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Meetings. Speeches. Quick thoughts to self. Those words are more than words. That's your company's secret sauce. Philip Kiely, Head of Developer Relations at Baseten, joins us to discuss.

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Topics Covered in This Episode:
1. AI Transcription Benefits
2. Whisper Model by OpenAI
3. Cost of Transcription
4. Business Applications for AI Transcription

Timestamps:
00:00 Conversations are gold; AI makes them valuable.
03:56 NVIDIA advances exceed Moore's Law; Apple's AI inaccurate.
09:48 Text transcription technology error-prone; manual transcription necessary.
11:19 Whisper V3: Low error rate, multilingual accuracy.
14:58 Whisper rapidly transcribes audio with high efficiency.
17:26 Emotion inflection crucial for text-to-speech synthesis.
23:58 AI transcriptions need human verification for accuracy.
25:35 Chain cheap AI models for efficient calls.
30:53 On-device AI less powerful than cloud AI.
33:07 Build prototypes now; technology improving rapidly.

Keywords:
Whisper by OpenAI, Automatic Speech Recognition, Open-source ASR, Accuracy, Multilingual ASR, MIT licensed, Amazon Transcribe, Whisper V3 Turbo, Live transcription, Speech inflection, ChatGPT, Philip Kiely, Jordan Wilson, Everyday AI podcast, Unstructured data, Anthropic funding, NVIDIA AI advancements, Apple AI alerts, AI transcription, Base 10, Searchable data, AI infrastructure platform, AI cost efficiency, Wearable technology, Voice control, On-device inference, Cloud inference, Speech synthesis, Business applications of transcription, Future of work

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