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z3ugma

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Organic Maps 18 days ago

Just downloaded CoMaps. Why does it start with a zoomed out view of the entire world, especially given that I gave it location services and it shows my current location (in North America). The very first UX experience this app gives is "I am primarily for people interested in maps and geography"

Contrast this with Apple Maps - when you open it, there are 4 big tap controls for actions like "Home" "Work", a search bar, and a map that covers a 1-mile radius around you .

I'd encourage your UX flow to go something more like: request location services > if granted, immediately start downloading their local tileset in the background > zoom to a 20-mile radius around the user

What always gets me about these red team attacks is the same thing that gets me about internal phishing test emails.

My company sent an internal phishing test last week. Several people immediately reported it to a cybersecurity engineer, posted about it in Slack, saying they were surprised that such a sophisticated phishing attack was happening.

I too was surprised - Google is usually much better about catching these kinds of things in the GMail filter before they get through. Oh well, sometimes one slips though. Reported it and moved on

Come to learn that the only reason it made it through is because we let it through _on purpose_.

By analogy to these red team attacks: _theoretically_ someone could rent a car, pose as an employee, and set up a Raspberry Pi in the network.

But who would go to all that trouble?

Theoretically, someone could craft a perfect phishing attack, but who would go to all that trouble? Spray-and-pray, low precision, high surface area, attacks are the ones I end up reading about.

The only reason this attack vector was open is because the red team stood to gain a massive benefit from succeeding in the attack. What real-world actor would go to the trouble and stand to benefit as much?

Maybe we ought to be making little hardware passthroughs that plug into the headphone/mic jack and control them with idk the Caps Lock signal from USB HID to start recording.

It's very cyberpunk eventually...the human operator of the console needs to be able to see and hear the screen and sound, there will always be an interface that can be adapted to a machine, however low-fidelity

Been a huge fan of LibrePCB and especially the improvements in the past 3-4 releases. I have found it generally to be more performant than KiCAD and for building my own footprint and library tooling alongside, LibrePCB's library design paradigm works a lot better to me than does KiCAD's.

I wish it were easier to extend the way the KiCAD plugin system is, but I also have a lot of respect for the developer's approach. High-performance, choose features carefully, everything can be done local or with Git with no cloud dependencies.

I don't really understand what this is for... there is a lot of ML-researcher talk on the GH page about the model architecture, but how should I use it?

Is it a replacement for Kimi 2.7, Claude Haiku, Gemini Flash 3.1 lite, a conversational LLM for the situations where it's mostly tool-calling like coding and conversational AI?

It doesn't come with any RAM? You have to add $140 for 8GB or "bring your own"...so the list price does not represent a working computer?

not re-implement SQLite, I mean "use SQLite as your persistence layer in your program"

e.g. worry about what makes your app unique. Data storage is not what makes your app unique. Outsource thinking about that to SQLite

but it's so trivial to implement SQLite, in almost any app or language...there are sufficient ORMs to do the joins if you don't like working with SQL directly...the B-trees are built in and you don't need to reason about binary search, and your app doesn't have 300% test coverage with fuzzing like SQLite does

you should be squashing bugs related to your business logic, not core data storage. Local data storage on your one horizontally-scaling box is a solved problem using SQLite. Not to mention atomic backups?

At some point, don't you just end up making a low-quality, poorly-tested reinvention of SQLite by doing this and adding features?

I have been using this library for a few months alongside Gemini 3.1 Fast

It's really useful to get an iteration loop going with an LLM.

The OCCP viewer extension for VS Code helps make sure you can see and manipulate the resulting model

I will say I came upon this same design pattern to make all my chats into semantic Markdown that is backward compatible with markdown. I did:

````assistant

<Short Summary title>

gemini/3.1-pro - 20260319T050611Z

Response from the assistant

````

with a similar block for tool calling This can be parsed semantically as part of the conversation but also is rendered as regular Markdown code block when needed

Helps me keep AI chats on the filesystem, as a valid document, but also add some more semantic meaning atop of Markdown