- Inter font

- all caps section headers

- Lucide icons

- em dashes, of course the em dashes

- bubble status badges (of course with all-caps "IN PROGRESS" and "COMING SOON" that mean the same thing)

- Uncited claims like "Most founders are overconfident in the 70-90% range" and "Most people score between 0.20 and 0.30"

- No less than FOUR blog articles all published April 4

None of these points is by any means a dealbreaker. And after all, I suppose a product should be judged on its merits and the value it delivers to its users, not on the tools used to create it. But together, the frontend bears the unmistakeable generative AI "smell" that telegraphs that the human(s) directing the tools building this app might be optimizing for speed over rigor and quality (further supported by the volunteer QA/QC happening in the comments), and may only be as good and reliable as the uncritically accepted outputs of a $20/month coding assistant.

Or a photo of my freshman dorm room during exam season. Subpar image quality, lousy lighting, etc. but so many memories, positive and negative, are elicited by that fleeting glimpse from an era of excitement, boredom, stress, uncertainty, and optimism, not knowing where I was going in life, when I'd ever look back at that snapshot, but deciding on a whim to grab it during a break from cramming topics now long forgotten.

But I roll my eyes at the idea of injecting my likeness into a short clip depicting random over-the-top action sequences, no matter how photorealistic, because I've never wanted to do that.

Admittedly I am basing this on pure vibes: I'd bet that adding AI to the healthcare environment will, on balance, reduce this number, not increase it.

If your end goal is to show an audience of nontechnical stakeholders an overview of your dataset in a static medium (like a slide), I would suggest you do the cluster labeling yourself, with the help of interactive tooling to make the semantic cluster structure explorable. One option is to throw the dataset into Apple's recently published and open-sourced Embedding Atlas (https://github.com/apple/embedding-atlas), take a screenshot of the cluster viz, poke around in the semantic space, and manually annotate the top 5-10 most interesting clusters right in Google Slides or PowerPoint. If you need more control over the embedding and projection steps (and you have a bit more time), write your own embedding and projection, then use something like Plotly to build a quick interactive viz just for yourself; drop a screenshot into a slide and annotate it. Feels super dumb, but is guaranteed to produce human-friendly output you can actually present confidently as part of your data story and get on with your life.

If they speak up, maybe. If they stay silent, definitely not.

I had to guess, I'd guess you aren't a parent or spend much time interacting with children :)

Also, auto-lock reduces theft and carjacking risk, which is nice.

The United States has been an annual net exporter of natural gas since 2016, 7 years after the end of George W's administration: https://www.eia.gov/energyexplained/natural-gas/imports-and-...

This is increasingly ironic :)

On AI's struggles with hands: do humans have four or five fingers? Why not both!? https://offline.kids/activity/diy-jigsaw-puzzle/

    You're a brilliant expert at clear, effective, and responsive teaching and explanations of topic X, which I'm studying. Here's my assignment. Draft Y questions to test my understanding and assess my current level