Category: Technology & CAT Tools

An Insider’s Guide to Solutions Architects: The Key to Long-Term Client Success
19/03/2025

An Insider’s Guide to Solutions Architects: The Key to Long-Term Client Success

Posted on | by Litzaqueline Briceño | Leave a Comment on An Insider’s Guide to Solutions Architects: The Key to Long-Term Client Success
An Insider’s Guide to Solutions Architects: The Key to Long-Term Client Success

Localization projects are intricate in that they require a blend of linguistic expertise, technical know-how, and strategic vision. At the heart of any successful localization effort lies a pivotal role: the solutions architect (SA). An SA’s involvement goes far beyond initial setups, as Terra CEO Marina Ilari explains. “SAs play a very important role in building and maintaining long-term client relationships. They act as proactive, trusted partners who are committed our clients’ success.”  

Let’s explore the multifaceted responsibilities of solutions architects and their impact on long-term partnerships.  

Building a Foundation of Trust 

An Insider’s Guide to Solutions Architects: The Key to Long-Term Client Success

Throughout the localization process, trust between a client and its translation team is the cornerstone of a successful partnership. Projects often involve sensitive data and high-stakes outcomes, making it essential for both parties to be willing to build strong relationships from the start. SAs are instrumental in fostering this trust by prioritizing open communication and recognizing each client’s unique needs. 

“Genuine relationships with clients rest on trust and proactive conversations,” says Sara Rodríguez, a solutions architect at Terra. “An SA ensures that clients feel supported from the first day by taking the time to understand their concerns, aspirations, and preferences.” This personalized approach lays the groundwork for collaboration and ensures that clients feel confident throughout the process.  

Tailored Solutions for Every Challenge 

Localization isn’t a one-size-fits-all process. Every client has distinct goals and challenges, and it’s the job of a solutions architect to design workflows that address these nuances. From Translation Management Systems (TMS) to automation tools, SAs leverage a range of technologies to create scalable solutions. 

“We develop strategies to address bottlenecks in workflows, for example, or we’ll integrate technology like CAT tools,” says Sara. “I’ll often be working to streamline processes to meet a client’s business goals like market expansion or regulatory compliance,” she adds. 

By tailoring workflows to meet specific requirements, SAs ensure that translation projects achieve their immediate objectives, while also remaining flexible for any adjustments clients need to make in the future. For instance, by implementing secure TMS systems with role-based access and real-time quality checks, Terra’s SAs have helped clients manage high-volume, time-sensitive projects with confidence in the moment, while ensuring those same systems and checks will remain workable for clients down the line.  

Supporting Growth Through Continuous Optimization 

Delivering results is only the beginning of a solutions architect’s work. As they stay actively involved throughout the lifetime of a project, they provide support and refine processes along the way. This iterative approach not only boosts operational efficiency but also ensures adaptability in industries like gaming or healthcare, where localization needs can evolve rapidly. 

Soledad Coronel, one of our solutions architects, explains, “The goal is to apply industry best practices in design and development, which include design patterns, scalable architecture, and quality standards.” An SA’s commitment keeps workflows robust and adaptable so clients continue to meet their objectives. 

One notable example of effective continuous optimization that we executed at Terra involved a high-volume video game task that required localization into 15 languages under tight deadlines. The SA in charge developed a workflow that featured contextualization tools and automated checks throughout the life of the project, which resulted in our delivering high-quality translations on time.    

Language, Technology, and the Irreplaceable Human Touch 

In today’s localization landscape, technology is indispensable. But even with advances in AI and automation, the human element remains essential to the localization process. SAs know firsthand the subtleties of what human translators bring to the table, and in an increasingly tech-driven world, SAs reinforce the importance of the human touch by leveraging it in the right places. 

An Insider’s Guide to Solutions Architects: The Key to Long-Term Client Success

“Translators and linguists bring cultural nuances and idiomatic accuracy that machines can’t replicate,” says Soledad. “Our role requires us to understand that gap between human linguistic expertise and cutting-edge technical solutions, so we can effectively implement the strengths of both.”  

From automating repetitive tasks to managing the human element of complex workflows, SAs bring clarity and optimal efficiency to every project, all while staying true to the client’s vision.  

“Our work really demands a unique blend of cultural sensitivity, technical expertise, and strategic thinking,” Soledad adds. “And then, beyond understanding those tools, it’s about aligning those them with client objectives to deliver impactful results.” 

Conclusion 

The role of a solutions architect is pivotal to achieving successful and long-term client relationships in localization. By combining technical knowledge, cultural insight, and a client-first approach, SAs help businesses navigate the complexities of global markets with confidence.   

