Key Takeaways from LangOps Universe 2021

2021年LangOps世界要点

2021-11-09 09:00 unbabel

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We just wrapped up our exciting LangOps Universe event, which was full of thoughtful conversations with localization and customer support leaders from around the world. During this two-day event we hosted and participated in discussions about everything from ethics in AI, to tackling surges in customer support demands, facing fears to spur success, and everything in between. Below, some of the biggest takeaways from this year’s event. Language blocks your ability to scale It’s no secret that global organizations need to translate product information, training materials, customer support systems, and more to connect with customers around the world. Research released during LangOps Universe unveiled that two-thirds of customers surveyed will switch to a brand that provides them with native language support, making it clear that companies can’t afford not to prioritize language. But language is a tough nut to crack. It’s impossible to (affordably) employ native language speakers within every department of your business to cater to each customer’s unique needs. And it’s especially complex to deal with this issue when you account for surges in demand that occur throughout the year. This is a major roadblock to success for many organizations. But, there’s hope. AI-based innovations are leading the charge to solve this problem. AI is powerful but imperfect AI is changing the way organizations approach translating and localizing content. As Unbabel’s VP of Product Innovation Paulo Dimas put it, “AI is equivalent to electricity” in terms of its ability to disrupt the way our world operates. AI tools allow customer support teams to rapidly analyze keywords and triage urgent customer requests, and instantly translate customer support conversations into a variety of different languages. AI is also supplementing the role of humans — empowering them to take on more complex roles to improve the quality of AI itself. Unbabel CEO Vasco Pedro compared the role of humans to that of a musician. Right now, humans are able to master a single instrument, but with AI supplementing their abilities humans can become the entire symphony. This is especially important as we deal with issues related to bias in AI. Machines aren’t perfect, but humans can teach them to be better. Centralizing Language Operations is key AI also holds the power to centralize the way in which organizations approach translating content across various departments and projects. This centralized approach is called Language Operations (LangOps) and relies on an AI-powered data layer to break down silos and store glossaries, translation memories, and custom machine learnings specific to a brand, that can then be used across an organization. The benefits are clear — it’s a simplified and more cost-effective approach to translations. As Associate Professor of Translation & Localization Management at Middlebury Institute of International Studies Adam Wooten said, “Centralized LangOps should be much more common than it already is.” Careers are changing to accommodate this shift Many of our LangOps Universe attendees were curious how a move toward centralized Language Operations would change the role of translation and localization experts in the future. The biggest takeaway from many of our speakers was that language pros will need to expand their expertise from language to language and technology. The success of Language Operations programs depends on the application of technological tools to power the function of translations across a company. Language experts will take on the role of editor and facilitator, guiding AI tools to properly translate content, accounting for context and cultural nuance. Seeking executive buy-in on Language Operations Many attendees were also curious about how to gain executive buy-in on Language Operations. The consensus from our speakers? Prove its value. The data is already out there. Companies are losing money by supporting multiple department-specific approaches to language translations. Money is wasted on multiple tools that serve duplicate functions. Translation and localization can’t be treated as something that’s attached after the fact to product teams or marketing departments — it must become a centralized function that lives across departments. Thank you to all who attended and participated in LangOps Universe. Keep an eye on our blog for more recaps and takeaways breaking down all of the interesting conversations that took place.
我们刚刚结束了激动人心的LangOps Universe活动,在此期间,来自世界各地的客户纷纷发表了深刻的谈话。在为期两天的活动中,我们主持并参与了有关从 AI 道德到解决客户支持需求激增、面临促进成功的恐惧以及介于两者之间的一切的讨论。 以下是今年活动的一些显著收获。 语言阻碍了你的扩展能力 众所周知,全球组织需要翻译产品信息、培训材料、客户支持系统等,以便与世界各地的客户建立联系。 在 LangOps Universe 期间发布的研究表明,接受调查的三分之二的客户将转向为他们提供母语支持的品牌,这清楚地表明公司不能不优先考虑语言。 但语言是一个难以破解的难题。 不可能(以经济实惠的方式)在您业务的每个部门内雇用母语人士来满足每个客户的独特需求。 当您考虑到全年发生的需求激增时,处理这个问题尤其复杂。 这是许多组织成功的主要障碍。 但是,有希望。 基于人工智能的创新正在引领解决这个问题。 人工智能虽强大,但并不完美 人工智能正在改变组织翻译和本地化内容的方式。 正如 Unbabel 的产品创新副总裁 Paulo Dimas 所说,“人工智能相当于电力”,因为它有能力颠覆我们世界的运作方式。 AI 工具允许客户支持团队快速分析关键字并分类紧急客户请求,并立即将客户支持对话翻译成各种不同的语言。 人工智能还补充了人类的角色——使他们能够承担更复杂的角色,以提高人工智能本身的质量。 Unbabel 首席执行官 Vasco Pedro 将人类的角色与音乐家的角色进行了比较。 目前,人类只能掌握一种乐器,但通过人工智能补充他们的能力,人类可以成为整个交响乐。 当我们处理与 AI 中的偏见相关的问题时,这一点尤其重要。 机器并不完美,但人类可以教它们变得更好。 集中的语言操作是关键 人工智能还可以集中组织跨部门和项目翻译内容的方式。 这种集中式方法称为语言操作 (LangOps),它依赖于人工智能驱动的数据层来打破孤岛并存储特定于品牌的词汇表、翻译记忆库和自定义机器学习,然后可以在整个组织中使用。 好处显而易见——这是一种简化且更具成本效益的翻译方法。 正如米德尔伯里国际研究所翻译与本地化管理副教授 Adam Wooten 所说,“集中式语言运营应该比现在更普遍。” 职业生涯也在改变,以适应这种转变 我们的许多 LangOps Universe 与会者都很好奇向集中式语言运营的转变将如何改变未来翻译和本地化专家的角色。 我们许多演讲者的最大收获是语言专家需要将他们的专业知识从语言扩展到语言和技术。 语言运营计划的成功取决于技术工具的应用,以支持整个公司的翻译功能。 语言专家将扮演编辑和促进者的角色,指导人工智能工具正确翻译内容,考虑上下文和文化细微差别。 寻求高管对语言操作的认可 许多与会者还对如何在语言运营方面获得高管支持感到好奇。 我们发言人的共识如何呢? 证明它的价值。 数据已经出来了。 公司因支持多个部门特定的语言翻译方法而亏损。 金钱被浪费在提供重复功能的多种工具上。 翻译和本地化不能被视为事后附加到产品团队或营销部门的东西——它必须成为跨部门的集中职能。 感谢所有参加和参与 LangOps Universe 的人。 请密切关注我们的博客,以获取更多回顾和总结,分享所有发生的有趣对话。

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