I agree that the species concept is a bit of a mess but how do you conclude that these two populations can still interbreed?
From the article I do not get the same suspicion. Even though they mention the "sister species" is 1200km removed this might be true while being a "finished" allopatric speciation.
From the paper:
"Our fossil calibrated mitochondrial clock analysis estimates the most recent common ancestor of C. congoensis and C. satanas existed ~4.27–5.78 Ma. In an additional analysis that used the same secondary calibration point as Roos and Zinner [36], we obtained younger divergence estimates by approximately 1 million years (3.44–4.73 Ma)."
This is such a nice fix but then you install it's set it up to launch on start and forget about it. 5 years later the bug has been fixed for 4 and I still have tho script record a random pixel every 10 seconds.
Never know how to know that the hacky fix is no longer needed
Maybe someone can explain: in image generation some models are already using rectified flow. Which was hailed as the next big thing. Are we going to see discrete rectified flow models next or is that unlikely?
I've also started using typst for some projects.
I am slowly getting used to the syntax. But it's a process for me.
I also still have latex projects/docs
Someone asked for the model you use but I am also curious how you handle ambiguous IDs. Not everything is clear cut especially when it comes to fungi and bugs.
Inaturalist uses second opinions what's your solution?
Edit: cool idea for the app btw, I always call inaturalist my Pokémon deck already so I think it's a nice new angle :)
What's the advantage over using Polars for the same task?
It seems to me the natural competitor here and I vastly prefer the Polars syntax over SQL any day. So I was curious if I should try duckdb or stick with polars
I am using socat right now to achieve this translation but it is rather slow. So o hope a proper solution using tool might be more powerful. But it seems it requires at least a bit more networking insight than what I have at this moment.
It's an opportunity to learn something new for me
Right now I simply rent a hetzner machine including a v4 ip to route the traffic to my V6 services.
Wait this looks interesting. I am a biologist so I might get the terminology wrong. Would this allow me to run a ipv4 to ipv6 and back service?
I got some services with only ipv6 addresses and want clients with only ipv4 (sadly still exists) to at least be able to reach them. So could I dedicate a machine to translating for them using this tool?
I am speculating here but as it genomics data I assume it's information such as: gene count, epigenetic information (methylation, histones etc)
Once you do 20k times a few post translational modifications you can come to a few columns quickly.
Usually this would be stored in a sparse long form though. So I might be wrong.
I agree, I used omz a while now but I have since also realised that the features I uses are so basic, it really does not warrant a whole software project as a dependency.
So I went and had Gemini make me a zsh config with the features I actually use. Took 15 minutes to get all the autocompelte, aliases and search functionality and done.
I don't quite understand:
Instead of using the phones GPS to let me simply chat with people around me, which would be great during traveling or commute, I need to choose the place I chat at?
This seems super counter productive in my opinion. It creates way more friction that I want.
Maybe I want to save a location I have been to as a chatroom, sure but my primary interest would be to have my location determine the chat. So if I enter a university building: boom university chat.
I enter Cern: boom Cern chat.
The hard part would be to not just use rectangles but actually make the shapes meaningful. I don't want to walk past a high school or live next to one and then be included in that chat. So yeah. Tricky
100% agree, I am still shocked that the models are not open sourced. It's the data from the community and I feel it goes very much against the spirit of the community to keep the machine learning part, which is very central to the app, so secret.
As far as I understand they do try to keep the heat around for the next decompression. As of course they need it.
But I could not find what type of heat storage they use.
Ultimately they "only" seem to need to store it for 12h, right?
Python, NGS, ML