AI’s Biggest Hidden Cost Isn’t Compute. It’s People.
Everyone is talking about the cost of AI. Usually they're talking about GPUs, model licensing, or token consumption. I think they're looking in the wrong place. The biggest cost of enterprise AI may turn out to be the people needed to supervise it. A recent study found employees save about 11 hours a week using AI, but spend more than six hours checking outputs, fixing mistakes, adding missing context and making sure the results are actually usable. Someone coined the term "botsitting" for it… [...]
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The AI compute gap: Enterprises are buying infrastructure faster than they can measure what it costs
Across 107 enterprises, AI infrastructure spending is accelerating well ahead of the ability to see or steer its economics. Most organizations run their AI on a familiar base of hyperscalers and model [...]
iPhone 17e vs. iPhone 16e: What's new on Apple's latest $599 handset
Apple’s most affordable iPhone just got an upgrade, but how does the new iPhone 17e compare to the iPhone 16e? Well, thankfully the price remains the same at $599, which is good news in our current [...]
Infrastructure and compute: Enterprises are buying AI compute for speed while flying blind on what it costs
Across 170 enterprises, AI infrastructure has moved decisively into production — two-thirds now run AI workloads live and three in 10 run them at scale — while the ability to account for what that [...]
iPad Air M4 vs. iPad Air M3: The few new things in Apple's midrange tablet
The iPad Air, the middle child in Apple’s tablet lineup, has been upgraded to the M4 chip with increased RAM and… Well, there’s not a whole lot else if I’m being honest. At the very least, the [...]
MacBook Air M5 vs. MacBook Air M4: What's changed beyond the Apple silicon
Apple unveiled a new MacBook Air today, and apart from the new M5 chip, things don’t look remarkably different. Sure, it’s getting a mild refresh, but maybe not in the way most people would want. [...]
Train-to-Test scaling explained: How to optimize your end-to-end AI compute budget for inference
The standard guidelines for building large language models (LLMs) optimize only for training costs and ignore inference costs. This poses a challenge for real-world applications that use inference-tim [...]