My points are about what it’s like current with removable batteries in cameras with current technology. Battery usage is dependant on usage to some extent. For casual use my cameras last weeks on a battery and even shooting all day e.g. in a studio, I would only get through one battery. Modern cameras also have usb-c charging and can be used whilst you do that, so that’s an option too, though less practical in my view. Yes, camera batteries are proprietary and it would be better if they weren’t, though they are generally the same across similar cameras from the manufacturer and the same in the successor cameras. Many mirrorless cameras are water resistant (with the right lenses) so the can be used in heavy rain, though not under water without a housing. Action cams like the GoPro 13 Black are waterproof with a removable battery.
Both of those things are also important in cameras, there is even sites that compare the size such as https://camerasize.com/. Cameras have got smaller in recent years and it makes the size makes a big difference to whether you take it with you on not or fits in your pocket or not for compact cameras. Ricoh’s gr4 camera is 0.5mm thinner than the previous model (gr3). Cameras are essentially smaller than they would be otherwise because they have replaceable batteries. People who need at more power usually use several batteries rather than use a bigger camera with more capacity.
Cameras also need to withstand drops for similar reasons to phones, it’s in you hand and you could drop it, also tripods can fall over, car mounts fall off etc.
It’s been long enough that people of forgotten what’s it’s like. Cameras still have replaceable batteries, there are several benefits:
I can have two (or more) batteries, if it runs out I just change it. I don’t need walk around with a USB battery pack and cable hanging off the device preventing me from using it properly.
I can put the battery on charge somewhere and leave it, even if not completely secure, because just the battery not the device. This way my expensive device and my data is not at risk.
I can use 40+ year old cameras, because I can just put a new battery in. This is not something you can do with newer device, e.g. and iPod and you can’t even find anyone who will fit them for the older models.
Battery tech moves on. There are now some batteries with charging ports on them. Other batteries offer more capacity than the original ones. Apple even did this once for me, when MacBook Air batteries were fairly easy to replace, I had mine replaced (it wore out) at the shop and they put a slightly bigger one in, which was the standard on the newer models.
The battery in my iPhone 11 pro (6.5 years old) is still basically fine as long as I charge it every day. None of my previous smart phones were able to keep enough charge to be useful after 3-4 years.
The title of site should probably have "for gaming" at the end as it doesn't consider GPUs for compute such as the A100 or the GTX 580 3GB that AlexNet was trained on.
Waterfox is dependant on Firefox still being developed. Mozilla are adding these features to try to stay relevant and keep or gain market share. If this fails, and Firefox goes away, Waterfox is unlikely to survive.
First off I’d say you can run models locally at good speed, llama3.1:8b runs fine a MacBook Air M2 with 16GB RAM and much better on a Nvidia RTX3050 which are fairly affordable.
For OpenAI, I’d assume that a GPU is dedicated to your task from the point you press enter to the point it finishes writing. I would think most of the 700 million barely use ChatGPT and a small proportion use it a lot and likely would need to pay due to the limits. Most of the time you have the website/app open I’d think you are either reading what it has written, writing something or it’s just open in the background, so ChatGPT isn’t doing anything in that time. If we assume 20 queries a week taking 25 seconds each. That’s 8.33 minutes a week. That would mean a single GPU could serve up to 1209 users, meaning for 700 million users you’d need at least 578,703 GPUs. Sam Altman has said OpenAI is due to have over a million GPUs by the end of year.
I’ve found that the inference speed on newer GPUs is barely faster than older ones (perhaps it’s memory speed limited?). They could be using older clusters of V100, A100 or even H100 GPUs for inference if they can get the model to fit or multiple GPUs if it doesn’t fit. A100s were available in 40GB and 80GB versions.
I would think they use a queuing system to allocate your message to a GPU. Slurm is widely used in HPC compute clusters, so might use that, though likely they have rolled their own system for inference.