competitive, and compliant in an era where consumers and regulators are watching closely. Rising environmental regulations, consumer expectations for ethical practices, and the economic benefits of resource efficiency all point towards making sustainability imperative in 2025. For example, a major electronics manufacturer recently revamped its entire supply chain to be carbon-neutral. From sourcing recycled metals to optimizing shipping routes for fuel efficiency, the company slashed emissions while also cutting costs. Another game-changer in the manufacturing industry? Energy-efficient factories. A European textile company installed solar-powered machinery and switched to water-saving dyeing techniques, reducing energy bills and waste output. An unexpected bonus was that their customers loved the eco-conscious branding just as much as the products. Transparent reporting is another key part of this shift. When companies publish annual sustainability reports in multiple languages, they ensure stakeholders around the world can clearly understand environmental commitments and progress.

Sustainability Strategies for 2025:

Green supply chains: Companies source materials ethically and minimize carbon footprints.
Waste reduction: Smart factories cut down on production waste with AI-driven efficiency.
Transparent reporting: Global brands release multilingual sustainability reports, reinforcing accountability and trust.

Looking Ahead: The Future of Manufacturing is Smart, Sustainable, and Inclusive

Manufacturing in 2025 is about more than just building products—it’s about building better, faster, and more responsibly. AI and automation are streamlining efficiency, smart operations are optimizing production, multilingual strategies are fostering a truly global workforce, and sustainability is at the core of business models. For manufacturers expanding into international markets,language and localization matter now more than ever. Whether it’s AI-powered translations, multilingual training programs, or global compliance documentation, companies need partners who can bridge communication gaps seamlessly and stay aligned with evolving manufacturing trends. That’s where ��ɫ comes in—helping manufacturers thrive by ensuring that language, culture, and technology work together. Ready to kickstart your global strategy? Explore ��ɫ’s global content solutions for manufacturing.

By ��ɫ

Technology

Manufacturing

��ɫ Connect- AI in CCO space webinar

tanvi.channe — Thu, 20 Feb 2025 07:18:41 +0000

��ɫ Connect- AI in CCO space webinar tanvi.channe Thu, 02/20/2025 - 02:18

Webinars

Catch our expert panel as they explore how automation is transforming multi-language contact centers .

Diego Bartolome and Claire Mullins cover:

Real-World Deployments – Lessons from successful automation rollouts.
Emerging Trends–The latest advancements in multilingual customer engagement.
Technology Adoption – How organizations are embracing automation.
Risk Mitigation – Strategies for a smooth, secure transition.
Maximizing Benefits – Enhancing efficiency and satisfaction for agents and customers.

Technology

The Future of Driving: How AI is Shaping the Automotive Industry in 2025

jpressman — Mon, 17 Feb 2025 16:49:35 +0000

The Future of Driving: How AI is Shaping the Automotive Industry in 2025 jpressman Mon, 02/17/2025 - 11:49

Blog

The automotive industry is racing toward an awe-inspiring future, fueled by groundbreaking advancements in artificial intelligence (AI) and emerging technologies. While we’re already seeing the impact today, the true potential of AI in vehicles is just beginning to unfold. From smarter connectivity and self-driving cars to seamless updates and predictive maintenance, AI is poised to completely redefine how we design, drive, and interact with these vital machines. Buckle up as we explore the game-changing ways AI will transform the automotive world in the years ahead.

Connectivity: The Backbone of Smart Vehicles

As consumers demand more from their in-car experiences, automakers are increasingly integrating advanced connectivity features that enable cars to communicate with devices, systems, and even other vehicles on the road. Many vehicles already offer Wi-Fi connectivity, Bluetooth integration, and smartphone apps that let drivers control various functions remotely. However, with the rise of AI-powered systems, cars will become even smarter—learning driver preferences and behaviors, automatically adjusting settings based on historical data, and providing real-time updates on road conditions, weather, and traffic.

How AI is transforming vehicle connectivity is evident in technologies like vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication. Powered by AI, these systems allow cars to “talk” to each other and surrounding infrastructure, such as traffic lights and road signs. This will improve traffic flow, reduce accidents, and even help reduce congestion. Additionally, AI will enable the integration of cloud-based services, allowing vehicles to receive real-time updates, access new features, and download software patches without visiting a dealership. This level of vehicle connectivity will transform cars into dynamic, ever-evolving systems that become more efficient and user-friendly over time.

