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From the floor of HumanX, CoreWeave CTO Peter Salanki is making a case that most teams building with AI are getting ahead of themselves. His message is straightforward: before you over-architect a complex system, get the basics right — observability, utilization, and smart scheduling. Running AI in production is harder than it looks, and the gap between prototype and reliability is where most projects quietly fall apart.
On a very different note, Motorola is facing some uncomfortable questions after reports emerged that its phones have been intercepting traffic inside the Amazon app to inject affiliate codes. That means the device manufacturer may be quietly earning commissions on purchases made through an app it has no role in building or maintaining. It's the kind of behavior that sits in an ethically murky space, and it's drawing sharp reactions from users and developers alike.
And in the world of local AI tooling, Ollama has pushed a new release candidate, version zero point thirty, that moves toward directly supporting llama dot cpp and improving compatibility with the GGUF model format. For developers running large language models on their own hardware, tighter integration at this level means fewer workarounds and more stable performance out of the box.
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