grchelp2018

grchelp2018 t1_j899me3 wrote

A lot of knowledge work is simply knowing stuff and knowing what to look for and where. Our current setup doesn't allow for robot lawyers standing in front of a jury maybe but they can absolutely replace the associates doing the grunt work of finding precedents/cases, drafting and proof reading briefs etc.

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grchelp2018 t1_ixv09vz wrote

This only works for computation that can be easily parallelised. We still build supercomputers that cost 100s of millions of dollars.

When it comes to things like the JWST, a large amount of cost is in the r&d, making sure that it works reliably in space etc. It wouldn't cost the same amount to build another one now though it would still be expensive. For chips, you have high demand to amortise the costs.

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grchelp2018 t1_ixmmpoh wrote

Software dev with no ml background here. I'm trying to implement semantic search. User enters a query and I should return the top 3 closest results. Right now, I'm basically splitting all my text into sentences and storing the embedding of each sentence. Is this scalable? Is there a better way? Are there pre-trained models that can generate embeddings for paragraphs and larger bodies of text?

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grchelp2018 t1_iuht264 wrote

His arguments sound like problems of tesla. Having multiple teams, dealing with different supply chains, the cost etc are all tesla problems. Elon doesn't want to deal with it so he convinced Karpathy. To be honest, I'm not sure how much he believes it himself. He isn't going to disagree with Elon in public.

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grchelp2018 t1_isu8rsd wrote

I don't know if the europa clipper mission is as exciting as a manned mars mission but I do think that europa should be given as much importance as mars. IMO if there is life to be found, it will be in one of these ocean worlds. Rather than looking at far away exoplanets for signs of life and habitability, we should make europa a priority.

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