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In one of Stephen Boyd's lectures on convex optimization, he has some quip like "if your optimization problem is computationally intractable, you could try real
by levocardia 1y ago
In one of Stephen Boyd's lectures on convex optimization, he has some quip like "if your optimization problem is computationally intractable, you could try really hard to improve the algorithm, or you could just go on vacation for a few weeks and by the time you get back, computers will be fast enough to solve it."
I feel like that's actually true now with LLMs -- if some query I write doesn't get one-shotted, I don't bother with a galaxy-brain prompt; I just shelve it 'til next month and the next big OpenAI/Anthropic/Google model will usually crush it.
- user3939382 1y agoTry getting it to write a codepen sim of 3 rectangles parallel parking.
- AbstractH24 1y agoHas the pace of this slown down or I have just lost track of the narrative? Feels like innovation in AI is rapidly changing from paradigm-shifting to incremental.
- owebmaster 1y ago> I just shelve it 'til next month and the next big OpenAI/Anthropic/Google model will usually crush it. 1 month to write some code with LLM, that's quite the opposite of the promised productivity gain
- th0ma5 1y agoExcept here the core functionality changes day to day and hinges on specific word usage.