The needless processes / bloat still burn electricity though. I'd have to guess that given the millions of installed macOS machines it's a non-trivial amount of wasted electricity. Long gone are the days of ruthlessly optimizing software for the limited hardware.
Apple has done more than anyone to make its hardware more energy-efficient and its software too. It even warns you about which apps are using the most power.
macOS is far from perfect, but when the background services are working properly, I don't see any evidence that they're any significant driver of energy usage.
On the other hand, when they're buggy and suddenly start consuming 100% CPU all the time for no reason...
Indeed, these processes are not all sitting there doing nothing.
Two processes in particular have been this exact sort of problem for me: mds_stores and mediaanalysisd. On three separate Macs (all Apple Silicon), I've observed the case heating up whenever the computer is plugged in but not actively being used. Assuming Activity Monitor is more or less accurate, the culprit seems to be those two, who always have massive amounts of accumulated CPU time, but never seem to actually be using CPU when watched. I suspect, given what they supposedly do, that they're also needlessly exhausting SSD write cycles, but that's harder to analyze/prove. Naturally, they are also in the untouchable area of the file system. Completely disabling Spotlight, which you can do without disabling SIP, seems to always fix this problem, albeit at the cost of seriously decreased usability. I've also had mixed results with just limiting the categories of Spotlight indexing in System Settings.
Yeah, that's not supposed to be happening. Yet it does. For me it's fseventsd that goes crazy sometimes. These processes are all meant to be lightweight, but they're just buggy and end up in bizarre loops. Once my Mac crashed because it was endlessly downloading the same Aerial screen saver videos in a temp directory until it ran out of space.
Such sad news. As a kid growing up in RI I used to love watching Computer Chronicles on our local PBS station each weekend. Stuart and Gary were the best. RIP to a legend
That's a great point. Sometimes we look for architecture or technology solutions for a problem that could be easily solved at the sales level by negotiating a PPA (Private Pricing Addendum) with AWS.
I can quickly see something like this turning in an AI arms race between insurance and the provider with each auto-approving/denying/disputing the other. All the while locking out smaller players because they can't afford the 3rd party disputotron.
I already have a solution to the downcoding practices of these health insurance carriers.
I recently created an application called EMpowerAI that uses AI to analyze clinical notes and assign appropriate billing codes based on medical complexity or documented time. It also can enhance the Assessment/Plan to justify higher billing codes if the note content supports it.
As a Cardiac Electrophysiologist, I optimized the application for cardiology and EP, though it is scalable to other specialties. I am looking for beta testers and would appreciate any feedback. Here is a link to the app:
You would have to leverage the law (if you have one) that involves the state resolving the dispute because otherwise the automated disputes would probably be dropped on the floor. The insurance company has the leverage because they're actually in possession of the money and the contract that gives them stupidly high discretion on how much to pay out.
Doing nothing but flipping the burden, doctors get paid whatever they invoice and insurance have to claw it back would make a lot of this stonewalling bullshit go away. But with an openly corrupt government paid by insurance it'll never happen.
For a workload of that size you would be able to negotiate private pricing with AWS or any cloud provider, not just CloudFlare. You can get a private pricing deal on S3 with as little as half a PB. Not saying that your overall expenses would be cheaper w/a CSP than DIY, but its not exactly an apples to apples comparison of taking full retail prices for the CSPs against eBayed equipment and free labor (minus the cost of the pizza).
egress costs are the crux for AWS and they didn't budge when we tried to negotiate that we them, it's just entirely unusable for AI training otherwise. I think the cloudflare private quote is pretty representative of the cheaper end of managed object-bucket storage.
obv as we took on this project the delta between our cluster and the next-best option got smaller, in part bc the ability to host it ourselves gives us negotiating leverage, but managed bucket products are fundamentally overspecced for simple pretraining dumps. glacier does a nice job fitting the needs of archival storage for a good cost, but there's nothing similar for ML needs atm.
Yes, the lottery has rules and governance. It's a much safer bet. Startups can decide to devalue their employees' shares. I'd venture that the odds are at least stated on the back of the ticket with the lottery. Employees of privately held startups are often sold a dream of future riches that rarely happens. Even where there is an exit, often even founding employees get taken for a ride.
