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. ...
The Race for AI Speed, Efficiency, & Infrastructure: Haiku 4.5, Diffusion Models, & Project Suncatcher | 109
Sidecar Sync
46 minutes
1 month ago
The Race for AI Speed, Efficiency, & Infrastructure: Haiku 4.5, Diffusion Models, & Project Suncatcher | 109
Send us a text In this episode of Sidecar Sync, Mallory Mejias and Amith Nagarajan dive into three high-octane AI developments reshaping the landscape of innovation. They kick things off with Claude Haiku 4.5, Anthropic’s blazing-fast small model offering near-frontier performance at a fraction of the cost. Then, the hosts explore diffusion models—an architectural shake-up that could revolutionize how AI generates language. Finally, they venture into orbit with Google’s ambitious Project Sunc...
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. ...
