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How on Earth can AI Transcribe and Summarize an 8-hour Podcast?
Recently, a tweet by Robert Scoble highlighted an 8.5-hour podcast conversation with Elon Musk and the Neuralink team, sparking a discussion about the feasibility of using AI to handle such a task. This blog post delves into the intricacies of this challenge, focusing on the barriers posed by token limitations in current Large Language Models (LLMs) and how Alani AI offers a promising solution.
The Transcription Challenge
Length and Volume
Transcribing an 8-hour podcast is no small feat. On average, people speak at a rate of about 125–150 words per minute. For an 8-hour podcast, this translates to a staggering 60,000 to 72,000 words. To put this into perspective, that’s equivalent to approximately 200 to 288 pages of text, assuming an average of 250–300 words per page.
Technical Complexity
The podcast in question is described as “super technical,” meaning that any transcription tool must accurately capture specialized terms and jargon. Automated transcription tools often struggle with accuracy, especially for long and complex…
