Sending an AI response communicates more than just the response itself:
1. "I'm not entirely sure, but this is what it says to save you some time."
2. "You didn't ask the question precisely because you are not an SME, but I reworded it using the jargon that would allow the AI to answer better and here is the response."
3. "This response is AI, but in general my other ones are not"
These are somewhat valid reasons, but I think most of us have seen the use of pasting AI responses that are simply a laziness of communicating.
If you're trying (1), it's easier to say "I don't know, maybe <available ai> can answer". It doesn't save any time to ask an AI that the other party is equally equipped to ask. It just saves the responder time from being genuinely helpful.
If you're (2), at least explain this (or include the prompt so it's self evident and a teaching moment). Of course, if you're a SME, maybe you also have the knowledge to just answer directly - see 4.
For (3), why reply at all: see 1.
For (4), saying this associates your own authority and knowledge, and is valuable, but the omission of such disclaimer makes it indistinguishable from 1.
Sometimes people ask questions on HN off handedly while making some kind of argument where the questions can easily be answered by plugging them into a Google search box. And then I wonder why didn’t they just do that? Usually they don’t do it because it causes whatever argument they are making to implode quickly. I’m guessing they aren’t anti AI they just don’t want to know. It’s not even a “do you trust the AI or not” since the AI is just able to quickly find and present basic data. The fact that their question can be answered quickly and easily is what they find offensive.
At work I’ll use AI to answer colleague questions and then wonder why they just didn’t use it instead. It’s usually just a training issue, the answers are usually right enough to unblock them at least.
The order returned from the Index Scan is not the ordering requested by the user, so there would still have to be a full (or topk) Sort over the dataset returned from the index scan, which could negate the gains you get from using an Index Scan; PostgreSQL itself does not produce merge join plans that merge a spread of index scans to get suffix-ordered data out of an index.
Spiel Des Jahres is a prize they give every year to a bunch of board games. Don't look at very old board games, but some of the modern ones: https://en.wikipedia.org/wiki/Spiel_des_Jahres
As for Go, I was tempted, but it's also very abstract, I do like some kind of theme in my board games.
A board game well integrated with the theme gives great vibes.
Some of the games great from there:
- Sky Team, discovered right there on the wikipedia page: for 2 players, me and my wife spent countless hours on it. Very simple rules yet so damn fun
- Azul up to 4, simple rules and a lot of depths. Place tiles on a board while stealing from others the stuff they want to use
- Kingdomino is so simple yet choosing the piece (some form of draft) requires thinking ahead so many turns!
- Dominion is still a great game: deck builder with simple rules. Didn't think that was possible? It is!
A lot of the children games are also great (this is for families with kids)
Some nominated are also great, even if they didn't win
Spiel des Jahres (Game of the Year) is a boardgame award that notably favors family-friendly accessibility. If you're seeing the award on the box, you can be confident that even if the strategy can potentially get really deep, you can still break this out to have a fun time with both grandma and your 12 year old cousin.
One of the values of doing your own research is it forces you to speak the "language" of what you're trying to do.
It's like the struggle that we've all had when learning our first programming language. If we weren't forced to wrestle with compilation errors, our brains wouldn't have adapted to the mindset that the computer will do whatever you tell it to do and only that.
There's a place for LLMs in learning, and I feel like it satisfies the same niche as pre-synthesized Medium tutorials. It's no replacement for reading documentation or finding answers for yourself though.
This seems like a difference between learning styles. You seem to champion learning by reading. I’d argue using an LLM to build a toy or tool and learning that way is just as valid.
The lack of syncing doesn't bother me, because the purpose of taking notes always falls into one of these categories:
1. I read the code to get an idea of how something works. The code is there to make examples/variable names concrete, but I don't need to know the exact implementation.
If the notes need to sit in the code, usually that's because the answer spans multiple methods (eg "what does an e2e request look like?"). A set of comments on outdated code is always good enough for me.
Otherwise, a lot of times the answer can be summarized in one line (eg "where is the state tracked?" -> in FooBarClass). These can go into personal notes.
2. I need to know the implementation and it is complex and hard to follow.
If I need to know the implementation, either it is because I'm actively working on it, or I need to make [complex idea] more concrete in my head.
If it's the former, usually I'll have memorized it by the time I read through it.
If it's the latter, by the end of it I'll have gotten the main idea and it's fine to forget the implantation details.
It's really helpful with MongoDB Query Language (also MQL). Document models without a rigid schema and a less intuitive API are where this stuff comes in real handy. MongoDB's GUI Compass already shipped a feature to generate queries and aggregation pipelines from natural language.
1. "I'm not entirely sure, but this is what it says to save you some time."
2. "You didn't ask the question precisely because you are not an SME, but I reworded it using the jargon that would allow the AI to answer better and here is the response."
3. "This response is AI, but in general my other ones are not"
4. "I trust the AI's response in this scenario."