For instance, you can speak a lot of languages with AI freely and this is becoming more flexible to help telephonic communication internationally. We used to be able to extract knowledge in up to 100 languages for AI models (e.g. from OpenAI GPT-4) and Google’s multilingual BERT, which covers more than 90% of the global population Based on these datasets, the models have learned to understand more than a lot of different constructs at an 85%-95% level when asked for generating responses.
These multilingual AI models work using the medium of neural networks, that analyze syntax and grammar or semantic patterns across languages—a functionality offered by bilingual translators as well. For example the Google Translate uses neural machine translation (NMT) to make real-time translations as it learns context so that it translates sentences and not just words. Sora designed a system where these levelling scores reduced the error by 60% against older translation systems. This development highlights the ability of AI to effectively close language divides.
That said, while AI excels in languages such as English and Spanish to Chinese but when it comes to less probably heard speaking languages, the technology underperforms. At times, translation accuracy even falls below 70% in languages that have fewer digital resources or data (Amharic and Māori). This is so, partly due to the fact that these languages lack sufficiently digitized corpora — both monolingually and in parallel with other widely spoken tongues (Jamie Lum of TWB noted this as well).
Multi-lingual customer service is a play which will be greatly influenced by AI. Large corporations such as Microsoft and Meta use multilingual AI to integrate into their platforms, thus offering customer support in more than 60 languages. This has provided an efficiency lift, increasing customer satisfaction by 20% for non-English speakers when they are able to get help in their local languages. Thanks to machine learning, those systems continue the gauntlet race towards perfection as they learn and adopt new slang idioms or regional dialects; meaning conversation can sound even more real.
Elon Musk famously commented, “AI doesn’t sleep and is everywhere,” highlighting how AI's multilingual capability makes it an invaluable tool in a connected world. With ongoing advancements, the capacity to talk to ai in various languages grows, fostering a more inclusive digital environment.