TT(O)M

Introduction Several months ago, I posed a question in the r/audacity subreddit regarding the differences between various OpenVINO Whisper Transcription models and their impact on transcription quality. Having received no response, I conducted this comparative study independently. Evaluating the performance of these models across diverse audio content is essential for a comprehensive assessment. This report compares four audio processing models: base , small , medium , and large-v3 . The analysis encompasses scores achieved by each model on ten different audio tracks (labelled Track 1 through Track 10), along with their respective processing durations. The objective of this analysis is to provide a data-driven foundation for assessing each model’s effectiveness, examining their processing efficiency, and identifying the strengths and weaknesses of each model.   Analysis Data All tracks, outputs from the different Audacity models, source code used to generate the scores, and in...

Comparing the Predictive capabilities of AI Engines Introduction In this edition of Great Technology Links, we will focus on the topic of Artificial Intelligence (AI). We discuss four products rather than the usual three and will compare their outputs and, in the process, highlight certain limitations of these tools and of AI in general. AI technology can be divided into two categories: Generative - This category describes AI engines that are able to generate output based on prompts. Examples of such output include text, graphics, audio, and videos. For example, in this study, the graphic generated by CoPilot is an example of generative output. Predictive - These AI models ingest massive amounts of data and, based on the source material, provide knowledge-based (expert-systems) output or extrapolate into the future. The analysis focuses more on the predictive aspects of the evaluated AI engines. The AI Engines The four AI engines that were analysed are: Anthropic Claude : h...