AI-Powered Autonomous Driving

One of the most transformative applications of advanced technology in the automotive sector is the role of AI in autonomous vehicles. Over the past decade, AI capabilities have made significant strides in enabling self-driving cars. This progress is driven by machine learning, deep learning, and computer vision, which allow cars to “see” and interpret their surroundings, understand traffic patterns, and make real-time decisions. As AI models continue to advance, autonomous vehicles will become safer, more reliable, and increasingly accepted by the public.

While autonomous vehicles may not dominate our roads in the immediate future, the gradual rollout of semi-autonomous features—such as adaptive cruise control, lane-keeping assist, and automatic parking¬—is already underway. AI will also play a crucial role in the development of “driverless fleets,” which could revolutionize the transportation and logistics industries. These AI-powered fleets would be able to operate 24/7, reducing costs and increasing efficiency while removing human error from the equation.

Annual Updates: A New Era for Vehicle Evolution

Automakers are increasingly offering vehicles that receive over-the-air (OTA) updates, enabling them to add new features, fix bugs, and even improve performance remotely. These OTA updates, often powered by AI, will become a core part of the future driving experience. For instance, AI systems will learn from real-world driving data and fine-tune a car’s driving dynamics, improving things like fuel efficiency, performance, or handling through software updates. AI could also be used to enhance infotainment systems, making them more personalized and intuitive based on user preferences.

Annual updates will affect not only software but potentially hardware improvements as well. As automakers adopt more advanced AI technologies, it’s possible that vehicles will evolve more rapidly, receiving new features and functionalities each year. This means consumers may no longer have to wait for the latest model to enjoy the latest advancements in vehicle technology.

Predictive Maintenance and Enhanced Safety

By continuously monitoring a vehicle’s components, AI systems can predict when maintenance is required before a part fails, potentially saving consumers time and money by avoiding breakdowns. For example, AI could monitor battery health, tire pressure, and brake wear, notifying drivers when it’s time for service or a part replacement.

AI will also play a significant role in enhancing driver and passenger safety. AI-powered systems will enable more accurate collision avoidance, real-time hazard detection, and advanced driver assistance systems (ADAS). These systems will continuously learn from driver behavior, road conditions, and accident data, becoming more effective at preventing crashes and reducing the severity of those that occur.

In the future, fully autonomous vehicles will eliminate many human errors that cause accidents, resulting in a dramatic reduction in road fatalities and injuries. AI-driven vehicles will have the ability to react faster and more accurately to sudden changes in the driving environment, providing a level of safety far beyond what human drivers can achieve.

Sustainability: AI in the Quest for Efficiency

Electric vehicles (EVs) are already gaining traction, but AI will help optimize energy consumption, battery management, and charging infrastructure. AI algorithms can predict the most efficient routes, adjust energy usage based on driving habits, and even help manage charging times to minimize energy costs or grid congestion.

In addition, AI will play a key role in vehicle design, helping manufacturers create lighter, more efficient cars with minimal environmental impact. By analyzing vast amounts of data, AI can suggest design improvements that reduce fuel consumption, lower emissions, and enhance overall vehicle efficiency.

The Road Ahead: Challenges and Opportunities

While the potential of AI in vehicles is immense, there are still challenges to overcome. Concerns around data privacy, cybersecurity, and the ethical implications of autonomous driving remain prevalent. However, the industry is moving toward solutions that address these issues, with stricter regulations, better encryption, and AI models that can operate transparently and safely.

The future of AI-powered cars and driving technology will depend on how the industry navigates these challenges. As connectivity, autonomy, and AI-driven technologies evolve, vehicles will become smarter, safer, and more efficient, offering unparalleled experiences for drivers and passengers alike.

With our global reach and cutting-edge AI capabilities, ��ɫ is helping the automotive industry break down barriers and create vehicles that are not only intelligent but also adaptive to the diverse needs of drivers worldwide. By bridging language, connectivity, and technology gaps, ��ɫ is ensuring the future of driving is more connected, intuitive, safe, and efficient for everyone on the road.

Ready to accelerate your global strategy? Get in touch with our experts and drive your business forward today!