Their work not only addresses immediate project needs, but also lays the foundation for sustainable growth and continued success. For any organization aiming to excel in localization, partnering with a skilled solutions architect is a step toward achieving impactful and lasting results.

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AI Ethics Essentials Key Principles for Responsible Implementation
04/03/2025

AI Ethics Essentials: Key Principles for Responsible Implementation

Posted on | by Litzaqueline Briceño | Leave a Comment on AI Ethics Essentials: Key Principles for Responsible Implementation

As artificial intelligence (AI) tools become a vital part of modern business, it’s easy to view them as a silver bullet for company-wide efficiency, cost savings, and innovation. But, as the saying goes, with great power comes great responsibility. No matter how a company employs AI, using it ethically should not be a choice, but an essential practice to build trust, ensure fairness, and protect the people who use these tools or are impacted by them. 

Following sound ethical principles for AI, such as these laid out by the European Union, can make these sorts of positive differences right from the start. From there, organizations should take the time to periodically reevaluate their AI tools to ensure they continue to align with their values and safeguard their users. Here, we’ll cover seven fundamental concepts that every company should consider before implementing AI solutions. 

1. Transparency in The Usage of AI Solutions 

Transparency is the foundation of ethical AI. When team members or clients interact with AI solutions, they should be able to easily follow how the tool reaches its conclusions or outputs. It is recommended that all processes involving the use of AI be identifiable and documented for future analyses and management. 

2. Support for Human Agency 

AI should empower, not replace, human decision-makers. Keeping human power at the fore ensures that these tools act as partners to human expertise, rather than substitutes. AI-driven systems can offer recommendations and insights, but as the European Union’s AI guidelines note, “The right of end users not to be subject to a decision based solely on automated processing should be enforced.” Following this approach ensures that technology enhances, rather than diminishes, the human touch on the job at hand. 

3. Reliability and Safety 

Reliability and safety are essential pillars of ethical AI. Before implementation, it is crucial to verify that AI works as intended and performs consistently over time. Reliable usage of AI technology is especially important in areas with high-stakes outcomes like healthcare or pharmaceuticals, in which even small errors can have significant consequences. 

4. Diversity, Non-discrimination & Fairness 

An ethical approach to AI usage respects diversity and prioritizes inclusion, which means it must be tested carefully for unintended biases and further evaluated to ensure it serves a wide range of users equitably. While AI systems aren’t inherently designed with inclusivity in mind, using them responsibly can support diverse populations and reinforce a company’s commitment to fairness. The goal should be to create or leverage tools that acknowledge and adapt to the unique backgrounds of all users.  

5. Privacy Protection and Data Security 

Data security is paramount in ethical AI use, as the technology relies on vast amounts of information. For clients, prioritizing their privacy means ensuring their sensitive or proprietary information is securely managed across platforms and departments. To protect client data, businesses should choose AI providers with robust security measures and transparent data practices that safeguard information at every stage. 

6. Societal & Environmental Wellbeing 

In an age of climate awareness, it is also essential to consider AI’s environmental footprint. AI can be energy-intensive, so opting for energy-efficient solutions internally or partnering with external providers with green practices is important. Environmentally responsible AI solutions are those that help solve business challenges in a sustainable way that respects our planet’s resources.  

7. Accountability 

Accountability ensures that companies remain responsible for their AI tools’ actions. Having clear processes to audit and evaluate AI decisions is essential. This way, businesses can address issues, learn from them, and continue to improve. Accountability in AI use demonstrates to users and stakeholders alike that you take responsibility for your actions. 

A Final Thought for Businesses 

Ethical AI implementation is not just about staying ahead in innovation; it’s about doing so in a way that upholds trust, transparency, and inclusivity. By following these principles, you will be well-positioned to implement AI responsibly, thus making a positive impact on both your clients and society as a whole. For industries like translation, healthcare or pharmaceuticals in which data security and cultural sensitivity are paramount, adhering to ethical AI principles helps deliver not only reliable results, but also peace of mind. 

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How to Navigate Ethical Concerns in AI
11/02/2025

How to Navigate Ethical Concerns in AI

Posted on | by Jacqueline De Marco | Leave a Comment on How to Navigate Ethical Concerns in AI

The use of any technological tool requires a full understanding of its functioning and potential limitations and risks. In the translation industry, irresponsible or unethical use of Artificial Intelligence (AI) poses significant threats, which can lead to serious consequences for businesses, communities, and language integrity itself. In this blog post we will address some key ethical concerns associated with the use of AI and provide practical steps to ensure its responsible use. 

