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#models#previous#more#always#months#training#version#maybe#different#improvement

Discussion (8 Comments)Read Original on HackerNews

firemelt37 minutes ago
https://isaiprofitable.com/

I like this one better

ealready_value17 minutes ago
Oh look, the answer is the same when I looked a couple months ago. Interesting
Topology1about 1 hour ago
Mom said it was my turn to post this
glensteinabout 4 hours ago
>Agent-2, more so than previous models, is effectively “online learning,” in that it’s built to never really finish training. Every day, the weights get updated to the latest version, trained on more data generated by the previous version the previous day.

That seems to me to be a natural progression, from discrete models to models that are just continuously improved. Maybe we'll end up with different models with different rates of improvement rather than static differences in performance, and methodologies for that improvement will be the thing we care about. Maybe over time, even benchmark tests will be primarily concerned with that kind of efficiency.

I think a huge debate right now is the relative value of the "frontier" models from Western companies at the cutting edge, vs distilled versions of those models that are good enough and exponentially cheaper coming from China. But a paradigm of 'always training' means an always active, always advancing frontier, which is a stronger moat than a one-off model that's more advanced for a few months.

sigalorabout 4 hours ago
I wonder when the people will get that intelligence is not only directed at the external, but only really starts when you look at the internal (joy, pleasure, traumas, taboos, awkwardness, abuse etc.). Look up the word "interoception".
Ydarbleojabout 1 hour ago
Sorry, but the notion that creative writing and robotaxi's exist as proof of anything is like saying my child can drive and write; and while true, the measure of that ability is not at the level of the best humans. It's average at best.
27183about 4 hours ago
> It’s informed by trend extrapolations, wargames, expert feedback, experience at OpenAI, and previous forecasting successes.

In other words: bias. Tons and tons of self-congratulatory, glue sniffing bias.

weezing37 minutes ago
At which point do we get to fight in the anti clanker uprising?