By ��ɫ

Technology

Automotive

Technology

Translation AI: Hype vs. Impact

muna.abdulkader — Mon, 13 May 2024 16:09:15 +0000

Translation AI: Hype vs. Impact muna.abdulkader Mon, 05/13/2024 - 12:09

Blog

The launch of ChatGPT in late 2022 sparked immediate hype around generative AI. Many were quick to declare that AI would destroy all jobs. In the translation world, what AI is doing is enhancing productivity and opening up new opportunities.

In a recent webinar, ��ɫ’s Diego Bartolome, head of AI.NOW, and Ty Trainer, Machine Translation Implementation Manager, delved into what they call “translation AI,” a way of doing translation that stacks generative AI on top of existing technologies. They talked about how to get started implementing AI into workflows, use cases, and emerging opportunities.

Translation AI: The New Reality

��ɫ has been doing machine translation (MT) for about 30 years. Now, we’re integrating generative AI (specifically, large language models, or LLMs) to help us do more. Translation AI is a framework for understanding this AI-integrated way of performing translation and localization. It’s thinking about AI not as a distinct, unconnected technology but as a set of technologies that work together to maximize productivity while also ensuring quality and extending savings.

How Has AI Hype Impacted Companies?

Push to implement: Companies are pressured by leadership to implement AI solutions. But they may not know how to do it, or what it will mean for operations. Ideally, it’s done slowly and thoughtfully in a way that considers different use cases and requirements for various business units within the company.

IT solution to “the language problem”: Translation has shifted from being owned by marketing to being owned by IT departments. Companies think human translation is expensive, and they see generative AI as the most efficient solution. But often, the people involved in the content and localization processes are not consulted before solutions are implemented. To be effective, companies need to drive change with people, as technology alone will not solve everything.

Reshaping content and localization goals: The translation industry is becoming more technological, which is reshaping roles and challenging traditional processes—even creating new career paths. People need to understand the technology and how best to incorporate it into workflows.

The AI Maturity Model

There is a temptation to implement AI for the sake of it, but this is the wrong approach.

Don’t implement AI because it’s there; do it to solve a business problem. Many companies are in the early stages of implementing AI, and the best way for them to “move up” is through experimentation. We experiment with customers on their AI journey. We create pilots and minimally viable products (MVPs)—the first version of a product or service that allows customers to understand when generative AI or AI can help the business. If it works, we scale. If not, we try something else.

From Hype to Reality: Where Are We Seeing Generative AI Applied Most Usefully?

We look at how LLMs can combine with existing translation workflows to improve processes. We ask: How can we stack—or more meaningfully incorporate—generative AI into translation-specific workflows? We can use generative AI in conjunction with existing AI technologies that companies are using for translation, i.e., neural machine translation (NMT).

Machine translation is a mature application of AI. It’s been at the peak of productivity for 15–20 years. LLMs are a more nascent technology. While NMT is designed for translation, LLMs are open-ended in what they can do. At ��ɫ, we have found in almost every use case that NMT outperforms generative AI in terms of translation quality. We leverage both for their respective strengths.

Here are three areas where we are seeing success:

Accelerating post-editing tasks
Maximizing translator efficiency
Offering greater translation fluency

Once we have our source content, we use AI to optimize it. This is a fully automated step. We then use translation AI (NMT + LLMs) to translate and perform post-editing, with a human-in-the-loop option.

Emerging Opportunities

Synthesis AI is being used to draw insights from content. We foresee being able to incorporate synth AI for multilingual content generation. Instead of producing the content and then translating it into multiple languages, we’d be producing it in multiple languages. Eventually, instead of translators, we’d have in-language reviewers.

This would happen first with lower-risk content. For example, you could feed synth AI a prototype, a few features, and an image to write multilingual product descriptions for different retailers.

Assess Translation Needs

Do you need machine translation for projects that would be too expensive if you used humans only? Do you need real-time translation to quickly reply to a large number of customers in various geographies? Do you want to increase the efficiencies of your human translation process?

Look at samples of documents that need translating. How many and which languages do you need? What are your quality requirements? Do you have historical translations to draw from? We can use what you have to calculate the approximate level of productivity and quality you can expect to see from MT.

The best thing companies can do to integrate AI is to start small. An organization doing human-only translation can’t expect to jump immediately to a fully automated workflow.

