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lifeisloving • today at 12:03 AM • 2 replies • view on HN

Training costs are not in free fall, and not every "post training" process is equal, Everyone does this differently. The costs certainly haven't gone down, to train a new 10T param model from scratch, like at all.

You cannot point at Xiaomis tiny model and compare it to training a 10T param model. The levels of dunning krueger are getting out of hand.

You also arent calculating the salaries of the people involved, of which there's only a few thousand worldwide in your hiring pool.


Replies

overfeed • today at 4:27 AM

> You also arent calculating the salaries of the people involved, of which there's only a few thousand worldwide in your hiring pool.

There were probably a few dozen 20 years ago, and the existing pool grew from somewhere. AI (nee machine learning) is not rocket science - but it is a science, so it rewards those who are literate, curious, can hypothesize, experiment and learn from results to gain an intuition. I bet most statistics-adjacent professionals (millions, worldwide) can move laterally into AI research and excel at it. Nevermind AI has been among the most-in-demand undergrad programs since ChatGPT dropped. The only limited pool is for celebrity AI talent.

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verdverm • today at 2:10 AM

you haven't cited any examples, nor acknowledged this is how everything in computing has gone, DK is a two way street I suppose

stable diffusion is an excellent example, the price to train today's or yesterday's frontier is the analogy, many more people will be able to train up what we have today, especially as more of the pipeline is open sourced and the knowhow distills

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