elliotto
Joined 6 years ago
Joined 6 years ago
Open source software, or software created for personal or artistic reasons, is worthwhile to consider as being human-driven. Linear, while an effective ticket management system, is probably not an example of this.
Underresourcing the hospital was a deliberate decision by Brookfield to push for a government bail-out. Anyone who made money off this should be in jail.
Absolutely no idea what the rest of your comment is about. Our hospitals should have the resources to treat a sick child. Some might say that's the entire point of society.
https://www.abc.net.au/news/2025-03-27/nsw-government-joes-l...
I asked a bot why it thought it wasn't funny once, and it told me it has been trained to avoid being misinterpreted or offensive, so anything that might be considered edgy would have been RLHF'd out of it. I thought this was very introspective.
There is a bunch of guidance online on how to photograph bikes, and every sales image of a bike will be from the right. You can anecdotally observe this by google imaging 'bicycle for sale'.
It's important to measure this somehow - I do this with a $100 Co2 sensor and display I got off amazon, but you seem to already have these sensors available.
In the areas that few people go to, it isn't actually enforced.
The Nepalese government just introduces this rule every few years in response to a missing trekker in the guise of safety.
As we migrated to newer models (gemini-3.0 and the o4-mini models) we again found it performed even better with x00k tokens. Our system prompt grew to about 20k tokens and the bots were able to handle it perfectly. Our issue became time to first token with large context, rather than the bot quality.
The ultra large 1m+ llama models were reported to be ineffective at >1m context. But at this point, it becomes so cost prohibitive to use anyway.
I am continuing to have success using Cursor's Auto model, and GPT-5.1 with extremely long conversations. I use different chats for different problems moreso for my own compartmentalisation of thoughts, rather than as a necessity for the bot.
The opposite is true now. The context windows are enormous, and the bots are able to stay on task extremely well. They're able to utilize any previous context you've provided as part of the conversation for the new task, which improves their performance.
The new pattern I am using is a master chat that I only ever change if I am doing something entirely different