The trajectory is such that current L2 70B models are easily beating 3.5 and are approaching GPT4 performance - an A6000 can run them comfortably and this is a few months only after release.
Nah the trajectory is not in favor of proprietary, especially since they will have to dumb down due to alignment more and more
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Reminds me of the article saying open ai is doomed because it can only last about thirty years with its current level of expenditure.
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Cost reduction in the field is orders of magnitude potential. Look at llama running on everything down to a raspy pi after 2 months.
There are massive gains to be made - once we have dedicated hardware for transformers, that’s orders of magnitude more.
See your phone being able to playback 24h of video but die after 3h of browsing? Dedicated hardware codec support
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The trajectory is such that current L2 70B models are easily beating 3.5 and are approaching GPT4 performance - an A6000 can run them comfortably and this is a few months only after release.
Nah the trajectory is not in favor of proprietary, especially since they will have to dumb down due to alignment more and more
https://www.anyscale.com/blog/llama-2-is-about-as-factually-accurate-as-gpt-4-for-summaries-and-is-30x-cheaper?trk=feed_main-feed-card_feed-article-content
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A 30B model which will be fine for specialized tasks runs on a 3090 or any modern mac today.
We are months away from being affordable at current trajectory
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