Charts like these are a reminder that people don't understand cats as well as I would like
A cat does all the same things a dog does, they just don't give it away for free. You gotta earn the respect, more like you would a person!
My cats follow me from room to room, love being held, love to play, and all sorts of good stuff
Amazed an NYPost article isn't getting more scrutiny on Lemmy
But either way it appears to be verified by multiple other sources
You can find the site here: https://www.pay.gov/public/form/start/23779454
Not a food crime, and definitely just an ad from a new account
Doubled my monthly contribution to NPR. Doing my small part
I can't say whether it can execute, but the metadata is a privacy concern if you are posting online. Depending on the camera taking the picture it can include the model of the phone, date, or even GPS information
Copying from the x-post
Research paper here: https://metr.org/Early_2025_AI_Experienced_OS_Devs_Study.pdf
I think these are interesting findings, they definitely conform to my experience, but I'd want to always have more data and larger sample sizes.
One point in particular stood out to me - the lack of LLM context. I have a new person on my team (junior level) that uses AI for everything, and it's so obvious that the LLM is getting tripped up with the lack of context. Not all the required information is in a single repository, and it needs additional info like the documentation and spoken architectures that aren't explicitly documented, historical choices as to why we make decisions in a certain way, or even just style guides. The LLM context window just isn't large enough right now to be a truly effective programmer for large, complex projects
Research paper here: https://metr.org/Early_2025_AI_Experienced_OS_Devs_Study.pdf
I think these are interesting findings, they definitely conform to my experience, but I'd want to always have more data and larger sample sizes.
One point in particular stood out to me - the lack of LLM context. I have a new person on my team (junior level) that uses AI for everything, and it's so obvious that the LLM is getting tripped up with the lack of context. Not all the required information is in a single repository, and it needs additional info like the documentation and spoken architectures that aren't explicitly documented, historical choices as to why we make decisions in a certain way, or even just style guides. The LLM context window just isn't large enough right now to be a truly effective programmer for large, complex projects
Thursday Murder Club was just such a genuinely fun read. There was something so light hearted about it I loved
That's actually a really good point you've made here. It's easy to defend the shoes as a parent because you're the one who (1) understands the rationale behind buying them and (2) made the decision to buy them
I wonder if a good decision in this scenario is to just give the child a shoe allowance and let them pick. If they want Nike's they will have to find a pair that fits the budget
Abundance by Ezra Klein and Derek Thompson. My understanding is that it is a woefully misunderstood book, and that people keep getting angry with the content without understanding it (or worse, without reading it).
So far, I actually really like it just a handful of chapters in. I think they make incredibly salient points and have very convincing rationales.
Agreed, this is a relatively simple "tool" as the LLM parlance goes. It's what Model Context Protocol (MCP) is designed to facilitate
To verify, the author should try the same prompts on a local LLM with no tools enabled and most likely the LLM will respond with some nonsense
I'm torn - while I'm not a fan of the new look, I'm also viciously anti-lawn-grass so I can't complain too much.