334 karma · joined January 20, 2014
This article sounds like the professor was reprimanded by higher powers and tried to dig themselves out of a hole for having a badly structured grading system.
Students should be encouraged to use AI in their learning, because they will anyway. The understanding should be that they will be assessed in supervised environments so they need to learn the work either way. This gives the students incentive to learn without fear of using the best tools available to do so, and provides evidence to the powers that they actually did so.
I use nixvim for generating my neovim config (and I have a flake output for running that on MacOS where I don't use nix a lot) although I've been pairing back my plugins lately as I find I'm spending less time in the editor.
You can build your entire system from a worktree and merge if it works or boot the old generation if it doesn't. This is great for trialing new kernels, NixOS releases, or alternate Window managers, and rolling back is trivial.
One downside is that there is only one stable NixOS at a time, and no LTS. However in practice I haven't found this to be an issue across multiple desktops, servers and SBCs.
Currently updates from the schools are spread over multiple sources: paper notes, email, sms, "news" and "calendar" in school app (which are not kept in sync), and Facebook. Different schools use different apps.
Additionally the channels are often noisy, with messages about groups my kids don't belong to, and "helpful tips" like how to pack healthy lunchboxes. These notifications come in during the day while I'm working, get dismissed due to the low SNR and then the useful ones often slip through unnoticed.
Definitely an area that is ripe for disruption, but as others here have commented, I don't feel confident about Google being the provider.
https://github.com/deadbringer17/Copperbrain
They have similar names, seem to solve similar problems and both have first commit within a few days in July. One is Python and the other Typescript though and they don't seem to be forks.
Meanwhile I'm shipping tons of new features, upgrading outdated systems and delivering real value. But I do worry.
I have a repo for kiosk appliances that can build an SD card image for a specific device in a fleet (so no on device configuration is required) but it can also push out updates or changes at runtime. NixOS isn't perfect for embedded devices yet but works well for cases like this in my experience.
ISC License
Copyright (c) 2010-2022 Broadcom Corporation
Copyright (c) brcmfmac-freebsd contributors
Based on the Linux brcmfmac driver.https://chatgpt.com/share/68e5e68e-00c4-8011-b806-c936ac657a...
I also found it interesting that despite me suggesting it might be a password generator or API key, ChatGPT doesn't appear to have given that much consideration.
nricy.jd t.fxrape oruy,ap. majro
3 groups of 8 characters, space separated followed by 5 for a total of 32 characters. Seemed like text from a password generator or maybe an API key? Maybe accidentally pasted into the URL bar at one point and preserved in browser history?I asked ChatGPT about it and it revealed
Not a password or key — it’s a garbled search query typed with the wrong keyboard layout.
If you map the text from Dvorak → QWERTY,
nricy.jd t.fxrape oruy,ap. majro → “logitech keyboard software macos”.The most jarring was probably maps - other things like email, messaging etc could be delayed until I could reach a computer but not knowing how to get somewhere right now was problematic and required planning in advance.
I usually kept my smart phone in my car and did a sim swap on the occasion that I really needed it.
For your first task - give it smaller steps along the way that you can validate. Provide context where possible (like docs for st7789, examples of other zephyr projects). Use Opus instead of Sonnet for tasks that are on the edge of it's capabilities like this. It will still make mistakes, be prepared for iterating on the design and providing feedback.
For your font example, you always need to validate the output of the LLM, but did it still save you time? If so then I consider that a win. If not, give it the task that it's good at (ie generating the surrounding code and definitions) and then fill in the font data yourself.
Essentially, match the size of the resonance chamber in your mouth to the note you're trying to bend to. This is different for every note you bend. You can find the right size by making "hissing" noises while breathing in (without harmonica) and matching the pitch.
I've got x86 servers running NixOS that are deployed using Colmena, but it seems to fall apart when I add cross compilation into the mix.
Edit clarified car radios are battery powered
There are situations where AI is good enough, other cases where you need more accuracy, and others still where you should be reading the reference directly.
AI is improving quickly though, and context windows will allow for summaries to be tailored to each end user.