A decade ago, when we told Alexa to play a song, the world was surprised at Machine Learning’s (ML) ability to do it effectively, quickly, and accurately. Cut to today, where ML is now smarter than ever, because of Natural Language Processing (NLP) and Transformer Models.
In this point of view, we explore the surge of transformer models and their impact on business. As more businesses adopt transformer models, the field is rapidly evolving and now takes on the responsibility of even more complex and difficult tasks. The role of transformer models has become integral today in getting customer feedback and understanding their behavior, preferences, etc., and thus, enable crucial, data-driven business decisions.
Transformers are a type of neural network architecture that uses attention mechanisms to process sequential data, such as text. They have shown remarkable performance in a variety of NLP tasks, such as language translation, question answering, and sentiment analysis. As a result of their success, transformer-based models have been used in a wide range of applications, including chatbots, search engines, recommendation systems, and more. With its vast availability of such insights, transformer models have become a force to reckon with for meaningful customer engagement and strategic business decisions.
The growth of the transformer model industry has been fueled by the performance of these models in NLP tasks and their increasing popularity in a wide range of use cases, applications, and industries. As research in this area continues to advance, even more innovative applications of transformer-based models are slated to arise in the future.
As Transformers in Machine learning are paving the way for transformative new use cases of AI, hyperscalers are scaling their Transformer Model capabilities and investors are funding more Transformer Model-centric start-ups. We map these investment trends, patterns of hyperscalers, make predictions about macro trends, as well as take stock of the industry verticals most impacted and how the landscape has changed over the years.