My M3 Max can burn through battery much faster than my M1 Max ever could.
And some apps are really inefficient. New Codex app drains my battery. If you are using Codex I recommend minimizing it, since it’s the UI that uses most power.
This is the voice model, which doesn’t have any «thinking» or «reasoning» phase. It’s a useful model for questions that aren’t intended to trick the model.
I’ve used it for live translation with great success. It tends to start ignoring the original instructions after 20 min, so you have to start a new conversation if you don’t want it to meddle in the conversation instead of just transferring.
Mine is mounted to the fridge, so it's not seeing as much use as it otherwise would. Screen does get smudges and they are more noticeable compared to the regular iPad screen. Not so much that it's a problem to be honest. I wipe it down every few weeks, and that's fine with me.
I tried the iPad with Nano Texture and didn’t really like the rainbow effect that shows up on white brackgrounds. So I ended up returning it.
A while later I had an idea to mount an iPad to my fridge so that I could check the weather, add things to my shopping list, play music, etc. I bought the rather expensive iPad with Nano Texture screen and it has been amazing to use. There is a big window opposite the fridge, and without the nano texture the glare from behind makes it hard to read what’s on the screen.
Not sure I would enjoy nano texture on my MacBook. For outdoor use I found that Vivid is great to turn up the brightness using the extended range of HDR that Apple doesn’t otherwise allow me to use.
When I took my first database course one topic was IO performance as measured in seek time on regular old hard drives.
You can’t really optimise your code for faster sequential reads than the IO is capable of, so the only thing really worth focusing on is how to optimise everything that isn’t already sequential.
I’m curious about if the model has gotten more consistent throughout the full context window? It’s something that OpenAI touted in the release, and I’m curious if it will make a difference for long running tasks or big code reviews.
I hate the new electric busses from China. Their acceleration is much better and braking effect is also stronger.
Bus drivers in Norway are binary people. They either press the accelerator or they press the brake. Most drivers call it leg day, because you spend the entire day pushing on these peddles as hard as you can.
Our existing buses have terrible acceleration, which helps a lot with the comfort of the bus ride. But for some unknown reason someone decided that the bendy busses should have the only wheels with power, in the rear of the bus, after the bend. So any slight hill that is slippery from a bit of snow or frost, now becomes a a comedic video of buses trying to drive up before they flop in the middle of the bend and slide back down again.
I don't think anyone is pretending that a Macbook Pro can compare to 8 H100 cards from Nvidia in terms of LLM training or for serving LLMs. But you can buy an awful many macbooks for the price of 8 H100 GPUs.
But if your workload belongs on 8 H100 GPUs then there isn't much point in trying to run it on a macbook. You'd be better served by renting them by the hour, or if you have a quarter million dollars you can always just purchase them outright.
The H100 is just an example, this is true for any workload that doesn't fit on a laptop.
Phishing. Super easy now to send a fake email with a great offer, and have your name and loyalty programme number right there in the email. Much easier to trick someone when your email contains a bunch of personal info that you wouldn’t assume others to have.
«Happy birthday! As a loyal Quantas customer, we would like to offer you a sneak peek of our upcoming Black Friday deals. Consider it a little birthday present from us.»
In Norway I've noticed that stringent requirements for privacy make it much easier to run things in the cloud if the physical location of said cloud is actually in Norway.
So if OpenAI is hosting their services within the borders of the UK, then they would also be beholden to UK law. Makes it easier for the financial sector, government and healthcare to use their AI models than if they would have to send their data to a datacenter in the US.