Garrett Goodman’s Post

Tackling challenges with LLM-powered dubbing at Papercup. Our LLM-powered dubbing is a game-changer, but every tech has its hurdles. Here’s how we’re tackling them: 1️⃣ Hallucinations: LLMs sometimes make up information. We counter this with prompt engineering and human review to ensure translations stay true to the source. 2️⃣ Consistency: Keeping terminology and character voices consistent in long-form content is tough. We use memory mechanisms, glossaries, and human oversight to maintain continuity. 3️⃣ Specialized Content: For niche industries, we fine-tune models on domain-specific data and consult with experts to get it right. 4️⃣ Emotional Nuance: AI struggles with capturing emotional shifts. We’re improving this with sentiment analysis and human touch for the final polish. 5️⃣ Ethical Considerations: We’re transparent with data use, address biases, and see our AI as a tool to enhance, not replace, human creativity. By acknowledging these challenges, we’re constantly refining our system to push the boundaries of AI dubbing while ensuring top-notch quality! https://lnkd.in/epbHCgix #AI #LLMs #Dubbing #LargeLanguageModels

Dubbing can be a real headache. 💆🏻♂️ Expensive, time-consuming, and tricky. But at Papercup, we're flipping the script! By harnessing the power of large language models (LLMs), we've created a context-aware translation system that makes AI dubbing smoother than ever. So, what do LLMs do for us? They extract context, generate summaries, identify key terms, and even pick up on style and tone. 👀 https://lnkd.in/epbHCgix #LLMs #AIDubbing #AI #Language

Writing in the times of AI. One often overlooked but very important aspect of meaning acquisition in language is its two-mode semantics: reference and inference. Reference is how words (and other linguistic entities) latch on things in the outside world. The meaning of an apple is partially contained in our experience of that red (or any other color for that matter), round, plant-based object that we eat. Inference, on the other hand, is how the meaning of a word is encoded in its relationships with different words or linguistic entities. The meaning of an apple is related to the words 'fruit', 'red color', 'round', 'plant', 'food', etc. AI, and large language models, in particular, excel in the latter mode of semantics. They contain extremely large and complex networks of relations between linguistic entities. That is why they sound like very fluent speakers. They are very good 'word matchers' for the lack of a better term. When we write (or use language in general), we strive to engage the reader (or the communication receiver) in these two modes of meaning acquisition. We try to invoke experiences of real or imagined objects while at the same time taking advantage of the relationships of the vast network of words and sentences we learned throughout our lives and believe we share with other humans. As writers in order to thrive in the age of AI while taking advantage of such technology, we need to double down on making our writings more immersive and evocative while making use of the vast semantic networks provided by LLMs. In relation to brands and content in general this means that now all brands can sound fluent, but only the personal ones will stand out. In other words, only the brands with a human face will thrive and garner the sought-after engagement. I believe we already reached a saturation level of generic content and the need for differentiation and fine-grained personalization is more pressing than ever. As a closing remark, the current status quo reminds me of the beautiful opening paragraph in Dickens's masterpiece 'A Tale of Two Cities': "It was the best of times, it was the worst of times, it was the age of wisdom, it was the age of foolishness, it was the epoch of belief, it was the epoch of incredulity, it was the season of light, it was the season of darkness, it was the spring of hope, it was the winter of despair."

Today, it finally happened. Today 𝐈 𝐰𝐚𝐬 𝐜𝐨𝐫𝐫𝐞𝐜𝐭𝐞𝐝 𝐛𝐲 𝐚𝐧 𝐀𝐈. I knew it would happen sooner or later, but I hoped I'd take it better. Perhaps because I hoped it would be a 𝐬𝐥𝐢𝐠𝐡𝐭𝐥𝐲 𝐥𝐞𝐬𝐬 𝐬𝐭𝐮𝐩𝐢𝐝 AI proofreading me. The 🤡𝘤𝘭𝘪𝘦𝘯𝘵🤡 used an AI that: 🚀 Doesn't know the basic punctuation rules of French (the famous unbreakable space before certain punctuation marks) 🚀 Thinks that "P" is a vowel (therefore suggests a specific article for words starting with a vowel ➡ "𝐀𝐜𝐪𝐮𝐢𝐬𝐭𝐚 𝐮𝐧' 𝐩𝐫𝐨𝐛𝐚𝐛𝐢𝐥𝐢𝐭à" LMAO) 🚀 Detects non-existent spaces at the end of sentences 🚀 Suggests removing accents from words that need them 🚀 Proposes changes in prepositions at its own taste 🚀 Flags my non-existing word Zampastico (transcreation for Pawsome) but doesn't bat an eye at "Miaoravigioso" (transcreation for Purr-fect) (and the client didn't even bother thinking "Hey, there's a made up word in the source, 𝐦𝐚𝐲𝐛𝐞 it's fine in the target too?") 🤬 Three linguists in three different languages had to justify, to a PM who doesn't know any of these languages, why the flags raised by the AI were nothing but BS. 🤬 Three linguists who wasted precious minutes doing so (and a PM having to deal with useless BS) (And me, who spent an hour creating this post, but you get it, I needed to vent/share). 𝐈𝐧𝐬𝐮𝐥𝐭𝐢𝐧𝐠. I can't find any other words. My calm response, on the right. Oh, BTW, it's a 𝐡𝐮𝐠𝐞 𝐛𝐫𝐚𝐧𝐝, a leader in its sector for gaming apps and board games. Just to give you some context. Just great. #Gameloc #Localization #AI #GameOverForGreed

