Braincast vs Conformer2: Which is better?

Braincast is an AI-powered application that transforms links and PDFs into interactive quizzes similar to those found in Duolingo, facilitating enhanced learning experiences. It collects minimal public data from users' Gmail accounts for secure authentication and operates internationally while prioritizing data privacy and security. Users can create accounts, manage subscriptions, and have the option to delete their accounts at any time.

Conformer-2 is an advanced AI model designed for automatic speech recognition. It has been trained on 1.1 million hours of English audio data, resulting in significant improvements over its predecessor, Conformer-1. This model focuses on enhancing the recognition of proper nouns, alphanumerics, and noise robustness.The development of Conformer-2 was driven by the scaling laws proposed in DeepMind's Chinchilla paper, which highlighted the importance of sufficient training data for large language models. Consequently, Conformer-2 has been trained on a substantial amount of data, utilizing 1.1 million hours of English audio.One notable feature of Conformer-2 is its adoption of model ensembling. Instead of relying on predictions from a single teacher model, Conformer-2 generates labels from multiple strong teachers. This ensembling technique reduces variance and enhances the model's performance when faced with unseen data during training.Despite the increased model size, Conformer-2 offers improvements in terms of speed compared to Conformer-1. The serving infrastructure has been optimized to ensure faster processing times, achieving up to a 55% reduction in relative processing duration across all audio file durations.In real-world applications, Conformer-2 demonstrates significant enhancements in various user-oriented metrics. It achieves a 31.7% improvement on alphanumerics, a 6.8% improvement on proper noun error rate, and a 12.0% improvement in noise robustness. These improvements are a result of both increased training data and the use of an ensemble of models.The Conformer-2 model is ideal for generating accurate speech-to-text transcriptions, making it a valuable component for AI pipelines focused on generative AI applications that utilize spoken data.