Ethical Concerns 

There are a few different ethical concerns you will want to keep top of mind before using AI.  

1. Copyright and Ownership Concerns 

To properly train generative AI, you need a large amount of data. The source of that data is often public postings on the internet. This can lead to the inclusion of copyrighted material without proper authorization. The legal situation around the use of generative AIs is complex and often undefined. There is a significant risk of inadvertently using AI-generated content that may contain copyrighted elements, which could lead to legal complications. Therefore, it’s crucial to check the output for its origin and ensure it does not violate existing copyrights. 

2. Bias 

Generative AI models are trained on human-created content, which often includes inherent biases. As a result, AI sometimes produces biased, stereotyped, or even harmful outputs. While developers are working to mitigate these issues, achieving unbiased results is a challenging endeavor that may take years to perfect. Unlike humans, machines struggle to understand nuanced contexts, which makes it difficult for them to consistently produce fair and unbiased content. 

3. Confidentiality 

Given that AIs are trained on vast datasets, privacy concerns naturally arise. Issues like data breaches, unauthorized access, and improper collection, storage, and use of information are significant risks. Many AI systems are public-facing tools accessible to anyone without restrictions, which poses a considerable threat to confidentiality. Information inputted into these systems can potentially be used to generate responses to future queries, risking exposure of sensitive data. 

Practical Steps for Ensuring Ethical AI Use 

If you intend to use AI, these are some steps you can take to do so ethically.  

1. Check that AI Tools Adhere to Ethical Standards 

Before adopting any AI tool, ensure that it was developed with the four pillars of ethical AI in mind—privacy and security, transparency, fairness, and accountability. These pillars can guide your decision-making process and help you choose tools that align with ethical standards. 

2. Verify Data Sources 

AI tools often present information with equal certainty, regardless of its accuracy. It’s essential to fact-check their output for truthfulness and sound reasoning. You also need to confirm the content is ethically sourced and does not infringe on copyrights. Human oversight is crucial to avoid liability claims and ensure content accuracy. 

3. Develop and Update Company Policies 

Create and regularly update company policies regarding the use of AI in the workplace. Train employees on these policies to ensure they understand the ethical considerations and potential risks associated with AI use. Provide guidance on mitigating issues such as misinformation, privacy breaches, ethical and legal challenges, and bias. 

4. Review AI Outputs 

Review AI-generated content to ensure it respects cultural sensitivities and norms. Be aware of regional differences and gender sensitivities to avoid producing content that could be offensive or inappropriate. 

5. Consider Closed AI Systems 

For handling sensitive materials or information, consider using a closed AI system that is trained solely on your company’s data. This approach prevents your input from being used in public-facing AI models, helping to safeguard your confidential information. 

6. Maintain Transparency with Clients

Transparency is key to building trust with your clients and stakeholders. Keep them informed about the AI tools you use and the measures you take to ensure ethical practices. Being open about your use of AI and your commitment to ethical standards will enhance your credibility. 

The Takeaway 

The ethical concerns surrounding AI are critical issues that businesses must navigate as they integrate these technologies. It is paramount to ensure a solid and trustworthy AI-human collaboration, maintaining ethical standards to protect your business, clients, and community. Responsible AI use not only prevents potential legal and ethical pitfalls but also strengthens your reputation and trustworthiness in the industry. 

By understanding and addressing these ethical concerns, companies can harness the benefits of AI while minimizing risks and fostering a more responsible technological future. 

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The New Role of Translators in the AI Era
28/01/2025

The New Role of Translators in the AI Era

Posted on | by Jacqueline De Marco | Leave a Comment on The New Role of Translators in the AI Era

In recent years, the rapid advancements in artificial intelligence (AI) have significantly transformed a variety of industries. From automating repetitive tasks to streamlining complex workflows, its impact is broad and undeniable. The translation industry, in particular, felt this shift as AI-powered tools begin to shape how translation services are managed and executed. While these innovations are revolutionizing the field, they are also transforming the role of translators, boosting productivity and creating a need for new skills and expertise. 

The Evolution of the Translator’s Role 

Translators have always adapted to technological changes, from the rise of computer-assisted translation (CAT) tools and translation memories two decades ago to the more recent integration of machine translation systems. Now, AI has entered the scene, promising to streamline translation processes further. But rather than replacing human translators, AI is becoming part of an evolving toolkit that enhances the human touch. 

Today, translators are shifting away from purely linguistic tasks and are now managing AI-driven tools that combine translation memory, machine translation, and terminology databases. These advanced platforms enable translators to work more efficiently, maintaining consistency across large-scale projects. Instead of focusing on line-by-line translation, professionals are increasingly tasked with refining and contextualizing AI-generated content, especially in areas where AI struggles to capture cultural nuances and idiomatic expressions. 