And remember that data is critical for both AI model training and for proving ROI. Organizations need to reliably report on ROI. Having a reliable way to use data to measure impact is crucial. Finally, integration doesn’t happen overnight. Expect to build, learn, and iterate.

Click to view the webinar.

��ɫ Team

Technology

How Generative AI is Changing the Localization Game

muna.abdulkader — Thu, 01 Feb 2024 19:10:48 +0000

How Generative AI is Changing the Localization Game muna.abdulkader Thu, 02/01/2024 - 14:10

Blog

As we reflect on 2023, we do so with tremendous gratitude. Over the last year, ��ɫ continued its track record of uninterrupted growth, and we had the humbling opportunity to apply our resources and technologies in many ways to support our clients and communities.

Nothing was more prevalent in our 2023 offering than the application of generative AI. As our businesses continue to evolve around this exciting innovation, we wanted to highlight the top three business areas where GenAI is changing the localization game.

Translation

Generative AI has revolutionized multilingual content by enabling faster, more fluent, and cost-effective solutions. However, it’s important to note that machine translation is a mature technology that started in the ‘50s with rule-based systems, and current products in the market pioneered the use of transformers, the architecture behind large language models (LLMs).

��ɫ’s solution, already based on deep learning, will enable the combination of the best-trained machine translation models with LLMs to adapt sentences for better understandability. In our models, we use translation memories, glossaries, and other linguistic assets to tailor machine translation outputs to the client’s style, terminology, and tone of voice. For many languages, the output quality can be on par with human translation, but we would still recommend the human touch to guarantee an error-free text.

Additionally, in some verticals where the output doesn’t need to be an exact translation of the source, pioneers are piloting multilingual content creation thanks to the effective use of LLMs and other solutions that enable SEO-optimized content.

While we have integrated OpenAI models into translation workflows, we’ve found that performance is lower when compared to a well-trained, custom MT engine. We are also integrating LLM-based actions into our tools to improve outputs—upgrading machine translations or turning a fuzzy match into a better translation. For AI content pre-editing, we’ve also started using LLMs for quality improvements, quality estimation of machine or human translation, and automated post-editing of MT outputs.

Digital Marketing

Beyond content creation and optimization for a wider reach, AI-powered tools are helping marketers accelerate their digital marketing campaign pipelines and reduce the effort needed to get campaigns off the ground.

At ��ɫ, we have experience across a variety of scenarios, like optimizing multilingual ad copy with generative AI and traditional digital marketing tools. What was previously done in days now takes minutes, enabling faster time-to-market as well as continuous A/B testing to improve campaigns in real time. By streamlining keyword research, we can reduce workloads for digital strategists so they can spend their time on more valuable activities. We also work with images to generate visuals for online content as well as descriptions of the images for efficient and cost-effective accessibility and SEO alt-text. For campaigns that involve video, synthetic voices can be used to create a “brand voice” that is consistent across markets and platforms.

Generative AI and automation enable businesses to efficiently engage customers with relevant, high-quality content, maximize their online visibility, and create more inclusive and accessible shopping experiences, ultimately driving sales and brand loyalty.

Besides text projects for meta titles and descriptions, product or destination content, and many others, one of the most promising areas is visuals. On one side, we’re using AI to describe images—and applying those descriptions not only to alt-text but also to train AI-generated text. On the other side, we’re leveraging image AI to significantly reduce costs for creating website images. We can modify backgrounds, place products in different scenes, extend images, or even create images that do not exist. The next frontier: multimodal models for text, images, speech, and videos.

Customer Support

By providing predictive responses and accelerating query resolution, AI-powered customer support tools can increase agent capacity by up to 50%. Chatbots and virtual assistants leverage massive datasets (FAQs, knowledge bases, product information, previous tickets, etc.) to anticipate and provide accurate solutions to customer inquiries in real time. Thanks to the multilingual nature of AI technology, the customer support tools can do this in multiple languages and therefore, empower monolingual customer service teams to respond to queries no matter what language they speak. This not only speeds up response times but also allows human agents to focus on more complex issues that a chatbot wouldn’t be able to solve. By enabling customer support teams to handle a significantly larger volume of interactions, overall efficiency and customer satisfaction are improved, leading to increased brand loyalty. Finally, due to the multilingual aspect of AI-powered customer support, you may no longer need representatives in all markets where you sell. Something ��ɫ is working on long-term is integrating speech-to-speech translation in call centers, which will improve efficiencies and enhance customer satisfaction.

