throwing in my 2 cents: It just replaced pandas for me. It's just so much easier to write sql against csv/json/whatever format data in jupyter/marimo notebooks through duckdb rather than reasoning through pandas. SQL is far more natural for me, and agents also work through it easily.
So this is using deepseek-v4-pro / flash and using claude code as the harness right? That's really good that it works. I'm pretty impressed with how v4-pro is doing, sadly there's no subscription packages so I'm not using it too much. (Wafer used to offer it but now they don't).
Yeh. But wire's storage is based on Cassandra which handles replication of storage. So you could deploy it on local nvme drives as well using a local storage CSI.
That's also how the wire.com cloud is/was run. Large Cassandra cluster on top of EC2 Instance Store as opposed to EBS.
my experience with RustDesk + Tailscale is really good. when i only needed windows remote devices, the Windows Remote Desktop over Tailscale is great. I used RustDesk for access to macOS and Android devices (all over Tailscale) and works great too. No complaints really. Much less hassle to setup than Parsec (latency isn't as good though), and way snappier than AnyDesk through their network. Great tool enabled by Tailscale.
i wish that's for their logging/alert. i definitely gauge model's performance by how much those words i type when i'm frustrated in driving claude code.
It’s actually around 1.5x for the default resolution out of the box and 1.3x for “more space” setting on m1/m2 MacBook Air. 1.1x supersampling on Macs makes it worse because down sampling to pixel alignment becomes a hot mess.
Those numbers of 1470x956 are “points” or “looks like” values, not the size of the frame buffer. The frame buffer for “looks like 1470x956” is exactly 2x that, or 2940x1912. On a 2560x1664 display, that’s a 1.148x scale factor. Again, nowhere near 2x, even on the “more space” setting.
If you’re counting by the framebuffer than the only 2x is the hidpi-forced-into-lowdown like the link suggest. The ratios I’m referring to is the UI scaling against the physical display pixel dimensions.
Apple basically settles into 220 dpi physical displays (250 moc MacBook Pro), rendering UI at a 2x scale as a default, except for MacBook Airs.
goal? yeah. but in reality just timing it right (starting a session at 7-8am, to get 2 sessions in a workday, or even 3 if you can schedule something at 5am), i rarely hit limits.
if i hit the limit usually i'm not using it well and hunting around. if i'm using it right i'm basically gassed out trying to hit the limit to the max.
ok it's a bit late but i think a big part is the non-verbal thing you're putting out.
my story is me and my wife moved to another country a few years ago for my study. after 4 months moving there, she already know and conversed with the people working the apartment and some neighbors. while i mostly just exchanged cursories and nods and glances. then one day we just walked out together and the same people i passed earlier just says hello and converse and stuff with my wife and me. yes she's very much an extrovert but i can see people are way 'more open' and my wife has that too. me on the other hand do have 'i don't want to bother you so please don't bother me' vibe.
man this is cool. this is what i want since i read about fly.io's sprites.
slightly related to this, and i'm not familiar with linux sandboxing/containerization in depth, but any similar turn key solution for linux desktop/server? ideally i have something like sprites/shuru but on my own linux/ubuntu server instead of in the cloud.
We built SlicerVM for this in 2022, but not just for sandboxing. It's for servers + API launched VMs (i.e. what we now like to call a 'sandbox'). Feel free to take a look, a lot of our early users are saying things like this.
Same, I really want to use sprites (for me and my whole team) but every time I try to set up, I run into weird issues. Last time I got in some state where trying to launch Claude froze the whole VM every time.
i agree that is annoying but seems like anthropic's stance is that the task/agent should be provided an environment to write the file in the output you provide or provided a skill.md description on how to do that specific task.
personally it's a blurry line. most times i'm interacting with an agent where outputting to a file makes sense but it makes it less reliable when treating the model call as a deterministic function call.
There's definitely many ways to improve the output of the AI, and provide it extra hints. Also, some AIs are made for a specific use-case. Maybe I should rephrase it and say that those benchmarks are more about the single-reply intelligence of a model, and more like an AGI test then for specific use-cases.
