I’m not trying to criticize EVs, for those who can afford them.
But there material heavy, and if you need range, expensive at the moment. Not everyone can afford that.
And a range extender is a great way around that, especially in budget vehicles.
Yeah.
It’s a good stopgap, though. We can’t all get EVs immedately, but we could get more on the road quickly with this approach.
Well, most of us do.
But its much more expensive.
And (with current battery tech), a pure EV ultimately yields a car that’s much, much heavier.
And a range extender can be absolutely tiny since the “average” horsepower needed for typical driving is actually quite small. I think its also more palatable to potential buyers with EV range anxiety.
EV-drivetrain hybrids (eg an EV with a small battery + ~3 horsepower range extender) are a good idea, though.
It’s kind of the best of both worlds. And insanely fuel efficient, even if one uses that generator all the time.
ICE drivetrain hybrids are insane, though. It was the only option at the time, but it’s also basically the worst of both worlds.
I think the problem is marketing, though.
Try explaining the hybrid distinction to a layman. Or to a snooty, higher end EV buyer turning their nose up at anything that takes gas.
Could this ever be “self hosted” on a phone, in the future? Eg run as a web app, basically?
That would get around the issue of rate limiting for those of us with no home server.
That’s just a far flung idea though. Either way, this is amazing.
Eh, most of the poison is the dark patterns in the UI, the relentless engagement optimization, algorithmic recommendations, the tracking, the ads, and so on.
This short circuits all of that.
You could still watch toxic influencers, but it’s not funneling you towards that anymore.
True.
They tried, though. That was at least the premise of AV1.
Perhaps that’s why AV2 has steam behind it; it’s a “second attempt” to avoid the patent trolls.
The licensing.
Legally risky, too.
Unfortunately its implementation is spread through tons of hardware. Even my camera uses h265 for stills, as HEIF files, whereas not a single one I know of will do AVIFs or AV1 video (which is complex to implement as an ASIC).
One could say h265 takes the “easy” way to encode video, whereas AV1 (and presumably AV2) have to go out of their way and pursue complex alternatives to avoid patents.
It’s the last step, though.
I’m not making demands of free software; all of that development is appreciated.
But it does seem to be CPU-first, like dav1d and previous efforts. And I know from previous projects, GPUs have many constraints that make offloading a CPU-centric project difficult, unless it’s the #1 priority from the start.
I’m just saying it’d be interesting another AV2 project that shot for pure, or as-pure-as-possible, GPU shader decoding. It would make AV2 a whole lot more accessible than CPU-centric decoding.
What about some generic GPU decode?
$15k would get you a used AMD server, a 5090 or a set of 3090s, and enough leftover cash for electricity to just run a 1T parameter LLM at home. Plus, it’s yours.
And that’s hilariously inefficient.
It’s completely nuts to me that people pay Anthropic per token, at that rate. I think 1 whole year for GLM’s coding plan was a flat $30, or something.
Very interesting read, thanks.
One common theme seems to be that “better is the enemy of good,” with (for example) pushback against mixing coal with waste for gasification, using cement plants or power plants for CO2, using biomass plant waste and such.
I see Bio/e-fuels as a “intermediate step” into the future, anyway, so I think trading a little sustainability for practicality is way better than nothing.
Yes, though that’s true of other methods.
Another big factor is that its very inconvenient to buffer vs tanks on either end, for transmission breaks that take time to repair, uneven energy supply/demand and stuff like that. Or even just capacitance.
A big old tank of oil on either end is cheap.
I’m not trying to shill for hydrogen or anything (I don’t like hydrogen), but this is definitely an issue.
I am not a power engineer, but I do know the capital costs for the wire and components all along the way is massive. They’re complicated, and they require a lot of expensive (and probably carbon intensive) materials.
Basic physics dictates it. Its more complicated than small scale DC/AC current with negligible transmission time you’re likely thinking of.
Maintenance is a pain, too. HV wires (especially the crazy DC ones) are extremely, extremely dangerous and basically can’t be near anything.
I’m not sure about installation labor costs vs a pipeline though.
Power transmission is hard.
The wire, the complex components, keeping it all in phase and steady and not exploding, the maintenance…
I cannot emphasize this enough. People tend to trivialize this when talking about remote production, but moving electricity long-distance is basically the hardest part. And pipes really are dead-simple in comparison.
It’s also why local production is so appealing.
…Regardless of the code assistant, I’m not seeing any cause for alarm in my personal usage, yet. Feature requests and issues are getting closed, even urgent security ones that shouldn’t have been posted in that manner:
https://github.com/RsyncProject/rsync/issues/871
https://github.com/RsyncProject/rsync/issues/882
Seems like business as usual:
https://social.treehouse.systems/@thesamesam/116662824873341085
One thing I will say on rsync is that regressions aren’t new with it. It does something hard: it has to deal with symlinks. Releases have often had regressions for a long time, especially for security fixes, and it long predates LLMs, because symlinks are hard. Of course seeing a gazillion Claude commits still makes me uncomfortable, but it’s important to see what’s new as well.
In practice, they’re not very good because of broken FP16, broken kernels, high idle usage and a bunch of other things.
Same with the AMD MI50 and MI100. Looks great on paper, not practical IRL, unless you want to pay a whole team of software devs to fix them for you.
Better to just save up for a 2080 TI or 3090, sadly.
No.
Even the biggest open weights models are trained on pennies compared to OpenAI and Claude. They just don’t have the hardware to be so wasteful.
In fact, the Nvidia GPU ban was the best thing to ever happen to “small” AI devs. It made them thrifty.
MoEs can be very fast with hybrid inference. I run Xiaomi Mimo 2.5 (a 310B model, 116GB weights) on my single 3090 + 7800 CPU, and it outputs faster than I can read it.
It’s also easier to fit long context, if you need that.
It’s best to use the ik_llama.cpp fork for that, though. It gives a huge boost to hybrid MoE speeds.
Here’s a incomplete list:
https://gr.ht/aur_pkg_list.txt
I know some on Lemmy here use the RuneScape launcher.