4 ms·

I'm more amazed that the hardware industry has hoisted our shit software into usable state. Just bravo. I can only imagine the people working on the actual chi

I'm more amazed that the hardware industry has hoisted our shit software into usable state. Just bravo. I can only imagine the people working on the actual chips are screaming in silence somewhere at the complete waste of energy we've made.

srgpqt 3y ago
It goes both ways. Shit hardware is papered over with firmware/driver hacks.
- picture 3y ago
  Reading the silicon erratas from various companies.. it's a wonder that anything works https://www.st.com/resource/en/errata_sheet/es0182-stm32f405407xx-and-stm32f415417xx-device-errata-stmicroelectronics.pdf https://www.st.com/resource/en/errata_sheet/es0182-stm32f405... https://www.nxp.com/docs/en/errata/IMXRT1170CE.pdf https://www.nxp.com/docs/en/errata/IMXRT1170CE.pdf https://www.nxp.com/docs/en/errata/IMX8_1N94W.pdf https://www.nxp.com/docs/en/errata/IMX8_1N94W.pdf
ThrowawayR2 3y ago
They are. Patterson & Hennessy at their Turing Award lecture back in 2017, when they started talking about where future opportunities for increased speed were going to come from, the very first thing they took a (polite) dump on was how software was written very inefficiently: https://www.youtube.com/watch?v=3LVeEjsn8Ts&t=2183s https://www.youtube.com/watch?v=3LVeEjsn8Ts&t=2183s The old canard that programmer time was worth more than processing time that bad coders quote is less and less true by the year; SWEs who are able to wring better performance out of less hardware resources are going to become more valuable in the future.
- oofnik 3y ago
  > SWEs who are able to wring better performance out of less hardware resources are going to become more valuable in the future. As much as I'd like for this prediction to come true, I think it's wishful thinking. Compute capacity continues to increase exponentially while (human) cognitive resources, for all practical purposes, do not, which means less efficient code will continue to be the more economically viable option as far as I can tell. Even with AI, where we're essentially trading compute (used for running code) for extended cognitive resources (used for writing code), what incentive exists to channel those resources into writing faster code rather than writing the same code faster?
  - sfpotter 3y ago
    It’s a literal waste of energy. LLMs draw a tremendous amount of power. They enable problems to be solved in a low effort, careless sort of way, but this neglects the power efficiency of our own brains. We can think through and implement better solutions consuming only a tiny fraction of the power. In a world where we’re running up against climate change and finite resource constraints, that is valuable, it’s just not self-evident yet. We’ll first have to crash headlong into a wall to realize it.
    - oofnik 3y ago
      We can use AI to help us design and build a functional fusion plant, which we can then use to power more datacenters running ever bigger LLMs to help us design more efficient datacenters to run bigger LLMs to help us build ... yeah this is going to be one hell of a century.
  - deleted 3y ago
    [deleted]
shitpostbot 3y ago
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JohnFen 3y ago
> I can only imagine the people working on the actual chips are screaming in silence somewhere at the complete waste of energy we've made. As a dev, this bothers me a great deal. We have miracle machines on our desks and in our pockets, and 80% of the capabilities of that hardware are pissed away by terribly inefficient software.

srgpqt 3y ago

It goes both ways. Shit hardware is papered over with firmware/driver hacks.

picture 3y ago
Reading the silicon erratas from various companies.. it's a wonder that anything works https://www.st.com/resource/en/errata_sheet/es0182-stm32f405407xx-and-stm32f415417xx-device-errata-stmicroelectronics.pdf https://www.st.com/resource/en/errata_sheet/es0182-stm32f405... https://www.nxp.com/docs/en/errata/IMXRT1170CE.pdf https://www.nxp.com/docs/en/errata/IMXRT1170CE.pdf https://www.nxp.com/docs/en/errata/IMX8_1N94W.pdf https://www.nxp.com/docs/en/errata/IMX8_1N94W.pdf

ThrowawayR2 3y ago

They are. Patterson & Hennessy at their Turing Award lecture back in 2017, when they started talking about where future opportunities for increased speed were going to come from, the very first thing they took a (polite) dump on was how software was written very inefficiently: https://www.youtube.com/watch?v=3LVeEjsn8Ts&t=2183s https://www.youtube.com/watch?v=3LVeEjsn8Ts&t=2183s The old canard that programmer time was worth more than processing time that bad coders quote is less and less true by the year; SWEs who are able to wring better performance out of less hardware resources are going to become more valuable in the future.

oofnik 3y ago
> SWEs who are able to wring better performance out of less hardware resources are going to become more valuable in the future. As much as I'd like for this prediction to come true, I think it's wishful thinking. Compute capacity continues to increase exponentially while (human) cognitive resources, for all practical purposes, do not, which means less efficient code will continue to be the more economically viable option as far as I can tell. Even with AI, where we're essentially trading compute (used for running code) for extended cognitive resources (used for writing code), what incentive exists to channel those resources into writing faster code rather than writing the same code faster?
- sfpotter 3y ago
  It’s a literal waste of energy. LLMs draw a tremendous amount of power. They enable problems to be solved in a low effort, careless sort of way, but this neglects the power efficiency of our own brains. We can think through and implement better solutions consuming only a tiny fraction of the power. In a world where we’re running up against climate change and finite resource constraints, that is valuable, it’s just not self-evident yet. We’ll first have to crash headlong into a wall to realize it.
  - oofnik 3y ago
    We can use AI to help us design and build a functional fusion plant, which we can then use to power more datacenters running ever bigger LLMs to help us design more efficient datacenters to run bigger LLMs to help us build ... yeah this is going to be one hell of a century.
- deleted 3y ago
  [deleted]

shitpostbot 3y ago

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JohnFen 3y ago

> I can only imagine the people working on the actual chips are screaming in silence somewhere at the complete waste of energy we've made. As a dev, this bothers me a great deal. We have miracle machines on our desks and in our pockets, and 80% of the capabilities of that hardware are pissed away by terribly inefficient software.