In a bid to reshape the landscape of artificial intelligence (AI) and make it more accessible to a wider range of languages, Cohere has unveiled the latest additions to its Aya project: the Aya Expanse 8B and 35B models. These groundbreaking models, now available through Hugging Face, are designed to enhance the performance and accessibility of AI language models across 23 different languages. By prioritizing multilingual capabilities, Cohere not only challenges the existing dominance of English in the AI realm but also fosters inclusivity for global users.
Cohere’s commitment to inclusivity is clearly evident in the design philosophy of the Aya Expanse models. The company stated that the 8B model opens doors for researchers worldwide, while the larger 35B model offers advanced multilingual functionalities. This strategy aligns with the overarching goal of the Aya initiative, which aims to democratize access to foundation models beyond dominant Anglophone contexts. Since launching the Aya project in the previous year, Cohere has systematically built a framework for expanding AI accessibility, beginning with the release of the Aya 101 model—a 13-billion-parameter model encompassing 101 languages.
Cohere’s methodology, which heavily relies on a technique known as data arbitrage, plays a pivotal role in the development of the Aya Expanse models. Traditional language models often struggle with generating coherent output when they depend solely on synthetic data produced by a “teacher” model, particularly for low-resource languages. Instead, by capitalizing on data arbitrage, Cohere circumvents the pitfalls of synthetic data generation that can lead to gibberish outputs. This approach allows for richer and more accurate model training, thereby yielding superior performance across various languages.
What sets the Aya Expanse models apart is their focus on global preferences—an acknowledgment of the diverse cultural intricacies inherent in language. Cohere believes in infusing these preferences into the models to ensure that the AI technologies resonate with users’ cultural identities and linguistic backgrounds. In achieving this, the company has faced challenges, particularly in ensuring that safety measures do not simply mirror biases prevalent in datasets rooted in Western contexts. Pioneering a more global approach to preference training, Cohere’s models extend their focus to align with diverse cultural perspectives, a significant step in the quest for equitable AI.
Not only do the Aya Expanse models promise substantial advancements in performance, but they have also outperformed notable competitors, including Google, Mistral, and Meta, on various multilingual benchmarks. For example, the 35B model consistently outdid Gemma 2 (27B), Mistral 8x22B, and even Llama 3.1 (70B). These victories in benchmarking are critical, as they signal the effectiveness of Cohere’s multilingual approach in real-world applications.
Moreover, similar success was noted for the 8B model, which surpassed both Gemma 2 (9B) and Llama 3.1 (8B), highlighting that even smaller models can be highly competent in multilingual scenarios. Such achievements underscore the importance of developing advanced models that cater to the needs of users across general multilingual populations.
Despite these breakthroughs, the journey toward fully equitable AI is fraught with challenges. The dominance of English as the lingua franca of government and business hampers efforts to train models in less-spoken languages. Cohere’s initiative shines a light on the broader discussion about data accessibility, particularly for languages that are underrepresented in digital content. The difficulty in gathering quality data for many languages further complicates the ability to benchmark and validate model performance accurately.
Other players in the AI landscape, such as OpenAI, have also recognized these hurdles and are attempting to build multilingual datasets to level the playing field. By releasing their Multilingual Massive Multitask Language Understanding Dataset on Hugging Face, OpenAI seeks to bolster research efforts centered around languages that are often marginalized.
Cohere’s Aya initiative represents a significant milestone in the ongoing narrative of AI development—prioritizing language accessibility and global representation. By consistently striving to enhance its models and methodologies, Cohere is not just looking to improve the capabilities of AI but is also advocating for a holistic approach that considers the diverse linguistic needs of users worldwide. As the AI landscape continues to evolve, initiatives like Aya will be instrumental in steering the industry toward a more inclusive and equitable future.
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