TAUS Data Marketplace has brought new opportunities to everyone, from individual linguists and LSPs to data and publishing companies, to leverage and monetize their content. The key to being a part of the surging trend of language data for AI is the successful conversion of available multilingual content into language data that is directly usable for AI model training.
Globalization lies at the core of the contemporary age. Knowing this, it’d be ideal to think that the enterprise of academic research would capitalize on contributions from researchers globally and also wants these contributions to be accessible by all students and academics all around the world. Yet, language barriers still present a considerable stumbling block when it comes to the global circulation of academic findings. English is the dominant language in the academic world, which means that researchers around the world are under pressure to publish their findings in English and academic students are expected to understand and digest all of these significant findings in English. This overall contributes to the creation of an academic monoculture.
The total volume of data created worldwide is expected to reach 149 zettabytes by 2045. Therefore, capitalizing on data has become as important as human, financial, or any other capital. Data as capital has gained even more importance now that data-trained systems start to dominate all imaginable aspects of the world we live in.
"The Web does not just connect machines, it connects people," said Tim Berners-Lee, the inventor of the World Wide Web. Whether online or offline, language is just as important to building human connections: it forms the basis of how users identify with each other and the boundaries within which communities come together for common interests.
AI systems are becoming a global trend. Businesses around the world are starting to explore how these systems can benefit them and their customers, but AI is not yet at the stage where it can simply be plugged in and expected to operate. They require an immense amount of data and training to provide the desired outputs.
Interaction between humans and computers has greatly intensified as we sail through the twenty-first century. The ability to access computers and the internet has become increasingly important to completely immerse oneself in the economic, political, and social aspects of the world. However, not everyone has access to this technology. The idea of the "digital divide" refers to the growing gap between the underprivileged members of society who do not have access to computers or the internet; and those who do have access. Education and learning lie at the heart of these issues and their solutions. Learning can only happen through available resources in the language one can understand.
Data is no longer just a good idea — now that so many businesses are using and monetizing it, driving business through data and adopting this new trend have become essential for keeping up with the competition. According to the technology adoption lifecycle model, the first group of people to use new technology is called “innovators,” followed by “early adopters”. Next come the “early majority” and “late majority”, and the last group to eventually adopt a new technology are called “laggards”. Being among the early adopters brings up the head start advantage.