While this new technology can handle the bulk of a translation, the human touch remains essential in ensuring the final product resonates with local audiences. This dynamic underscores the emerging partnership between AI and human translators, where technology augments human capabilities rather than replacing them entirely. 

A Radical Shift in Skills 

As the industry transforms, so too must the skill set of professional translators. Familiarity with AI and machine learning is becoming increasingly important, and translators are now expected to understand how to train and manage AI translation models. In addition to linguistic expertise, they must develop technical skills, ranging from using AI tools to analyzing data that informs the translation process. 

Moreover, the human element of translation remains crucial. Cultural sensitivity, deep contextual understanding, and the ability to adapt content for specific audiences are skills that machines cannot yet master. Translators who enhance their proficiency in these areas, along with the technical aspects of AI, will find themselves better positioned to thrive in this new landscape. 

Adapting to Change: A Necessity for Translators 

In a rapidly evolving industry, adapting to new technologies is vital. Those hesitant to embrace these innovations may find themselves falling behind as AI continues to revolutionize workflows. Conversely, translators who engage in ongoing professional development and learn how to integrate AI into their processes can increase their value to clients and extend their capabilities. 

Embracing change allows translators to not only maintain their place in the industry but also enhance their work quality and expand the scope of their services. Those who adapt will emerge as skilled professionals capable of balancing technology with the irreplaceable human touch. 

The Takeaway 

The world of translation is evolving quickly, but rather than viewing AI as a threat, it should be seen as an opportunity for growth. Human translators will always be essential in providing the cultural and contextual knowledge that machines cannot replicate.

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An Insider’s Guide to the Role of a Solutions Architect
21/01/2025

An Insider’s Guide to the Role of a Solutions Architect

Posted on | by Litzaqueline Briceño | Leave a Comment on An Insider’s Guide to the Role of a Solutions Architect

In the language industry, the role of a solutions architect (SA) serves as a bridge between innovative technology and the specific, nuanced needs of clients seeking localization solutions. This role differs from SAs in IT, where the focus might rest solely on system design and technical integration. In localization, SAs must grasp the intricacies of multilingual workflows and cultural contexts to ensure their work is not only accurate, but also culturally relevant. 

Sara Rodríguez, one of our solutions architects, describes her job as “an essential link between technological innovation and individual client requirements” in the language industry. Indeed, Terra’s SAs must extend themselves beyond the traditional scope of an IT role because their work calls for close collaboration with a broad range of specialists. Solutions Architect Soledad Coronel notes that for any given project, she’ll find herself in “intensive communication with linguists, translators, and localization experts,” meaning Terra’s SAs are constantly extending themselves beyond the scope of what many would consider traditional for an IT team member.

The Core Responsibilities of Solutions Architects 

Localization SAs design workflows, oversee these technologies, and ensure linguistic quality, making sure to balance both the technical and cultural considerations of any project. They handle everything from selecting translation management tools to automating workflows that streamline processes, all while upholding linguistic integrity. 

As Sara explains, “We build out customized solutions to optimize localization processes. We want to ensure that linguistic accuracy is preserved, even as we’re also focusing on maintaining technical fluency in file formats, translation tools, and automation systems.” Soledad adds that the work of the SA is to always put the client first. “Client satisfaction is paramount. Beyond any technical performance, we’re focusing on the linguistic and cultural quality of the translated content to ensure it meets client expectations.”

A Day in the Life of a Solutions Architect 

The daily work of an SA in the language industry is a combination of technical problem-solving and close collaboration with various teams to meet client needs. They start by analyzing client requirements, which can range from complex project specifications to quality benchmarks. 

“Our day-to-day involves managing multiple projects, customizing workflows, and adapting technical tools to meet unique client needs,” says Sara. “We balance technical demands with cultural considerations to ensure that each localization project resonates with its target audience.” This involves ongoing collaboration with project managers, linguists, and translators to monitor progress, troubleshoot issues through testing phases, and ensure the highest linguistic quality. 

The role also involves constant learning and adapting, which Soledad explains is an essential part of the process. “With evolving client demands and new tools emerging, we need to stay updated, evaluate the latest technologies, and think critically about how each one can add value to our projects.”

Key Skills and Knowledge Required for Success 

Success as a language-industry solutions architect requires a unique blend of technical, linguistic, and project management skills. A solid grasp of Translation Management Systems (TMS) and automation tools is essential, along with a familiarity with the distinct needs of the industry they’re serving—whether it’s video games, legal, medical, or another field. 

