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It's impossible to tell if someone is driving properly based on just sensor data because if it were, we would have full self driving.


Determining whether a particular driver is driving properly seems overkill. Any correlation between driving behavior and insurance payouts seems like it would be sufficient to improve the accuracy of your risk scores.

Let's say you only analyze vehicle speed data. That is clearly insufficient for training self-driving.

But it is very likely there is some correlation between speed and insurance payouts. For example, say you are able to segment your customer base including one subset with drivers who typically drive >80 miles an hour and another subset with drivers who typically drive <55 miles per hour. Are you saying that you would predict that the two populations have identical risk profiles? That speed data has no correlation with risk?


It's ok we'll just feed your speeds, GPS locations, braking data, and acceleration data into a black box AI model and have it spit out a bill multiplier.

All hail AI.


Too bad it isn't a drop in replacement for tmux because of memory usage. There are memory leaks and even without that the base memory uses is a couple hundred megabytes. Tmux on the other hand, consumes only tens of megabytes of memory.


Hey, there are no memory leaks that I'm aware of (there were a few, but we plugged them in recent months). If you know differently, I'd appreciate an issue report.


If you run e.g. btop or bpytop in a separate zellij tab, zellij will eventually gobble up all your memory and die.

In the beginning I wa very entusiastic and switched from tmux to zellij on remote machines, but as I usually have btop running in a tab it would die in a day or two, so now I'm back to using tmux on remote machines and reserve zellij for local (and make sure I don't run btop in a tab).


(Does HN have an indentation limit, I can't seem to reply to imsnif…)

I'm always running the latest zellij, but I'll start btop in a tab right away and see what happens.

I did mention it in https://github.com/zellij-org/zellij/issues/1625#issuecommen... and noticed the issue is still open, so I haven't tried btop in zellij since v0.36.0.


Keeping track is hard sometimes, I saw it again in the issue as you mentioned. :)


I'm like 90% sure this was fixed - if you'd be willing to try with a recent Zellij version, that would be great.

Otherwise, I'll try your reproduction myself and will fix if I can reproduce. Thanks.


I'm now running v0.37.2 on a remote machine with 3 tabs: a shell, syslog spooled by lnav, and btop. To me it looks like it grows by 2 kB RAM every minute. I am logging to a file with timestamps, and we will see the results tomorrow.


In the course of less than 12 hours zellij grew from 93 MB to 1227 MB in roughly 2 kB increments per minute. Closing the tab running btop will release the stolen memory.

I will append a comment to the Microsoft GitHub issue mentioned above a little later.


Thanks! If you could also specify how you measured it and attach some debug logs (there are instructions in the issue template) that would be great. Because my instance has run overnight without issue and I'd love to be able to reproduce this.


I entered a comment ( https://github.com/zellij-org/zellij/issues/1625#issuecommen... ) before I read your comment here. Please let me know if that is sufficient.


Yeah, and it does flicker a bit etc.

But I still use it all the time now — I found it so much easier to get up to speed with relative to tmux. And it's getting better all the time, so I'm happy to invest in it...


Leaks like crazy on macOS.

For WebAssembly plugins, I also wish they used Extism, which is kinda the de facto standard for this.


Yeah and sudden unexplained crashed made me stop using


We can ask it complex questions and see how the neurons activate similar to an MRI. I bet someone in OpenAI is doing it right now.


Be very careful with MRI studies : https://www.wired.com/2009/09/fmrisalmon/



> it's pretty much game over

Not if it takes the computational capacity of the entire world to simulate a brain with an iq of 65.


Why bother simulating a brain? GPT-4 scores 155 on the verbal section of the WAIS III.

https://www.scientificamerican.com/article/i-gave-chatgpt-an...


He's a fine actor. He just happens to look and act like the middle aged guy next door so he gets overlooked.


Just package virtualbox in a midrange android phone with an OS image that does what you want. Maybe some port forwarding to make phone calls and stuff.


Valve should try their hands at it. Steam deck already makes up ~40% of linux desktop installations. By the end of this year, it should be more than half of all linux installations.


> Steam deck already makes up ~40% of linux desktop installations

Do you have a source for this? This sounds a bit hard to believe, and I can't find a source. The sources I found show that within Steam installations, Steam Deck users are a significant share, but not the majority [0]

[0] https://www.gamingonlinux.com/2022/06/steam-deck-already-hit...


That's 20% of total energy consumption.


Didn't apple just release a VR headset with 4k displays for each eye?


Yes but those displays are stretched over a much wider field of view. When I sit on my couch and look at my TV it is covering maybe 30 degrees of my FOV. A VR headset typically would like to have 100+ degree FOV, which means a 4K VR display will have way less fidelity than a 4K TV.


Right, but presumably you would need insane pixel density to achieve 4K at that range?


This is the fundamental struggle with VR displays. Human eyes have very good visual fidelity and it would be real nice to match or exceed that with a VR headset. This presents many technical challenges.


Yes, it is around 3400ppi. This has been achievable for a bit in very small displays (these are 1.4in), although I believe there are difficulties with anything larger.


> You will need at least 85-100GB of memory

RAM or VRAM?


you need 94gb, does not matter which RAM.


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