I am yet to make any personal experiences with being "corrected" by AI, but this is what happens. [insert Surprised Pikachu face here] #translation #localization #xl8 #t9n #l10n #ArtificialIntelligence #AI #GenerativeArtificialIntelligence #GenerativeAI #GenAI #QualityAssurance #QuabityAssuance #CreedBratton #Useless #LITranslators

This is a startling example of why automated quality assurance tools may not work in certain languages or use cases. Many tools are fine tuned for English language and American spelling. They may fail in British spelling, sometimes. Their performance in other languages is questionable. Translation agencies and project managers need better training on AI enabled tools. Running a pilot project is always a good idea before obliging professional translators to use a new tool or function. In this case, I am sorry for the translator colleague. If I were the translation agency, I would pay her extra or send a gift to help compensating for the time lost and more importantly for the emotional damage.

BLGAi and you- As you embark on your journey with our PrivateGPT and our lifeStyleGPTs, you'll discover a world of possibilities powered by large language models (LLMs). Alani.ai offers you a diverse selection of LLMs, each with its unique strengths and capabilities, allowing you to tailor your experience to your specific needs. GPT-4: Intelligent and Proficient but Slower When you choose OpenAI's GPT-4, you're harnessing the potential of a highly proficient and intelligent model. GPT-4 excels in complex tasks, delivering accurate and contextually relevant responses. Whether you're seeking in-depth analysis, creative writing assistance, or research support, GPT-4 is your go-to model. Keep in mind that its advanced capabilities may result in slightly longer response times, but the quality of its output is unparalleled. Mixtral: Perfect for Real-Time Interactions If speed is your top priority, Mistral's Mixtral model, hosted on Groq hardware, is the perfect choice for you. This model is optimized for real-time interactions, delivering quick responses with minimal latency. Whether you're building chatbots, real-time translation systems, or any application that requires swift responses, Mixtral has you covered. However, it's important to note that this speed comes with a trade-off in terms of the model's overall language understanding and proficiency. Claude 3 Sonnet: Striking the Perfect Balance of Fast & Smart For those seeking a balanced experience, we highly recommend Anthropic's Claude 3 Sonnet model. This model strikes a remarkable equilibrium between speed and intelligence, providing you with the best of both worlds. Claude 3 Sonnet is versatile and can handle a wide range of tasks with impressive performance. Whether you're engaging in conversational AI, content generation, or language translation, this model delivers reliable results without compromising on speed. To get the most out of your Alani.ai experience, it's crucial to understand how to interact with these LLMs effectively. When using GPT-4, provide clear and detailed prompts to guide the model towards the desired output. Take advantage of its contextual understanding and provide relevant information to ensure accurate and comprehensive responses.

📚 Discover the forefront of innovation, Unbabel's TowerLLM! Our in-depth blog dives into this language model's cutting-edge capabilities: 🔑 Data's vital role in fine-tuning & training ⚡ RAG for ongoing adaptation & personalization 🔒 Benchmark data privacy for LLM development 📈 Results proving LLMs will lead translation AI 🚀 TowerLLM + Quality Estimation driving efficiency Read the blog 👉 https://t1p.de/1j0o7 #TranslationTech #InnovativeAI #UnbabelTowerLLM #TowerLLM #AI #ArtificialIntelligence

Unveiling the Power of Gemini: Google's Latest AI Model I'm excited to share my thoughts on Gemini, Google's latest and most powerful AI model to date! Gemini boasts impressive capabilities across various benchmarks, making it a significant advancement in the field of AI. It excels in tasks like: * Understanding and responding to complex questions: Gemini can grasp intricate concepts and deliver informative answers, making it a valuable tool for research and information gathering. * Generating different creative text formats: Whether it's crafting compelling poems, writing different kinds of creative content, or translating languages, Gemini's versatility is truly remarkable. * Translating languages accurately: Gemini demonstrates exceptional proficiency in language translation, fostering communication and understanding across diverse cultures. I'm particularly interested in exploring how Gemini's capabilities can be harnessed to: * Revolutionize scientific discovery: By processing massive datasets and identifying patterns, Gemini could accelerate scientific breakthroughs in various fields. * Enhance creative endeavors: Gemini's ability to generate creative text formats could inspire new artistic expressions and fuel innovation in various creative domains. * Bridge the communication gap: Gemini's language translation capabilities hold immense potential to break down language barriers and foster global collaboration. The potential applications of Gemini are vast and constantly evolving. I'm eager to witness how this powerful AI model shapes the future of various industries and empowers individuals in diverse fields. Feel free to share your thoughts and discussions about Gemini in the comments below!

Real-time speech #translation is one of OpenAI’s main selling points for its latest release, GPT-4o. OpenAI CTO Mira Murati demos live translated short conversation 💬 with a colleague. #AI #xl8 #t9n #LLM #largelanguagemodel #OpenAI