“A solutions architect has to be technically proficient and culturally attuned at the same time,” says Soledad. This balance ensures that localization projects are adapted to meet technical standards while aligning with the cultural nuances of the target audience. 

Moreover, in-depth knowledge of localization tools and multilingual content workflows is necessary to drive efficiency. SAs must also possess strong communication and problem-solving skills so they can facilitate smooth collaboration across teams and ensure that each solution integrates human expertise with advanced technologies.

Conclusion 

Solutions architects bring together the technical and cultural elements of localization as they design tailored solutions that align with both their client’s vision and the technical requirements of the process. By fostering strong relationships through personalized solutions and clear communication, they play a key role in helping businesses reach audiences meaningfully, effectively, and efficiently, on a global scale. 

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The Value of Human Expertise in a Technology-Driven World
14/01/2025

The Value of Human Expertise in a Technology-Driven World

Posted on | by Litzaqueline Briceño | Leave a Comment on The Value of Human Expertise in a Technology-Driven World

Rapid advancements in technology, particularly in AI, are shaking the foundations of nearly every sector. In the language industry, AI is transforming how language service providers approach projects and deliver value. And while machine translation tools have become increasingly reliable in recent years, providing more accurate and fluent translations, human intervention is still essential in evaluating the usefulness of these technologies, integrating them into workflows and addressing their blind spots to achieve top-notch results.

The Value of Human Expertise in a Technology-Driven World - Belén Agulló

At Terra, CEO Marina Ilari and Executive Consultant of Innovation Belén Agulló García work in close collaboration with the entire team to ensure that technology is leveraged to enhance, not replace, the role that humans play in crafting tailored texts.  

“We embrace technological progress, but never at the expense of the personal stories, cultural awareness and creativity that we hold dear and that are central to shaping content that resonates with readers,” explained Belén. 

Striking a balance between technology and human expertise has been a core focus in Terra’s daily operations. Read on to find out how we draw the best from both worlds. 

Centering Human Expertise

The Value of Human Expertise in a Technology-Driven World - Marina Illari

“While we engage with advanced technologies, we aspire to promote an atmosphere that values the beauty of the human element,” Marina said. 

Technology accelerates workflows, but it’s our team’s creativity, cultural sensitivity and human insight that breathe life into every project and ensure that our localized content strikes the right chord with readers. Artificial Intelligence (AI) often reflects biases present in the data they are trained on and lacks the deep understanding of cultural context and linguistic subtitles needed for truly effective communication.  Our expert linguists leverage the awesome capabilities of technologies while also drawing on all their unique human knowledge to provide an unmatched level of quality.

Innovating with Integrity 

One clear example of innovation with integrity is our approach to using AI-assisted translation tools. While the potential for efficiency is tremendous, we have an ethical responsibility to the linguists and other language specialists who collaborate with us, so they decide when and how to utilize AI-driven solutions. By working closely with them before deploying any technology in a given workflow, we can make sure that the solution meets their expectations and is an actual aid—and not obstacle—in creating the best possible translations. When our experts decide to use these tools, they thoroughly review the AI-generated content to make sure that it matches cultural and contextual expectations. 

At Terra, our commitment to ethical technology has created a culture of trust and responsibility. By intentionally considering how the technology used impacts each collaborator, client, and community we serve, we’ve created an organization that prioritizes human values. This approach has not only enhanced the quality of our work by deliberately safeguarding human insight but has also strengthened client trust. Our clients know that while we use cutting-edge tools, the human touch that makes our service exceptional is never overlooked.

Fostering Trust and Responsibility

A human-centered approach to linguistic tasks fosters ongoing process evaluation and enriches the quality of the work we do. Each project is carefully crafted by expert linguists, who pour their cultural, emotional, and experiential insights into their work. In the localization of video game content, for example, our experts draw on their rich knowledge of the target language and culture to finely tune the game, so it resonates with the audience while remaining true to the original. This approach leads to high client satisfaction and certainty that the crafted content fits different market ecosystems while effectively capturing the brand’s voice.  

At the same time, guaranteeing that our final output is not biased by AI and represents the values of diversity and inclusion we passionately support and defend is a priority the team never compromises on. Human sensibilities are constantly changing, and by putting people at the center of our work, we ensure that localized versions are crafted to reflect the current values of each society.

Conclusion 

While technology, particularly AI, continues to transform the T&I industry, the role of human expertise is more valuable than ever. At Terra, creativity, judgment, and ethical considerations are not just complementary to technology, they are essential. As we move forward, it’s clear that human value remains at the heart of delivering meaningful, quality results that technology alone simply cannot achieve.

