With jupyter notebooks in a devops perspective you could just build a process to export the notebooks to standard py files and then run them.
There are actually a lot of git hooks that will actually expoet/convert .ipynb to .py files automatically since notebooks don’t work great with git.
My understanding is that it’s a difficult feature to support and they can’t guarantee it works well. That’s the only explanation I’ve ever seen, cause to me it’s almost critical for working on a laptop.
I dont get why hibernate isn’t a more popular feature, I use it extensively as I hate having to set everything back up on each restart.
Its also one of my biggest issues with using Linux as it’s usually broken there.
Yeah that’s right, seems my link didn’t populate right.
I also think most people don’t see the market, it’s only got this amount of attention on phones because of the success on steam.
A odd side note, someone was pretty clever and found a way to port the steam version to ios and Android well before the official port - https://retrohandhelds.gg/how-to-install-balatro-on-android-and-ios/. I’ll admit to having used this to play on my phone over the summer, but definitely bought it again once it hit the app store.
Definitely sounds like it could be real. If I had to guess their mounting a drive (or another partition) and it’s defaulting to read only. When restarting it resets the original permissions as they only updated the file permissions, but not the mount configuration.
Also reads like some of my frustrations when first getting into Linux (and the issues I occasionally run into still).
I think you’re missing the point. No LLM can do math, most humans can. No LLM can learn new information, all humans can and do (maybe to varying degrees, but still).
AMD just to clarify by not able to do math. I mean that there is a lack of understanding in how numbers work where combining numbers or values outside of the training data can easily trip them up. Since it’s prediction based, exponents/tri functions/etc. will quickly produce errors when using large values.
Here’s an easy way we’re different, we can learn new things. LLMs are static models, it’s why they mention the cut off dates for learning for OpenAI models.
Another is that LLMs can’t do math. Deep Learning models are limited to their input domain. When asking an LLM to do math outside of its training data, it’s almost guaranteed to fail.
Yes, they are very impressive models, but they’re a long way from AGI.
Just read up more about the systems and always thought they charged you more, didn’t realize that for the time being they are zero interest loans.
Seems unsustainable, but sounds like they’re using the credit card technique of charing the storefront. It’ll be interesting to see where the bnpl industry goes.
Why be the bad guy when you can just enable them.
Am I an idiot or isn’t the “pip vs conda vs poetry” line talking about package management?
This is what I was going to say.
I wouldn’t say worst, but maybe greatest difference in expectation vs reality - “My Time at Portia”.
Cutscenes and voice acting were janky. The UI felt like it was originally an MMO and feels odd for a single player game. The gameplay loop felt tedious and seemed to disrespect the player’s time.
Maybe I needed to give it more time, but for a game that I thought had generally good/great reviews, it wasn’t clicking for me.
With things like wsl, conda has also become less useful. Anaconda is terrible software and the need for conda managed packages is mostly lost outside of the windows OS in my opinion.
Yeah they took that prediction an odd step too far.
Who likes the casting choices? I think I’ve only heard criticism on the casting.
Maybe not the same thing as FPS chess, but a great chess rougelike with guns is https://store.steampowered.com/app/1972440/Shotgun_King_The_Final_Checkmate/
These models are also already open sourced, you can’t stop it. Additionally all of those “requirements” would just mean that AI would only be owned by big corporations.
I feel like one of those isn’t like the others