@signulll Personal ai agents change the dynamic though. You can have very different thought processes based on the kind of questions you ask the bots. It's active thinking rather than the passive shit feed from social media, and hence quite refreshing
Your comment is so far from reality. Men can assume women have it on easy mode because they reduce a woman's entire existence to dating perks. Navigating career ceilings, societal double standards, biological clocks, periods, and then the expectation to carry both the family and the workforce is anything but easy.
@vodka_boy Very simple. Just keep running the model through a fixed internal eval set every day/week. If you notice a drop in performance with the same model, you know something fishy happened to that model.
@Thom_Wolf The bot looks amazing. And great design. But tbh I'm still not sure from the video, what is its utility? Is there an easy way to look at some list of what all it can do?
@zdogmode Garbage input, garbage output. If the person doesn't understand how to design well, they won't be able to differentiate bad design code from good one. Hence they can't iterate on it well enough, unlike someone who knows coding well.
While some words of reassurance from bots can feel good, we don't really crave that, we crave the fact that another human chose to spend finite time giving you some words of comfort. If you knew every reply on your feed was generated by an LLM, the psychological reward would be zero. Validation requires proof of conscious attention.
@sattyyouneed Anything built on human status games.
We solved chess 25 years ago, and professional chess is more popular now than ever. Nobody buys tickets to watch engines play engines.
There are very few people in the world right now who know how to run a LLM on a laptop locally. There are millions (~billion) who know how to run Chatgpt, Claude, Gemini, etc. Distribution matters. Companies distributing stuff to millions/billions need to prioritize safety. Safety research is not pointless. It helps us understand the issues and helps educate people about them. By the time these local LLMs reach a mass, people are already educated.
@mcuban Multimodal sensors, smart glasses, and robotics will eventually bridge the data gap, but keeping humans in the loop shouldn't just be a technical safeguard. it must be an intentional design principle if we want AI to genuinely serve human outcomes. Humans ftw.
the bottleneck in modern medicine isn't a lack of data, it's clinical bandwidth.
If a doctor receives 300 daily LLM chat logs, it doesn't improve care, it just creates notification fatigue. For AI to genuinely bridge the outpatient gap, it must act as a clinical triage filter, not an unconstrained daily journal.