bitofsnow

How Did it Work?

I was shocked listening to a net (amateur radio meeting) using RM Noise. Noise was eliminated without buying a new radio. I could hear a conversation with a weak signal barely above the noise floor that was absent on the pan adapter. I now believe a comment I read stating that they can no longer tolerate their radio without it. Today was the first time I listened to my HF radio all day.

How does it work & the importance of AI model customization?

I’ve previously experimented with NVIDIA Broadcast, which runs on my local PC with an NVIDIA RTX 3080. The 3080 includes AI functionality. Broadcast provided similar results to RM Noise for strong signals. Broadcast offered limited value since the weaker signals were dropped as noise. The difference between Broadcast and RM Noise is AI model customization.

What about Production workloads?

I also have a traditional VMware private cloud home lab. With this lab, I understand how the VMware stack runs directly on bare metal with a physical switched network, vSAN, and NAS. Second, this home lab has taken on amateur radio workloads in production 7×24. These production workloads provide me with the experience of managing and operating an environment I can’t just turn off and wipe out.

Who Should Sleep?

Sleep states and hibernation for bears and computers are necessary to save energy stores when nothing is happening. Both species go through a “waking-up” state which takes time and energy. Our Pacific Northwest bears benefit from powering off unnecessary functions in the winter but a server processor at full capacity does not. This only slows down the workload while wasting energy which isn’t a sustainable solution.