They keep tasking these LLMs with things that traditional programming solved a long time ago. There are already vending machines run by computers. They work just fine without AI.
Honestly the computer controlled vending machines are already over-engineered since many of them play ads when you walk up. The last customer-focused feature added was credit card support, and that just needs a credit card reader and a minimal IoT integration. They really shouldn’t even have screens.
Why are they… why are they having autocomplete recommend medical treatment? There are specialized AI algorithms that already exist for that purpose that do it far better (though still not well enough to even assist real doctors, much less replace them).
Even more surprising: the droplets didn’t evaporate quickly, as thermodynamics would predict.
“According to the curvature and size of the droplets, they should have been evaporating,” says Patel. “But they were not; they remained stable for extended periods.”
With a material that could potentially defy the laws of physics on their hands, Lee and Patel sent their design off to a collaborator to see if their results were replicable.
I really don’t like the repeated use of the phrase “defy the laws of physics.” That’s an extraordinary claim, and it needs extraordinary proof, and the researchers already propose a mechanism by which the droplets remained stable under existing physical laws, namely that they were getting replenished from the nanopores inside the material as fast as evaporation was pulling water out of the droplets.
I recognize the researchers themselves aren’t using the phrase, it’s the Penn press release organization trying to further drum up interest in the research. But it’s a bad framing. You can make it sound interesting without resorting to clickbait techniques like “did our awesome engineers just break the laws of physics??” Hell, the research is interesting enough on its own; passive water collection from the air is revolutionary! No need for editorializing!
Several years ago I created a Slack bot that ran something like Jupyter notebook in a container, and it would execute Python code that you sent to it and respond with the results. It worked in channels you invited it to as well as private messages, and if you edited your message with your code, it would edit its response to always match the latest input. It was a fun exercise to learn the Slack API, as well as create something non-trivial and marginally useful in that Slack environment. I knew the horrible security implications of such a bot, even with the Python environment containerized, and never considered opening it up outside of my own personal use.
Looks like the AI companies have decided that exact architecture is perfectly safe and secure as long as you obfuscate the input pathway by having to go through a chat-bot. Brilliant.