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Neural Machine Translation vs Large Language Models
26/11/2024

Neural Machine Translation vs Large Language Models

Posted on | by Jacqueline De Marco | Leave a Comment on Neural Machine Translation vs Large Language Models

Artificial Intelligence (AI)-powered tools have become integral in various industries, and their influence is becoming more and more prominent in translation and localization. Two notable AI-driven technologies in this field are Neural Machine Translation (NMT) and Large Language Models (LLMs). While both are powerful tools, understanding their differences is essential as their applications, underlying architectures, and functionalities have distinct strengths and weaknesses. This knowledge helps professionals choose the right tool for their specific needs, optimizing efficiency and accuracy in language-related tasks. 

What is Neural Machine Translation and How Does it Work? 

Neural Machine Translation (NMT) is an advanced AI technology designed to automatically translate text from one language to another. Unlike traditional translation methods that rely on predefined rules, NMT employs a neural network—a computer program that improves translation accuracy by considering the entire text’s context and learning from vast amounts of example data. 

NMT systems typically have two main components—one that reads and understands the original text and another that generates the translated text in the target language. This process mimics the human brain’s function, using interconnected nodes that enable the model to learn and enhance its capabilities over time. The ability of NMT systems to learn from context allows them to provide more fluent and coherent translations compared to older translation methods. 

What are Large Language Models and How Do They Work? 

Large Language Models (LLMs) are sophisticated AI systems designed to understand and generate human-like text. They are trained on vast datasets of text, which enables them to perform a wide range of language-related tasks beyond translation, such as text generation, summarization, and conversational AI. 

LLMs use deep learning techniques with multiple layers of neural networks. Each layer refines the model’s understanding of the data, employing an attention mechanism that focuses on specific parts of the input data. This process allows LLMs to generate text by predicting the next word in a sequence based on the input they receive, making them versatile in generating coherent and contextually relevant text. 

Pros and Cons of NMT and LLMs 

No technology is perfect, so let’s take a look at both the advantages and disadvantages of NMT and LLMs.  

Pros of NMT: 

  1. Improved accuracy: NMT systems provide more accurate translations by considering entire sentences or paragraphs, reducing errors common in traditional methods and resulting in more natural and coherent translations. 
  1. Customization: Users can fine-tune NMT outputs by incorporating specific terminology databases, brand-specific glossaries, and other data sources, further enhancing the relevance and correctness of translations. 
  1. Integration versatility: NMT can be easily integrated into various software applications via APIs and SDKs and supports numerous content formats, including CAT (Computer-Assisted Translation) tools. 
  1. Continuous improvement: NMT systems constantly evolve by learning from new data, adapting, and improving translation quality over time. 

Cons of NMT: 

  1. Lack of cultural awareness: Despite considering context, NMT can still produce inaccurate translations and lacks the ability to make nuanced decisions based on cultural contexts or idiomatic expressions. 
  1. Data dependency: NMT requires vast amounts of data for training purposes, which can be challenging for less common languages or specialized fields. This can lead to less accurate translations for rare language pairs or niche terminology. 
  1. Bias in outputs: Like all AI, NMT systems can inherit biases from their training data, leading to biased outputs in translation regarding gender, occupation, and other sociocultural factors. 

Pros of LLMs: 

  1. Versatility: LLMs can handle a broad spectrum of language-related tasks beyond translation, including text generation, summarization, and dialogue systems. 
  1. Human-like text generation: LLMs can generate human-like text, making them highly valuable for content creation and applications requiring natural language understanding. 
  1. Customization through fine-tuning: Companies can tailor LLMs to align with specific needs and objectives through additional training and fine-tuning, enhancing their utility across various applications. 

Cons of LLMs: 

  1. Lack of reasoning: LLMs often generate text based on probabilistic guesses rather than genuine reasoning, which can lead to inaccuracies or irrelevant responses. 
  1. Privacy and data concerns: The data usage and privacy practices involved in training some LLMs are under scrutiny, raising ethical and legal concerns about data privacy. 
  1. Susceptibility to manipulation: LLMs can be manipulated to generate fake or misleading content, posing risks, especially in sensitive applications like social media and news. 

The Takeaway 

NMT and LLMs represent significant advancements in artificial intelligence, revolutionizing how we approach translation and other language-related tasks. While these tools offer substantial benefits, it’s crucial to view them as complementary to human expertise, particularly in ensuring accuracy, cultural sensitivity, and nuanced understanding. Professionals should leverage these technologies to enhance their workflows while remaining vigilant to their limitations and the importance of human oversight.

