Ask it ten times to make list of 20-30 random words
This is true on ootb models but not the universal rule. You could adjust the temperature all the way up and get something way more random, probably to the point of incoherence.
The trick is balancing that with keeping the model doing something useful. If you’re clever you could leverage /dev/random as a tool to manually inject randomness while keeping the result deterministic.
Though to be honest I don’t usually use a recipe or cook anything. I cube a block of soft/silken tofu, dump on some chili oil, add some kind of vinegar (and maybe sesame oil if I have it), and eat it raw and cold.
You could probably do it with any kind of sauce you like and put it on rice if you’re feeling fancy
Photos are the same as most other data, you can store them pretty easily long-term in a physical medium. Of course, capturing an image is much easier and more convenient with a digital device, but that doesn’t mean it has to live digitally indefinitely. It’s simple enough to have an instant digital camera with a built in printer and access to a high quality scanner.
If you held a gun to my head I could pick out a few dozen personal photos that I own that are worth saving physically. If you allowed me a modern flash drive’s worth of storage (64-128GB, ~5000 good quality images), I could pretty easily store every picture worth a second look from my entire lifetime.
Apple’s marketing driven perception that every single person needs a cinema quality camera (and cinema sized storage) in their pocket is ludicrous. Only a tiny fraction of people actually truly need that. Let them borrow that gear from a library if we want to preserve fair access.
To be honest I don’t have any personal digital information that I give a shit about. It’s value is only derived from its ability to identify + track me, either for my convenience or for the highest bidder’s. Computational liberty is only an issue because we’ve made everything digital by default and that mindset has leaked into critical social functions (taxes, law, logistics, healthcare, etc…).
Software and data bloat is more astronomical than most people realize. Only about 10% of persisted data is ever touched again (don’t look up the ecological implications). Amazon could capture 90% of all compute hardware and the entire human race could get by just fine on 10%. We wouldn’t have access to niceties like app stores full of niche apps, 24MP phone cameras, 4k movies, 10 sluggish layers of software abstraction, 15 years of photos you never look at, etc…
But you could run a simple message server on basically any scrap of IoT e-waste. A highly available static website can be hosted with an old phone and a solar panel. Any device (fridge/watch/calculator/pregnancy test) can run Doom. All of Apollo 11’s source code is a fraction of the size of most web pages.
We’re continously expanding our hardware usage for infinitesimally small gains. We should demand that our governments legislate digital austerity for dozens of reasons, just pick what resonates best for you. Personal privacy, energy usage, ecological damage, corporate capture, information rot, brittle supply chains, national security, etc…

Research shows that 90% of stored data (photos, documents, emails, etc.) becomes unused after just three months. Digital waste isn't just a nuisance, but also impacts businesses significantly, both financially and in terms of productivity, not to mention energy wastage. We'll dissect why so much dig
I feel the bad feedback trope is inverted in 2025. Devs will release a game, get a solid audience, then completely change mechanics or style or direction for no apparent reason. The audience complains (pointing out what they like in the original release), the devs tell them to kick rocks and the game shrivels up and dies.
cough ^Battlebit^ cough
My shameful secret is admitting that LLMs are great for things like getting comfortable with a programming language. They’re generally trained on the same publicly available samples as these courses and the conversational extrapolation is great for identifying concepts you forgot the technical terms for (ie. “How would I do this in python: [Java code]”)
Vibe coding sucks, but walking through some examples with an LLM and a REPL can save hours of navigating docs or Hello World blog posts.