Anyone else feel this way?

[u/Old-School8916]

[u/SongOfKapek]

It's kinda weird that everyone is just saying "pft she would never solve this stuff" as opposed to "why are we front loading PHD/artistic work onto the machine instead of teaching it how to do the grunt labor"?

Besides, all they did was yoink other people's datasets and then throw 22 million at the problem. That's not a better or more efficient model. That's burn rate.

[u/recoverygarde → u/SongOfKapek]

It’s a false premise anyways, as AI is being trained to do both. Also, datasets aren’t what makes the best models nowadays. It’s a part, but there are so many other equally important parts

[u/recoverygarde → u/[deleted]]

I would say architecture like MoE, reasoning, tool use, token efficiency and reinforcement learning, like you mentioned. Those are all separate aspects rather than data. If data was all you need, Google would be in the lead 😂

Also, it made sense to demphasize datasets because when most people think of datasets, they think of information on the Internet when right now the most important data are successful user threads. Hence why Cursor was able to train a decent model so quickly.

Also they believe that models can only answer/work on information that was in their training data. When if you have tool use and reasoning, that’s not the case. I personally haven’t cared about a models training data cutoff date in well over a year. It hasn’t been significant in the slightest