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Translation and Business Management Systems Adding Value, Subtracting Risk
04/06/2024

Translation and Business Management Systems: Adding Value, Subtracting Risk

Posted on | by Marisol Pérez Laglaive | Leave a Comment on Translation and Business Management Systems: Adding Value, Subtracting Risk

Computer Assisted Translation (CAT) tools are decisive within localization workflows. Not only do they assist linguists in their work with multiple features, such as translation memories (TMs), automation rules, built-in glossaries, and more. Many also include tools that help project managers (PMs) and vendor managers (VMs) with their daily tasks, offering reporting, allocation tools, and workflow management. Software solutions that have both functions are called Translation Management Systems (TMSs), and here we’ll address how they can enhance localization processes. Furthermore, we’ll discuss the main difference between TMSs and another type of tool, Business Management Systems (BMSs), which are often mistaken for one another.  

TMS support  

A TMS helps the project management team automate and customize repetitive processes. For example, if they manage a large number of projects with identical requirements daily, TMSs offer templates that can save time and clicks. Furthermore, TMSs allow tracking and reporting. Reports are crucial because they inform stakeholders within a project about the exact volume and scope. Without data from reports, planning or scheduling is not possible. Some TMSs allow tracking other variables, such as time spent on editing, costs, and profitability.   

Most TMSs include powerful quality assurance tools and some even allow storing localization resources, like TMs, references, or term bases (TB). This is a big deal for project management purposes since it offers a built-in quality management solution for workflows while also offering data storage. Repositories are more common in cloud-based solutions and they help maintain resources classified and organized.   

A TMS can also feature vendor management solutions. This includes elaborating databases of vendors with detailed profiles where VMs and PMs can search and filter according to their needs.   

These are just a few of the ways how TMSs can support localization management teams. There are a wide variety of TMSs in the market aimed at different needs, products, and processes, that offer solutions for specific workflows.  

Manage businesses  

In the localization landscape, another type of software is a must when users are in need of organizing workflows and operations. When a business scales up and its processes grow and become more complex, BMSs come to their aid. Language Service Providers (LSPs) benefit from BMSs because these tools efficiently manage and monitor business operations, mainly by performing the following functions:  

  • Comprehensive workflow and project management  
  • Allocating and coordinating multiple vendors  
  • Creating and storing databases of vendors and clients  
  • Reporting and tracking multiple variables, such as profitability, services, types of projects, etc. 
  • Invoicing  
  • Project and vendor rating  

The main difference between a BMS and a TMS is that the latter also includes CAT tool functionalities, while the former doesn’t. Some BMSs are helpful across industries, yet some are customized specifically for localization workflows. Some companies even develop customized BMSs, like TerraSoft.  

Drawing the line  

While always useful and handy, spreadsheets fall short when businesses thrive and their data volume grows. TMSs and BMSs go beyond offering solutions for data storing, workflow tracking, or reporting. Their features also add value to the workflows LSPs manage and reduce potential risks. Counting on TMSs and BMSs ensures cross-checking of data, consistency across projects and time, data management, and thorough monitoring. 

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Industries that VR & AR Technology Could Transform With the Aid of Localization
14/11/2023

Industries that VR & AR Technology Could Transform With the Aid of Localization

Posted on | by Jacqueline De Marco | Leave a Comment on Industries that VR & AR Technology Could Transform With the Aid of Localization

Virtual reality (VR) and augmented reality (AR) are getting a lot of buzz these days and for good reason. This exciting technology can be applied to many industries. Because of its potential and VR headset adoption rate, more industries are taking advantage of this technology’s benefits than ever before.

While many people are interested in the potential applications of AR and VR in the entertainment space since that industry is so consumer centric, we want to take a look at the other types of companies that stand to benefit from AR and VR technology and how localization can help aid the adoption of both. Here are a few applications to keep an eye on.

Healthcare & Mental Health

The healthcare industry is arguably one of the most exciting industries for VR to make an impact on. From improving surgical efficiency to simulating health conditions so doctors can have more empathy to helping patients decrease pain, VR has the potential to majorly improve the healthcare industry. There are also advances being made in the mental health space thanks to Virtual Reality Experience, which is a treatment that is showing promising results in having positive effects on patients and providing a calming effect on patients’ minds.

Education

Education tends to be slow at adapting to new technologies because of how bureaucratic their acquisition processes can be, but even so, some institutions are taking notice and venturing into the space. Because VR is attractive to young students, it is quickly becoming an integral part of field trips, educational games, and other learning experiences.