In summary, generative AI is reshaping the localization landscape. From streamlined translation to enhanced digital marketing and efficient customer support, this technology is revolutionizing operations. Businesses adopting generative AI are empowered to reach global markets, adapt quickly, and provide more personalized experiences. It's no longer an option but a necessity for those seeking success in such a competitive industry.

Need help deploying GenAI at your company? You know where to find us!

��ɫ Team

Technology

��ɫ & Generative AI

muna.abdulkader — Wed, 03 Jan 2024 20:53:13 +0000

��ɫ & Generative AI muna.abdulkader Wed, 01/03/2024 - 15:53

Blog

Generative AI won’t kill you, but it could kill your business if you don’t adapt to it. According to Venture Beat, 59% of organizations lack the resources to address expectations around generative AI. As more and more people use applications such as ChatGPT, Bard, and Claude, companies are analyzing the implications AND potential impact on their teams in customer experience, accounting, marketing, digital, and more. Given the speed at which the technology is advancing, it can be difficult to distinguish what can actually be implemented and have value today.

So, how to do it?

We recommend a consultative approach with the right partner and with a core axis that adds business value, improves processes, and reduces costs.

Generative AI depends on the data you train with.

��ɫ leverages technology and incorporates generative AI in a lens best understood through three main categories:

Technology
Services
��ɫ

In technology, ��ɫ’s AI.NOW division was launched in 2023 after years of research and development with a specific focus on commercializing a solution that helps businesses leverage translation technology while prioritizing data protection and confidentiality. Some key advantages include:

Data Security and Privacy
Compliance Assurance
Customization and Control
Integration Capabilities
Risk Mitigation
Over 50% savings on localization costs

For services, data engineering partners stand out to help enterprises improve the way they interact with generative AI applications. This includes, but is not limited to, prompt engineering, example-based learning, and fine-tuning models to solve specific cases.

In the rapidly evolving landscape of artificial intelligence, the pivotal role of data engineering partners becomes increasingly apparent, particularly in the realm of services. These strategic collaborators serve as indispensable allies for enterprises seeking to enhance their engagement with generative AI applications. With a focus on refining the intricacies of data handling, data engineering partners excel in prompt engineering, leveraging example-based learning methodologies, and meticulously fine-tuning models to address specific use cases.

This collaborative approach not only amplifies the effectiveness of generative AI applications but also empowers enterprises to navigate the complexities of an ever-evolving digital landscape with unparalleled agility and innovation. Finally, our solutions are focused on quickly creating content that is scalable, gaining knowledge in market research, or creating popular multilingual chatbots in any language, based off of knowledge bases, among others.

Some examples from above:

E-learning

Problem: Complexity in content creation

Solution: Leverage training material for automated course outline

Results: 25% lower costs and (turnaround time) TAT

Product Support

Problem: Complexity in question answering in the value chain

Solution: GenAI to answer complex questions based on product information

Results: Increased CSAT and reduced in 25% the teams’ workload

Digital Content

Problem: Cost and TAT for SEO-optimized multilingual content creation

Solution: GenAI combined with SEO data points for optimized creation (with humans in the loop).

Results: Over 50% reduction in costs and TAT

Data Auto-Labeling

Problem: High cost in human labeling

Solution: AI for data labeling and classification

Results: 70% cost reduction

Custom AI ��ɫ

Problem: Low availability and high cost of internal resources

Solution: Dedicated AI teams

Results: Faster time-to-market

In any scenario, we recommend starting with a pilot to assess the pros and cons of generative AI. If it doesn’t work, it’s best to look for another use case. But if there is a clear return on investment (there usually is), we recommend iterating continuously and scaling. It is important to note that, in addition to technology, detecting where people can take AI to the desired human level is key.

Generative AI has the potential to be a powerful tool for innovation and creativity, improving our productivity in the most repetitive tasks and unlocking our initial blank sheet in creative processes. As collaboration gets closer, AI will evolve and be able to solve increasingly complex problems. At ��ɫ, we are committed to the principles of responsible AI. We are flexible on models and hence we can help diverse industries.

For more information, give us a shout!

