Discover the Business Value of Multilingual AI
Greetings Cohere Community,
On the heels of our series D investment, including institutional investors and strategic partners around the world, and our new partnership with Fujitsu to develop Japanese language models, let’s take a look at the importance of multilingual capabilities in generative AI.?
Three Reasons Why Multilingual AI Is Essential?
1. The Business Case: Global Companies Require Global Capabilities
For global corporations, having multilingual AI capabilities is a must. Plus, many countries like Canada, Switzerland, and South Africa have several official languages, so generative AI needs to operate seamlessly across languages for consistency and efficiency. It also needs to address the linguistic and cultural diversity of the global customer base and workforce.?
Cohere Command R+ is optimized for enterprise-grade solutions in the top 10 languages for global business: English, French, Spanish, Italian, German, Portuguese, Japanese, Korean, Arabic, and Chinese. The model also supports an additional 13 languages.?
This means that companies can enhance product features to generate accurate responses from a vast array of data sources in many languages. Our AI search and retrieval models, Cohere Embed and Cohere Rerank, support 100+ languages.??
Beyond customer interactions, these AI tools can also improve communication and collaboration within global company teams, helping boost productivity. Plus, supporting various languages helps companies enter new markets faster, offer localized context, and capture a broader market share.
2. The Performance Case: Mitigating Risks and Enhancing Consistency
From a performance perspective, multilingual AI models offer significant advantages. For example, they:?
3. The Social Case: Bridging the Multilingual Divide
The social implications of focusing solely on English, or a few dominant languages, in AI development are profound. This risks exacerbating existing inequalities and excluding large portions of the global population from the benefits of AI. But there’s no easy solution. Head of research lab Cohere For AI Sara Hooker explains in her latest interview with MLST’s Tim Scarfe, “The tricky thing is that when you try and make AI actually work for the world, you're talking about this vast array of different languages. So, there's 7000 languages in the world, and 80% of those have no text data.”
Developing multilingual AI without pre- and post-training datasets for many languages presents significant challenges. However, initiatives like Cohere For AI’s Aya project, which has developed multilingual models covering 101 languages, show that progress is possible. Such open science efforts ensure that diverse linguistic and cultural perspectives are represented in AI, fostering greater inclusivity and equity. For more, check out policy primer The AI Language Gap.?
At Cohere, our commitment to multilingual AI is unparalleled. As we continue to make strides in this area, companies leading the charge will be able to expand their global reach, boost performance, and promote social equity, making sure that the benefits of AI are enjoyed by everyone.??
For more, check out our latest articles or read on for this month’s highlights and upcoming events!
Product?
Calling all Microsoft Azure AI customers: Cohere Rerank 3 is now available on Azure AI Studio! Join companies like TD Bank and Atomicwork who are using Rerank to improve performance. And for Cohere customers looking for a faster, more efficient alternative, try our new Cohere Rerank 3 Nimble, available on Amazon SageMaker.???
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Developers
Check out the new LLM University home page, and while you’re there, start learning from our latest module on workflow automation with Tool Use. Plus, we have two new resources for building GenAI applications: Structured Outputs with JSON and Cohere Prompt Tuner.
Research
Cohere For AI turns two years old! Here are 10 ways the research lab is helping to solve complex machine learning problems and creating more points of entry to AI research worldwide. Just this month, Sara Hooker’s latest paper addresses the limitations of compute thresholds to answer the age-old question: is bigger always better?
Company
We continue our commitment to leading the way for secure and scalable AI around the world and meeting our mission to do whatever it takes to scale intelligence to serve humanity. This month, we announced our series D funding round and launched a partnership with Fujitsu to develop Japanese models to help support our efforts going forward.
Upcoming events with Cohere?
For all upcoming events, explore cohere.com/events.?
Explore what's possible in the Cohere playground.
Consultant | Digital Transformation | IT Project Manager
1 个月Balancing multiple tasks during your internship? Prioritize, set clear goals, and use tools like Trello or Asana. Keep calm, stay organized, and don't forget to document everything! You got this, future CEO!
Being able to support multilingual speakers' tendency to switch between languages during a conversation is a challenge for even AI transcription software. Phil Rivard, who mentors startups in Quebec, was telling me of his challenge of finding even simple speech to text transcription AI that's smart enough to know when speakers have switched between French and English. While English is still the business lingua franca, it's much more natural for multilingual speakers to intersperse non-English words, phrases, idioms etc. (see example - the language switching in the movie Everything Everywhere All at Once). This suggests that being able to serve multilingual users well with AI requires vast amounts of training on datasets for every language, not only capturing semantics but even nuances in meanings when people use metaphors and turn of phrases within their own cultural context. In terms of how this could even be deployed, the model has to be able to figure out which language databank to source from. That could suggest a UX requirement to have conversation participants self select the languages they commonly use before starting a meeting so the model isn't retrieving data from non-relevant languages that sound the same.
Head of Analytics, Ex-Meta, Teradata, Qualcomm; UCLA Anderson MBA
1 个月"Cultural inclusivity and equity" although intangible, is the most notable progress.
Analytics & AI at A-State | Technology | ESG | Asia Pacific | IITR
1 个月Countries have multiple languages, such as India...
Multilingual models are the way forward in democratizing this technology.