Send us a text In this episode of Sidecar Sync, Amith Nagarajan and Mallory Mejias dig into the startling findings of a recent MIT study: 95% of enterprise AI initiatives are failing to deliver measurable impact. Why are so many organizations investing in AI only to watch their efforts fizzle? Mallory and Amith unpack 10 core reasons for these failures—ranging from building chat-first features instead of end-to-end workflows, to skipping the unglamorous data cleanup that powers real results. ...
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Send us a text In this episode of Sidecar Sync, Amith Nagarajan and Mallory Mejias dig into the startling findings of a recent MIT study: 95% of enterprise AI initiatives are failing to deliver measurable impact. Why are so many organizations investing in AI only to watch their efforts fizzle? Mallory and Amith unpack 10 core reasons for these failures—ranging from building chat-first features instead of end-to-end workflows, to skipping the unglamorous data cleanup that powers real results. ...
Inside the AI Audio Revolution: Translating, Conversing, & Composing | 98
Sidecar Sync
50 minutes
4 months ago
Inside the AI Audio Revolution: Translating, Conversing, & Composing | 98
Send us a text In this audio-focused episode of Sidecar Sync, Mallory Mejias and Amith Nagarajan explore three groundbreaking advancements in AI audio technology—starting with Google’s real-time voice translation for seamless cross-language communication. They then unpack Microsoft’s open-source Vibe Voice, capable of generating full-length, multi-speaker podcasts, before diving into ElevenLabs Music, an AI tool creating fully-licensed, studio-quality tracks from simple prompts. Tune in for l...
Sidecar Sync
Send us a text In this episode of Sidecar Sync, Amith Nagarajan and Mallory Mejias dig into the startling findings of a recent MIT study: 95% of enterprise AI initiatives are failing to deliver measurable impact. Why are so many organizations investing in AI only to watch their efforts fizzle? Mallory and Amith unpack 10 core reasons for these failures—ranging from building chat-first features instead of end-to-end workflows, to skipping the unglamorous data cleanup that powers real results. ...