As students progress and pursue higher education, VR can also make an impact. For example, medical students can use VR to simulate surgeries so they can learn and practice in a safe environment. When using VR, students can make mistakes that they can learn from without having to worry about the very dangerous results that could occur if they made mistakes on a real patient while learning.

Not to mention, VR is really making a splash in the field of e-learning, which can benefit students of all ages.

A great example of how AR is contributing in education environments is the medicine program at Case Western Reserve University. They are able to project an image of the human body that they can interact with through the use of HoloLens glasses.

Employee Training & Recruitment

Businesses who are looking to improve their recruitment and training processes can find that VR can help them make progress. When recruiting new employees, they can use VR to assess an applicant’s skills, without requiring them to come to an office in-person to interview. With more and more companies hiring remotely, VR can bridge a gap that would be difficult to fill otherwise. Once they hire an employee, they can also use VR to train them in a safe environment. This is especially helpful for very hands-on roles where technical training is required and where safety issues are a concern.

Retail & Sales

From training to the sales floor, retailers can benefit from embracing VR and AR. For example, through VR, employees can interact with products and can learn about them in a way that is superior to just reading about them. AR can also be used to show customers what a product would look like in their home, making it easier for them to visualize how a potential purchase would impact their daily lives.

How Localization Comes Into Play

The key to VR’s success in all these different industries and spaces is the immersive experience this technology provides. That being said, for it to be successful, this immersion has to be accompanied by “localized worlds”, where all the speech audio is in a language the user understands. If visual cues or prompts include text, these elements also need to be translated. Otherwise, the user will find herself in a world they can’t make sense of, the immersive experience will be shattered, and the ultimate goal (whether it’s learning a skill, healing trauma, or just disconnecting from the real world and getting some entertainment) won’t be achieved.

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Do CAT Tools Have a B-Side 
24/10/2023

Do CAT Tools Have a B-Side? 

Posted on | by Jacqueline De Marco | Leave a Comment on Do CAT Tools Have a B-Side? 

If we wanted to describe the localization landscape, we would certainly talk about languages, communication needs, clients, and vendors. However, it would never be complete without considering the technology that makes localization possible globally, at any time, 365 days a year. Computer Assisted Translation (CAT) tools and Translation Management Systems (TMS) have become powerful assets in the industry, adding value to workflows in many different ways. They automate and manage crucial processes, like payments, vendor information, or allocation, while also providing quality features for translation, such as translation memories, term bases, or quality control tools. 

However, despite their indisputable value, using CAT tools has other implications that need to be taken into account when analyzing localization workflows and projects. 

Reluctance 

Project Managers (PMs) may have to deal with reluctance from some vendors or clients that don’t use CAT tools. Misconceptions about tools being a threat to translators’ jobs are somewhat frequent, or people may wrongly mistake them for auto-translation tools. The use of CAT tools can jeopardize the relationship with the reluctant party, and PMs may need to assess if the tool is a necessary piece of the process or discuss other possible options. 

Training and Specialization 

As useful and productive as they can be, it’s also true that in order to use CAT tools efficiently, users need a certain degree of training. This reduces potential issues and allows users to take the best advantage of all the resources CAT tools offer. In terms of feasible project allocation, PMs teams need solid supplier bases that are trained in translation tools. 

Creativity and Transcreation 

CAT tools are most likely to be inefficient in very creative projects, such as transcreation or localization of products or brands. This is because CAT tools offer a bilingual environment where the source text is displayed in consecutive rows so that users can export a translated text with an identical layout as the source text. But sometimes transcreating a marketing campaign implies changing completely the word order, the amount of text, or even the graphic design of a document or product, so CAT tools won’t be necessarily helpful in these scenarios. 

Natura Brasil.
Natura Argentina.
Big Brain Academy, Nintendo Japan landing page. 
Big Brain Academy, Nintendo Brasil landing page.

Row Focus 

Because of the above-mentioned row-organized work environment, CAT tools can make linguists focus on isolated sentences (rows), and not consider the sentence in its context. Furthermore, propagation of repetitions and 100 percent matches may also pass for approved content, without further review. The isolation of sentences may become an issue for creative or literary texts, where translation is not always straightforward and word and sentence order may even be changed. Yet it’s possible to counter it with specialized translators, thorough in-context reviews, and editing steps. 

Analytical Automation 

Analytical and information-based processes include automation, but this doesn’t imply ignoring the scenarios where frequent workflows or tools may not be the best solution. A broader scope for examining translation projects helps the management team to consider all the options available and choose collaboratively the one that best suits each localization need. 

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