The maker of ChatGPT had made progress on Q* (pronounced Q-Star), which some internally believe could be a breakthrough in the startup’s search for superintelligence, also known as artificial general intelligence (AGI), one of the people told Reuters. OpenAI defines AGI as AI systems that are smarter than humans.

Definitely seems AGI related. Has to do with acing mathematical problems - I can see why a generative AI model that can learn, solve, and then extrapolate mathematical formulae could be a big breakthrough.

I saw one suggestion which was to so away with male and female competitions, and instead have “open” and “restricted” comps. Open would be available to anyone, male or female, while you could set up as many restricted comps as you needed for the particular sport or activity with whatever rules make sense. So the 100m sprint might have Open, Restricted - Testosterone, and Restricted - Height - with whatever T level or height in centimetres decided by the relevant authority. Whereas something like weightlifting might have Restricted - Weight as it’s own class. The idea being any gender can compete provided provided meet the restrictions in place to make an interesting/fair competition within that bracket.

I find it interesting that DALL-E still doesn’t understand text - look at all the random Daschuund spelling in the generated images. It knows what the word should look like, but has no framework to interpret or distinguish text from the other elements of the image. It looks like trying to spell in a dream.

Where it gets really challenging is that LLMs can take the assignment input and generate an answer that is actually more educational for the student than what they learned d in class. A good education system would instruct students in how to structure their prompts in a way that helps them learn the material - because the LLMs can construct virtually limitless examples and analogies and write in any kind of style, you can tailor them to each student with the correct prompts and get a level of engagement equal to a private tutor for every student.

So the act of using the tool to generate an assignment response could, if done correctly and with guidance, be more educational than anything the student picked up in class - but if its not monitored, if students don’t use the tool the right way, it is just going to be seen as a shortcut for answers. The education system needs to move quickly to adapt to the new tech but I don’t have a lot of hope - some individual teachers will do great as they always have, others will be shitty, and the education departments will lag behind a decade or two as usual.

This is a good summary; as a reddit exile myself who exclusively used Sync, I think it’s worth emphasising that Dawson has done an amazing job of making the transition from reddit to lemmy pretty seamless from an app design point of view. I can set my views and filters up identically as they were in the Reddit version of the app, and the lemmy experience becomes essentially identical to reddit.

There’s definitely a conflict between “paid closed source app” and “FOSS fediverse”, and there’s arguments to be made about whether user revenue should be directed to server expenses to maintain communities or front end app development to attract more users, which I think will be interesting to see play out. But at the end of the day Sync makes lemmy “useable” in a way that replicates the reddit experience, which is what a lot of migrants were after - other apps (while arguably more feature rich in terms of the fediverse) just didn’t quite hit the dopamine-feed the way Sync does.