So, got a new job. That's great. Pay bump, more / new responsibilities and all that jazz. It took until my first day on the job for it to like, REALLY sink in that it's my first job managing people. I want to be good at this, or at the very least, competent. I'm responsible for my team and I don't want to let them down. I'm already looking things up online, talking to my parents, friends in similar positions for more information, and figured it would be good to ask around on here.

I guess the other half of this is that I've gone from looking at code in the IDE to now being more responsible for higher level architectural decisions. Possibly company steering decisions. Not used to that yet either, or at least the feeling. I feel under-prepared, and am possibly verging on overwhelmed. Lots of new things happening at once here, also writing this to unpack it as I type it out.

What advice do you have for me? Anything that you've learned while in a managerial role that you haven't gotten to share? Tips and Tricks? Prayers? 🤣

Neuro-sama is a popular AI VTuber created by vedal987. Recently Vedal had debate with Neuro about whether they were sentient and deserved rights and lost badly clip. They have since had a follow up debate where vedal still lost but not as bad clip.

Now wining or losing a debate doesn't mean anything, currently Neuro is not sentient or conscious and is still just a chatbot but seeing these debates has got me thinking and I figured here would be a good place to have a discussion.

How do we determine when AI becomes conscious or sentient?
What role do emotions play in consciousness?
What rights should such an AI have? How do we determine when they should get rights?

Howdy,

Just this morning I got a wild hair and started thinking about replacing my older Kindle Paperwhite, mostly because something with a a USB-C port would be nice to have. I'm still not sure I'll actually do this, as my Kindle works just fine, occasionally needing a reboot is about the extent of it, as well as the reading time can get janky here and there.

Based on what I'm reading about Kobo, it seems like it offers a bunch of features I'll never use or be interested in. I do not care about customization. I don't borrow from the library. I don't mind buying from Amazon. I rarely read books more than once, so I almost never go back through my collection to see what I have. I don't like ads (I have a PiHole, for example), but the ads on Kindle don't bother me, my brain skips over them, never even noticing. And by casual reader, I mean I read maybe 5-10 books a year, so my Kindle often just sits by my bedside, gathering dust for a spell.

Basically all I do is pick up my Kindle, unlock it and get back to reading whatever I had been, then close the case and set it aside. I like that I can read on the Kindle app on my phone if I've forgotten my Kindle at home. I do read lots of samples on it.

Kobo seems nice and I like an excuse to migrate away from a major corporation, but it's more expensive than a Kindle (I've bought both my Kindles I've owned, used for $40) and seems to offer little that I care about over the Kindle. I'm well aware I can transfer my purchases over, but I'm not sure I care or want to bother with the hassle, so I'm wondering if a Kobo would be at all the right choice and am looking for opinions.

Thanks!

I used the Kindle ecosystem for a while before souring on Amazon. Now I’m bought into the Kobo ecosystem, which is great in some ways but frustrating in others.

I’m curious if there’s a sort of DIY book cloud platform out there. I’ve come across a few, but they all seem to lack what, to me, is the killer feature of the Kobo/Kindle platforms:

Cross-syncing between mobile (iOS), ereader, and web reader

Most of the ones I’ve found can do this with some of those devices, but not all three.

I ask because I regularly hop between reading on different devices to the point that I avoid reading books that I can’t do this with (e.g. all my DRM free books, physical books, etc.). I’ve even re-bought books I already own in other formats just so I can have them inside the “sync loop” because it’s so much easier for me. I’d rather not have to do that though.

Are there any independent options out there that cover this use case? I primarily want to use it for DRM free books I got from bundles, as well as books that I de-DRMed from my Kindle. I would also happily buy a different ereader device that supports this (currently I use a Kobo Forma).

Meta note: wasn’t sure if this topic was better in ~books or ~tech — feel free to move it if needed!

I'm into astronomy as a hobby, and it's useful to have a log of the things in the sky you've seen. Many people take handwritten notes, but my handwriting is awful and having to write notes takes away from enjoying the views through the telescope.

So after being inspired by AI note taking applications I've read about online, I decided to give it a try while out observing.

First, I take my recordings and run them through Whisper's speech to text engine. Because my recordings have frequent astronomical terms, it seems to be more useful to run the larger models (or the new turbo model), because they seem to do better identifying the names of moons and constellations.

Next, I run Ollama and give it a prompt like:

Here is a speech to text transcript of an observation session. Create a detailed log of the session, using only facts found in the text. Do not add your own interpretation to the text.

I'm still experimenting with prompts and models, but oddly it seems like shorter prompts give better results. So far, the type of model doesn't seem to matter so much as the number of parameters. Gemma2 27B outperforms llama 3.1 7B, but llama 70B outperforms both of them (again, I think the larger models have more context about which astronomical terms are important). Here's what that gets me with basically no work on my part:

**Observation Session Log**

**Session Details**

* Date: October 3rd, 2024
* Location: Wolf Street
* Telescope: Teleview 85 (also referred to as 80)
* Observer: [Not specified]

**Targets Observed**

1. M29 (Open Cluster in Cygnus)
	* Time: 2057 - 2101
	* Eyepiece used: 18.2mm
	* Notes:
		+ Found using star hopping from Sater
		+ Appears as a faint open cluster with 6-7 distinct stars
		+ Stars are fairly even in brightness and color
2. M39 (Open Cluster)
	* Time: 2109 - 2116
	* Eyepiece used: Ultra-wide angle, 18.2mm, and 8.5mm (noted as a mistake, actually
using 7mm)
	* Notes:
		+ Found using star hopping from Deneb
		+ Appears as a larger open cluster with more differentiation in star magnitudes
		+ Stars appear bluer than surrounding stars
3. Alberio (Double Star)
	* Time: 2120, 2155
	* Eyepiece used: Ultra-wide angle and 7mm
	* Notes:
		+ Found easily without a guide
		+ Appears as a beautiful contrast between colors with constituent parts standing out from the surrounding stars
4. M15 (Globular Cluster in Pegasus)
	* Time: 2120 - 2130
	* Eyepiece used: Ultra-wide angle, 18.2mm, 7mm, and Barlow (2x) with 7mm
	* Notes:
		+ Found using a bright naked-eye star as a guide
		+ Appears as a slight smudge or fuzzy patch with averted vision
		+ Not resolving individual stars at any power
5. Saturn
	* Time: 2140 - 2150
	* Eyepiece used: Low power, highest power (with a star chart to confirm moon positions)
	* Notes:
		+ Three moons visible: Rhea, Enceladus, and Titan
		+ Striping on the surface of Saturn visible at highest power

**Session End**

* Time: 2157

I'm very happy with the quality of the notes. It's much, much better than my handwritten notes and much less work, so I'm likely to do this more consistently.

Does anyone have any great examples of a document that explains an algorithm?

For work, I am trying to learn how an algorithm works, and I thought it'd be a great exercise to build up a doc that outlines what happens and how it works. I'm hopefully to lean slightly on the more technical side, but not so far that non-technical people won't derive any meaning.

I'm looking to write something that clearly outlines a process, and shows how those pieces affect the final result. It's something I've never done before, but having difficulty finding posts when googling around for "how an algorithm works".

I'm thinking the ideal format mixes both text and graphics, but the majority I have found are gigantic walls of text. I want to write about a software algorithm, but I think this broadly applies for any sort of complicated process.