AI doubters grow louder as IBM bets on commodity models and inference shift
On the latest theCUBE Pod, SiliconANGLE's John Furrier and Dave Vellante discussed rising public doubt about AI against reports that OpenAI's annualized net revenue is about $50 billion — roughly $20 billion below earlier figures — with shares of Nvidia, CoreWeave, Oracle and Nebius falling. The analysts called the backlash an “AI freakout moment” and said IBM is betting on model commoditization, building on Red Hat's open-source foundation to offer a four-part architecture of agents, data, automation and hybrid infrastructure plus an orchestration layer that can integrate agents from multiple vendors. The episode also cited Marvell's target of $70 billion to $90 billion in revenue for fiscal 2031 and a workload mix that has moved from about 90/10 training-to-inference a year ago to roughly 60/40, with an expected flip to 10/90.
If inference dominates and models commoditize, enterprise advantage may shift to proprietary data, processes and operating models rather than the models themselves.