Mariana Ordonana

Director, Business Development

Technology

Breaking Language Barriers: The Role of Machine Translation in Globalizing Video Content

muna.abdulkader — Mon, 04 Dec 2023 20:18:37 +0000

Breaking Language Barriers: The Role of Machine Translation in Globalizing Video Content muna.abdulkader Mon, 12/04/2023 - 15:18

Blog

In our interconnected world, the power of video content is undeniable. Whether it’s educational content, entertainment, or corporate communications, videos have the potential to reach audiences far and wide. However, one significant challenge stands in the way of truly globalizing this content: language barriers. This is where machine translation steps in as a game-changer, offering a transformative solution to make video content accessible and engaging for diverse audiences worldwide.

What Is Machine Translation?

Machine translation is a computational process that uses artificial intelligence to translate text or speech from one language into another automatically. It leverages complex algorithms, statistical models, and neural networks to analyze the structure and context of the source text and generate an accurate translation in the target language. While it’s a powerful tool for quickly converting content across languages, it’s not without its limitations, such as nuances, cultural context, and idiomatic expressions. Nonetheless, machine translation has become an invaluable tool for breaking down language barriers, facilitating communication, and expanding global access to information and content.

How Is Machine Translation Involved in Making Videos Globally Accessible?

Opens Doors to Global Audiences

One of the primary benefits of machine translation in the context of video content is its ability to alleviate language barriers and open doors to a global audience. By providing accurate and contextually relevant translations, machine translation ensures that your content is accessible to viewers from different linguistic backgrounds. This inclusivity fosters a sense of connection and expands the reach of your message beyond borders.

Makes Inclusive and Accessible Viewing Possible Through Subtitles

Imagine a scenario where your video content is not confined to a single language. Machine translation allows for quick and effective creation of multilingual subtitles, making your videos accessible to a wider audience. This is especially crucial for individuals with hearing impairments or those who may not be proficient in the language of the original content. Multilingual subtitles enhance the viewing experience, making your content more inclusive and engaging.

Localizes Video Content

Machine translation goes beyond mere word-for-word conversion—it considers local nuances, idioms, and cultural contexts. This process, known as localization, allows content creators to tailor their videos to specific regions, ensuring that the content resonates with local tastes and preferences. This customization not only enhances the relevance of your content, it demonstrates a commitment to understanding and respecting other cultures.

Provides a Quick Turnaround, Reducing Costs and Improving Time Efficiency

Machine translation offers an efficient and cost-effective alternative to traditional translation processes, allowing content creators to release multilingual versions of their videos quickly. It enables the swift rollout of content in multiple languages, ultimately reducing time-to-market. This, in turn, gives corporations the freedom to reallocate their resources to other critical areas.

Conclusion: The Power of Globalizing Video Content

The globalization of video content is no longer a distant dream but a tangible reality with the assistance of machine translation. By breaking down language barriers, enhancing accessibility, and fostering global engagement, machine translation opens a world of possibilities for content creators and viewers alike.

GlobalLink inMOTION integrates ��ɫ’s machine translation technology, providing the highest available standard of machine translation. Using machine translation for subtitles in GlobalLink inMOTION is cost- and time-effective.

The inMOTION Team

Technology

A Recap of GlobalLink Next: Harnessing the Power of Generative AI and Multilingual Content

muna.abdulkader — Tue, 24 Oct 2023 15:11:16 +0000

A Recap of GlobalLink Next: Harnessing the Power of Generative AI and Multilingual Content muna.abdulkader Tue, 10/24/2023 - 11:11

Blog

��ɫ’s premier annual tech-user conference, GlobalLink NEXT Americas, unfolded in September. This special event experienced a significant shift as it found its home at our headquarters in the vibrant city of New York. Over the course of two packed days, attendees were treated to a rich program encompassing innovation spotlights, enlightening case studies, engaging product workshops, and diverse breakout sessions. In the wake of this inspiring gathering, we are thrilled to share some of the most compelling insights and conversations from a wide array of industries.

Among the numerous thought-provoking topics explored during the event, two pivotal themes emerged: the game-changing potential of generative AI and the essential focus on meeting the needs of multicultural communities.

