i have been anticipating this release for some time now. I am an avid user of ecosia and find the results passable in comparison to google. A couple of queries a week I am unsatisfied with and switch to google or a chatbot these days. I hope this new index is also comparable in quality and one step closer to a bit more competition in this market. Sadly, I could not find an official blog post or anything on the qwant news site..

I clicked because i was very curious what this actually is, but it really is just what it says. The problem is, there is no twerking, the girls are just swaying from left to right really slowly which is not really twerking, but that is beside the point. Why are things like this being built? How can someone look themselves in the eyes after this?

this seems very interesting: they got a big sensor dataset and generated some text from that. I guess this involves things like maximum values, mean values, maybe simple trends and things like was the person walking or biking etc. It would be interesting to see if the model identifies things that were not so easily provided in the training data. Otherwise this is just teaching the model to sort of calculate the mean from sensor data instead of using tools to do this

this exact same thing happened in the show bojack horseman, made me chuckle

i think this is quite neat! one feature would improve it for me quite a bit: if i just have a text document open i can easily click and input a character, so it is not much better there. but you could make it so that i can select a character and click and drag across the canvas, basically drawing the characters onto the canvas. that would be more fun imho

> Grok-4 significantly underperformed compared to expectations. Many of its initial responses were extremely short, often consisting only of a final answer without explanation.

this is very weird. given how verbose most models usually are, there must have been something wrong in the system prompt.

also: grok used 89996 input tokens compared to 591624 for o3 high. What kind of tokenizer are they using that compresses the input so much? I suppose all inputs are actually the same, since the math problem + instructions are the same. only difference is the tokenizer or the system prompt. but i suppose it would not make up the difference. is o3 using 500k more tokens for their system prompt?

i do not quite understand this point of view. even if bees suffer tremendously in the industrial complex, then the logical solution would not be to stop eating honey but to source honey from an ethical producer. there are lots of small beekeepers everywhere who treat their bees well and produce high quality honey. they get their hive in a often quiet area near a field or forest and live there mostly untouched until some of the honey is harvested. they also make sure to leave enough for the hive to survive, otherwise you would need to buy again.

i feel like this is the same for other animal products. for a lot of them there is an ethical way of sourcing them, which costs more and you would need to reduce your consumption of it. but this extreme view on veganism and animal products confuses me.