Multilingual Content Platforms

What if #AI could unlock new global audiences for sports broadcasting? A year ago, I predicted that #GenerativeAI would shatter #language barriers—and today, that vision is a reality. Innovative platforms like Lingopal, CAMB.AI and Staked AI are already transforming the industry by enabling seamless translation and AI-powered audio, now trusted by: Tennis Channel ,Major League Soccer, The Walt Disney Company, Samsung TV , National Basketball Association (NBA) In my JohnWallStreet article, I’ve included direct links to #translation and #AIaudio #samples from all three platforms, giving #sportsproperties and #broadcasters an exclusive, hands-on look at these cutting-edge solutions. Every solution offers unique advantages tailored to different customer scenarios. How do you envision AI transforming your content and expanding your reach? CC: Next League, John WallStreet , Deven Orie, Akshat Prakash, Chris Shreeve , Comcast SportsTech ,MLS NEXT Pro, AEG , Pac-12 Conference , DCM Ventures , TRTL Read the full column here: https://lnkd.in/emE26xcq #AIPlaybook #AIAudio #AIBroadcast #sportstech #KnowWhatIsNext #ChatgptSports #AILocalization

- What if your TM became a recommendation engine? - What if your glossaries powered your search infrastructure? - What if your localization team could help build the next layer of enterprise AI? 🔥🔥🔥⬇ I sat down with Filip Makraduli from Superlinked for one of the most insightful interviews I’ve had this year. We covered everything from semantic search and cross-lingual personalization to what it really means to build AI-ready language systems. SuperLinked is quietly building the infrastructure that allows machines to understand meaning across languages, formats, and data types. At the center of their work is vector-native technology, specifically, semantic embeddings that replace keyword matching with context-aware, language-agnostic understanding. Filip, who bridges ML-AI engineering and developer relations at SuperLinked, is helping organizations move from brittle string-based systems to flexible architectures where multilingual content can be retrieved, recommended, and repurposed based on intent, not just language. For localization professionals, this is a glimpse into the future: a world where glossaries, translations, and domain-specific content become part of an intelligent, searchable infrastructure and where localization isn’t just about output, but about powering AI systems that actually understand global users. Filip explains how vector embeddings allow us to move beyond strings and keywords to build systems that understand nuance, context, and user intent across languages, formats, and use cases. This is more than a technical upgrade. It’s a call to reimagine how we prepare language data for a world where search becomes a conversation and content must be understood, not just translated. Discover: - Why traditional keyword search is collapsing under user expectations - How vector embeddings create a shared space for meaning across languages - How LangOps breaks from tradition and requires us to treat language as infrastructure, not just output - How you can gradually roll out embedding-based systems without ripping out what already works And this gem: “You don’t have to build separate search systems for German, Arabic, or Spanish anymore. One language-agnostic vector space does it all.” This is not about replacing translators. It’s about a new opportunity to give multilingual content a structure that machines can understand, scale, and personalize without losing meaning. 📖 If you are a language tech geek like me, I am almost sure you'll dig the Full article below. Let me know what you think...

Your website speaks for your business. But if it only speaks one language, you’re leaving money on the table—and letting competitors win. Here’s how to fix that and go global 👇 🌍 1. Don’t Just Translate — Localize ❌ Google Translate won’t cut it. It misses context, tone, and cultural relevance. ✅ How to fix it: Work with native-speaking translators or use AI with post-editing. Adjust visuals, currencies, and cultural references. Match the tone of your message to local expectations. 🧭 2. Create a Clear Language Switcher ❌ Burying the language menu in a footer or making users guess the flag icon? Major UX fail. ✅ How to fix it: Add a visible and accessible language switcher at the top of every page. Use language names (“English”, “Español”) instead of flags. Remember users’ language choice with cookies or session settings. 🖥️ 3. Optimize for SEO in Every Language ❌ Just translating keywords doesn’t work. Search intent varies by country and language. ✅ How to fix it: Do keyword research per locale. Use hreflang tags correctly. Create separate URLs or subfolders (e.g., /fr/, /de/) for each language. ⚙️ 4. Make Sure Your Site is Technically Multilingual-Ready ❌ Many CMS setups break when scaling languages. Slow loading and layout issues drive users away. ✅ How to fix it: Use a robust translation plugin or CMS that supports multilingual content (like ConveyThis 😉). Test layouts across languages—some translations are longer! Optimize performance for every version. 📱 5. Mobile-First, Multilingual-Always ❌ A site that looks great in English on desktop but breaks in Arabic on mobile? That’s a dealbreaker. ✅ How to fix it: Test your site in every language on mobile devices. Avoid hardcoded text in images. Use responsive design that adapts to text length and direction (LTR & RTL). 🎯 A multilingual website isn’t a luxury anymore—it’s a growth tool. 💬 Comment “AUDIT” if you'd like help reviewing your website’s multilingual performance. #WebDevelopment #MultilingualMarketing #WebsiteLocalization #UXDesign #SEO #ConveyThis