Generative AI: Fuelling Content Productivity

Generative AI, where to begin… Let’s start off with the idea that when used strategically, it can be a game-changer for content creation. Throughout numerous speaker sessions, breakouts, networking opportunities, and more, we explored how generative AI can boost productivity and streamline content development. For those who missed it, our TPT Digital team hosted an insightful webinar on October 18, offering a deep dive into this ground-breaking technology. Watch it HERE.

Multicultural Communities: A Glimpse into the Future

During the conference, M&T Bank and PNC Bank presented a compelling projection: By 2045, multicultural communities are expected to constitute 55% of the US population. This statistic underscores the necessity for financial institutions to pursue the development of language access programs that cater to the customer journey in various languages. The key takeaway was the importance of adopting an iterative approach when designing, implementing, monitoring, and continuously improving these language-access programs.

Tailored Content for Unique Campaigns

Our clients often seek a bespoke approach to content production. In addition to TPT Digital's consulting and search marketing services, our ContentLabs team specializes in crafting event- or campaign-specific content. The conference showcased examples of content that effectively engage diverse audiences, highlighting the power of personalized messaging.

Seamless Bridging of Global and Local Markets

Global marketing requires a delicate balance between global consistency and local relevance. Our team assists in this endeavour by adapting global master content for local markets and media channels. We work closely with your local teams, creative agencies, media agencies, and more to ensure your message resonates with your target audience.

Security and Efficiency with GlobalLink

For our clients, security and efficiency are paramount. GlobalLink – ��ɫ’s proprietary modular technology underpinning any variety of our client relationships – offers a solution by allowing you to leverage existing tools and language assets, including robust platform integrations and cutting-edge AI-machine translation.

GlobalLink Next provided a platform to explore the transformative potential of generative AI and the necessity of multicultural marketing strategies. The future of marketing lies in harnessing these innovations and crafting content that resonates with diverse audiences. If you missed our conference, don't worry – you can still catch up by exploring the resources shared during the event. If you would like more information, reach out to us today! Join us in shaping the future of marketing.

Angus Ulyate

Regional Director

Technology

Op Ed: AI Was Coming For My Translation Business, So I Adapted

jpressman — Mon, 23 Oct 2023 20:18:53 +0000

Op Ed: AI Was Coming For My Translation Business, So I Adapted jpressman Mon, 10/23/2023 - 16:18

Blog

Depending on who you ask, GenAI will either usher in a brilliant new era of progress, discovery and achievement, or it will render countless jobs obsolete and erode fundamental individual liberties. But as is true in all highly charged debates, the truth lies in the middle.

While GenAI certainly poses risks if used irresponsibly, it would be good to recall that it wasn't long ago that people leveled the same charges against home computers and the internet.

At its most basic level, GenAI is artificial intelligence capable of creating text, images or other media using models that learn patterns and structure of their input data, then generate new data with similar characteristics. Though still in its infancy, there is no denying that this technological tool is a disruptive force. However, the notion that machines will generate new great works of literature, original reporting for news stories or cogent, well-argued legal briefs, is highly unlikely.

As the founder and CEO of one of the world's largest providers of language and translation services, the question for us quickly became, how do we deploy this technology ethically while still maximizing its very real potential?

In the past decade, our business model has inexorably changed, from technology-enabled, human-led translations, to "human in the loop" AI-driven translations — translations done by AI, then edited for grammar and cultural competency by a person. To that end, our AI is constantly learning from our linguists and adjusting its models accordingly.

Since deploying this technology, I have been asked frequently about our team's level of concern for whether or not this could be the beginning of the end for not just my business, but our entire industry. And though it may surprise you to hear, our answer is unequivocally: no.

While the disruptive force of AI could indeed render some businesses obsolete, it is my unwavering belief that those forces can be mitigated by embracing the change and evolving with it. And embrace it we have, investing millions into developing our own AI models, as well as creating a new division tasked solely with gathering and cataloging the raw materials for GenAI model generation. In fact, the key themes echoed throughout the recent GlobalLink NEXT User Conference in New York, which my company hosts, was that we need to embrace the fact that the world of GenAI multilingual content is upon us.

As executives, civic leaders and the broader tech industry are all learning firsthand and in real time, GenAI is likely neither a catapult to the next Renaissance nor the first chapter in a real-life Terminator story. So for now, GenAI won't kill you, but it will kill your business if you don't adapt.

Phil Shawe

President and CEO of ��ɫ

Technology