The companies selling speed are now racing to own the hardware that delivers it. OpenAI just rolled its first custom chip, Walmart paid 12× revenue for streaming ad pipes, and Meta's reorg broke most of what it touched.

The pattern is vertical: everyone wants the full stack, even when the integration timeline stretches into 2028. The bet is control, and the cost is flexibility. What breaks first?

That's the top model on an independent 6,000-question test. The rest score lower, and no single one wins every domain.

The problem isn't that AI is wrong sometimes, it's that it's wrong in the exact same confident voice it uses when it's right. Cuey lets you cross-check ChatGPT, Claude, and Gemini on one prompt, so you catch the miss before it goes in your deck.

Start cross-checking, free.

When a $410m startup sells for $1.4b nine months later, valuation gravity has clearly reversed. Walmart’s purchase of Vibe.co at roughly 12.6x revenue, versus public rival MNTN at ~1x, is a massive premium for pipes, not current performance.

The logic is simple: own the plumbing for performance CTV and you own how retail intent becomes ad dollars. Vibe’s self-serve platform for SMB streaming ads plugs straight into Walmart Connect and the Vizio footprint, turning “TV” into another closed-loop performance channel in the race to narrow Amazon’s ad lead.

At this price, Walmart is effectively marking the curve for mid-market retail media infra. Every retailer trying to build an ads business just watched the comps re-rate. For Vibe’s French founders, it’s another three-times-up exit that compounds inside a US giant and a signal that the ceiling for winning CTV tooling is now very high.

Your phone camera is lying to you.
And honestly… it’s kind of genius.

On paper, smartphone cameras now look almost identical to “real” cameras: 48MP sensors, f1.6 lenses, advanced image processing, cinematic modes. So why do pro cameras still feel different? And more importantly… would anyone actually notice on Instagram?

The GPU status quo just got its first jalapeño in the eye. OpenAI and Broadcom are rolling out Jalapeño, an inference-focused ASIC that represents OpenAI’s first custom inference chip, designed end-to-end in nine months with help from its own models.

This is not a side project; it’s the clearest signal yet that OpenAI intends to build the full stack behind its models, from data centers and power to the silicon itself. A dedicated inference ASIC trades flexibility for cost and efficiency, exactly where margins are tightest as usage explodes.

For founders, the headline is that insatiable compute demand isn’t going away, but who controls the economics is shifting. Expect cheaper, more predictable inference from the majors over time, but also a taller moat: if the frontier labs own the chips, they own more of the value chain being built on top.

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