Is AI Language Inclusive?

Did You Know? Most internet users are non native English speakers.

In today's global digital landscape, it's easy to assume that English dominates the internet. But new statistics reveal an eye-opening truth: In 2023, the worldwide internet user base exceeded 5.16 billion people, as reported by Statista. Although English emerged as the predominant language, accounting for 25.9% of global users, its dominance contrasts sharply with the fact that only 1.46 billion people speak English, representing less than 20% of the world's population.

But wait, there's more! Among those who do use English on the internet, a significant portion are non-native speakers. This means that even when presented with an option to use English, many people still choose alternative languages due to comfort or familiarity.

So what does this mean for businesses and developers? It highlights an urgent need to expand our thinking beyond just "English-first" solutions. By embracing multilingual support across websites and apps, we can tap into a vast untapped audience and enhance user experiences globally.

AYA, A Game Changer in AI Inclusivity

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Meet Aya, an open science project by Cohere For AI, a non-profit research lab. More than a language model, Aya reshapes AI inclusivity with its multilingual model, uniting over 3,000 researchers from 119 countries. Aya transforms multilingual AI research with its advanced dataset, featuring 513 million prompts in 114 languages—the largest open-access collection. 

As an inclusive AI Chatbot, Aya understands and responds in multiple languages, breaking down barriers for everyone. Its goal is clear: democratize the benefits of AI, ensuring accessibility for all linguistic backgrounds.

Try it out yourself HERE

Understanding Multilingual Models: Training & Evaluation

Imagine you want your AI assistant to understand and help people in different languages. That's where multilingual models come in! Training a multilingual model involves these steps: 

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1.Collecting lots of text data from many languages

• Books, articles, websites, and other sources provide this information.
• The more data we have, the better our model will perform.

2.Cleaning up the text

• Removing bad or duplicate content improves training efficiency.

3.Breaking down sentences into smaller pieces (tokens) 

• Words or small parts of words are converted into numbers for processing.
• Different writing systems are handled too!

4.Teaching the model how words relate to each other

• Using deep learning techniques, it learns patterns between words.

5.Testing its performance on new examples

• We use special benchmarks and test datasets to see how well it works!
• Remember not to include any part of the test set in what we trained on.

With these steps complete, our multilingual model is ready to help people speak and understand multiple languages!

The Challenge of Multilingual Support: More Than Just Adding Storage

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Now, let's talk about the real work behind supporting multiple languages in our digital products. It's not as simple as just adding another hard drive and throwing some data at it.

Languages are incredibly complex creatures! Each one comes with its own set of intricacies – grammar rules, parts of speech, idiomatic expressions, local contexts...the list goes on.

Can you imagine trying to learn and understand 100+ languages? That's an overwhelming task! It requires deep linguistic knowledge, cultural awareness, and constant adaptation to keep up with evolving language usage.

So, when emphasizing commitment to multilingual support for users – that means investing time and resources into truly understanding each language. This involves more than just putting together translations or relying on machine learning alone. It takes dedication, expertise, and genuine care for the diverse communities utilizing products around the world. And that is precisely what drives this effort forward!

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This is further discussed or explained in our Data Science & Machine Learning course.

What about Ethical considerations?

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Believe it or not, accommodating multiple languages might not be as straightforward as direct translations. Here are some considerations when accounting for many languages:

• Avoid linguistic bias
• Respect cultural sensitivities
• Ensure data privacy & security
• Prioritize accessibility & inclusivity
• Engage with diverse communities

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By doing so, we can create equal opportunities for all users,  fostering greater inclusivity in the digital space.

The Future looks bright!

Aya broadens language support to 101 languages, more than doubling previous open-source models. Why is this significant? It tackles long standing issues in AI language accessibility and cultural representation. By vastly increasing multilingual capabilities, Aya opens up AI research opportunities for numerous underserved languages and communities

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In summary, Aya represents a significant step forward in AI research, emphasizing inclusivity and accessibility. Its excellence in natural language understanding, multilingual support, and cultural awareness positions it as a trailblazer in the field of chatbot development. As we navigate the complexities of AI ethics and strive for technological progress, Aya is paving the way for a more inclusive and interconnected digital future.

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Dive into the world of cutting-edge AI technologies like Aya! Begin your journey in AI knowledge with a FREE Workshop in Data Science & Machine Learning. Book your spot HERE.