Models are increasingly showing their ability to extrapolate into the human unexplored (math proofs being the most apparent). What gives you confidence the absurdity of life is uniquely difficult for models to source?
> you are basically looking at a whole system prompt just describing the new language
whats wrong with this? You may be over-indexing on the need for large quantities of examples. These days self-play through RL is far more effective and data (not compute) efficient.
same can be said for a lot of things tho. e.g. nature used to be fun but then we discovered it all :’( I miss when ships literally sailed into the unknown and found surprising and novel things like hot peppers and pineapples
I agree fully. Hyundai has a mockup that starts to get there (different era, but same concept) called the N vision 74[1], but I doubt we'll see it in market anytime soon. The unfortunate reality IIUC is that modern cars (electric vehicles) have certain aero restrictions (for mileage) that heavily limit design options.
you're right, this is actually correctly placed! I was confusing the orientation. I live right around there and recognize the M&T bank in the photo on the left, so it can't be down by 9th
looks cool! one bit of feedback: make your demo gif get to the point faster. either practice typing a bit quicker or speed it up 2x for the typing section
on Bun's website, the runtime section features HTTP, networking, storage -- all are very web-focused. any plans to start expanding into native ML support? (e.g. GPUs, RDMA-type networking, cluster management, NFS)
we've discovered some kind of differentiable computer[1] and as with all computers, people have their own interests and hobbies they use them for. but unlike computers, everyone pitches their interest or hobby as being the only one that matters.
one thing I've learned in my career is that escape hatches are one of the most important things in tools made for building other stuff.
dropping down into the familiar or the simple or the dumb is so innately necessary in the building process. many things meant to be "pure" tend to also be restrictive in that regard.
what makes you say this? modern LLMs (the top players in this leaderboard) are typically equipped with the ability to execute arbitrary Python and regularly do math + random generations.
I agree it's not an efficient mechanism by any means, but I think a fine-tuned LLM could play near GTO for almost all hands in a small ring setting
sure, numerous examples can be shown to say smart play does help. but, would you argue the net benefits of smart play are identical between a sport like basketball and racing?
I wouldn't deny that (and probably should have caveated this in my OP), but compared to a basketball or football team, the benefit of smart play doesn't seem as significant compared to doping up and pressing hard.
http://github.com/bwasti
[all posted thoughts and comments are my own]