Data annotation, an essential step in machine learning and artificial intelligence (AI), involves labelling data to train models. While this process has traditionally been manual and relies on human annotators, advancements in AI technology are increasingly shifting the focus toward automated data annotation.
Ultimately, automated annotation systems were created to overcome the limitations of manual annotation, most notably in workforce management and annotation speed. Therefore, most of its benefits come from ease of use and the opportunity to forego human annotations while maintaining speed and consistency in high-functional AI teams.
Even though automated data annotation has clear benefits, there are still some challenges. First, the quality of the annotations can vary depending on how strong the model is and how similar the training data is to your own data. If your data is very different, the quality of the automatic annotations might be lower.
Another issue is customisation. If the automated tool cannot produce quality annotations, teams would need to spend time improving the model or manually fixing the mistakes. If improving the model isn’t possible, the cost of human labour to correct errors can increase over time.
Finally, if the model can be customised, it is essential to consider the ongoing cost of maintaining these customisations. The model will need regular updates to handle new types of data. At some point, companies might even need to decide whether to use different models for data annotation and prediction.
Therefore, effective automated annotation solutions should achieve accuracy and consistency, using a crowd workforce to meet every project’s turnaround requirements.
Scaling AI projects with Tictag
Tictag aims to build the future of the AI economy. Founded in 2019 by a team of AI veterans, this Singapore-based startup, with an operational base in South Korea, has developed a user-friendly, fully integrated, mobile-first platform.
It leverages cutting-edge AI augmentation and scalable human-in-the-loop crowdsourcing to achieve the highest quality in the collection and annotation of image, text, or audio datasets for the training of LLMs (for generative AI) or machine learning, as well as the fine-tuning and deployment of AI and machine learning models.
Tictag aims to become the best way for people and companies to work with data by simplifying data annotation tasks and putting it on a groundbreaking, gamified mobile application. Whether this is for powering computer vision AI models or enhancing data analytics systems, Tictag offers high-quality, labelled datasets regardless of industry.
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Lee Jin, Co-Founder and COO, is committed to “providing the three most important aspects when it comes to data annotation—accuracy, speed, and cost.”
He adds, “We have quality control processes to ensure the data is accurately labelled. Plus, having a large community of taggers to label the data makes the whole process much faster while bringing costs down too.”
Tictag’s technology features its mobile app, available on iOS and Android and boasting over 17,000 users, which contributes to the development and quality of AI datasets. This commitment to accuracy and scalability is reflected in its Truetag system, which targets up to 99.97 per cent accuracy through a hyperfocus on quality assurance and quality control, which is currently heavily overlooked in the market.
Beyond providing data solutions, Tictag is also dedicated to social good. Tictag was designed to be extremely accessible and inclusive, and through the Tictag #GoodData4Good initiative, Tictag collaborates with companies aiming to make a positive social impact. The initiative provides persons with disabilities or from underprivileged backgrounds with opportunities to earn income via an integrated payments system on the Tictag app.
In a recent interview, Kevin Quah, CEO and Co-Founder, expresses Tictag’s aim to bring more opportunities to the community, especially to the disadvantaged and vulnerable parts of our population.
Tictag aims to build the future of the AI economy, citing the Philippines as one of the fastest-growing economies. Quah believes PH-based companies will be interested in deploying AI to improve their businesses. “We are excited to meet with potential businesses, extend our reach, and network with local talents.”
In particular, Tictag specialises solutions centred around the agriculture, automotive, and manufacturing landscape, especially those looking to implement AI and co-develop AI solutions that serve the Philippine market.
Explore AI capabilities in the ASEAN with Tictag and Echelon Philippines
Interested attendees looking to explore their platform can access a 10 per cent discount on their first partnership. Participants can download the Tictag app on the Play Store and App Store today to earn cash and rewards while powering AI.
Tictag is among the many dynamic industry leaders joining us for Echelon Philippines 2024. Alongside them will be other key leaders, visionary entrepreneurs, and innovative startups from across the region. They will converge for an action-packed two-day September 26-27 event at Level 2, SMX Convention.
Echelon Philippines 2024, hosted by e27 in partnership with Brainsparks, offers dedicated content stages, exhibitions, panel discussions, and much more — all designed to support and empower the regional tech startup ecosystem with practical insights through various knowledge-sharing activities.
Whether you are looking to expand your expertise, connect with influential figures in the tech startup world, or present your groundbreaking ideas, Echelon Philippines 2024 offers an unmatched experience sure to boost you and your company. Secure your spot on our official page now and join us as a participant or official partner. Together, we can shape the future and create a lasting impact.
Join us at Echelon Philippines 2024, where innovation knows no boundaries and the possibilities are limitless!
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