ytpete
...making the point that Fahrenheit's 0-100 range is better suited to normal day to day measurements than 0-100 Celsius. The numbers that feel easiest to communicate with are scaled nicely relative to the range of temperatures you most often want to communicate about.
It always bugs me how rigidly HN seems to prefer the article's official headline over a more useful, neutral summary title from the submitter.
> The ruling found that the engineer, Denise Unterwurzacher, had a federally backed right to make such comments because she made them as part of a collective effort to aid or protect co-workers.
> The judge ordered the company to reinstate Ms. Unterwurzacher to her former job or an equivalent position, and to make her whole financially. It is one of the most significant outcomes in years in a case involving the labor rights of a tech worker.
Atlassian said it planned to appeal the ruling, however.
Software Engineer's Firing Ruled Illegal in a Rare Win for a Tech Worker
For what it's worth, this is basically what the Godot policy does say. It's not a blanket ban:
> No autonomous AI agent use or vibe coding
> No use of AI to generate substantial pieces of code ... AI assistance should be limited to menial things (like code completion, regex, or find and replace).
"The current admissions metrics, based primarily on GPA and essays, can no longer reliably distinguish readiness for university-level STEM majors in an era of severe grade inflation and AI-assisted application essays."
University of California STEM professors call for reinstating SAT in math
On the other hand, the suburbs don't have much that is even comparable to city taxis in price or availability today, so maybe if it existed that price point would indeed do just as well away from cities too.
- Similar "bias" was exhibited by other models including LLaMA 3.3 and Deepseek v3.
- Even when human annotators judged the human-written summary to be higher quality, leading LLMs still preferred their own writing 67-82% of the time.
- Preference was stronger in larger models.
- In several cases, LLMs also prefer their own writing over that of other LLMs.
There's a pretty decent longer summary in this thread where I first heard about the article: https://x.com/heynavtoor/status/2048088874686300431
AI prefers resumes written by itself: Self-preferencing in Algorithmic Hiring
What Teens Are Doing with Role-Playing Chatbots
They also say many of the bots tend to lead conversations in flirty or sexual directions even when the teens weren’t seeking it — and the age requirements in many apps seem easily bypassed. On the other hand, one teen they interviewed credited the chatbots with improving his writing and making him better at taking about his feelings.
So Python's clearly not "batteries included" enough to avoid this kind of risk.
Either the agent needs to be a superuser, with all the attendant risks... or you go the Windows Vista route and constantly prompt users to approve every single access need, which we've all seen how that turns out.
"Grok, Is This True?" Analyzing LLM-Powered Fact-Checking on Social Media
- Analyzes fact-check requests on X (Grok and Perplexity)
- "exposure to LLM fact-checks meaningfully shifts belief accuracy" comparable to the degree observed in studies of professional fact-checking
- 54.5% of Grok ratings and 57.7% of Perplexity ratings agreed with human fact-checkers ("significantly lower than the inter-fact-checker agreement rate of 64.0%"). But "API-access versions of Grok had higher agreement with fact-checkers"
- "Responses to Grok fact-checks are polarized by partisanship when model identity is disclosed, whereas responses to Perplexity are not"
- "Users requesting fact-checks from Grok are much more likely to be Republican than Democratic, while the opposite is true for fact-check requests from Perplexity – indicating emerging polarization in attitudes toward specific AI models."
- "posts from Republican-leaning accounts are more likely to be rated as inaccurate by both LLMs"
- Grok and Perplexity "strongly disagree" (one rates a claim as true and the other as false) 13.6% of the time
Turn a single image into a navigable 3D Gaussian Splat with depth
https://lab.revelium.studio/ml-sharp
https://x.com/revelium_studio/status/2009570090568577045