Tagged: work-culture

David Oks:

Kyocera was founded in 1959 as a producer of ceramic insulators for cathode-ray tubes; today it manufactures not only industrial ceramics but also printers, smartphones, ballpoint pens, kitchen knives, solar PV modules, lens components, industrial cutting tools, automotive camera modules, electronics components, semiconductor packaging, biocompatible tooth and joint replacements, UV-LED curing systems, LCD systems, medical products, and lab-grown gemstones. Or another e-chuck maker. Sumitomo Osaka Cement, as you might have been able to deduce from the name, produces cement and ready-mixed concrete; but it also produces optical components, measuring instruments, industrial ceramics, artificial marine reefs, cosmetics and nanoparticle materials.

Long fascinating read.

Benedict Evans:

Many people would like to analyse which jobs, companies and industries are most exposed to AI, and assign scores, build charts, and map that against the progress of LLMs. I think this is mostly impossible: you don’t know how the jobs will change, you don’t know what else will change around this, and you can’t measure work like that anyway.

Lots of commentary out there on the impact of AI on jobs, mostly on the lines of “AI will lead to massive job losses” (tch. Dario).

This is a more nuanced take from Evans. It may feel a little unsatisfactory given the crux of the argument is that nobody can predict where this will go (a common theme of much of Evans’ writing), but I strongly believe it’s a very good framework for thinking about this.

Recommended reading. Don’t just take the conclusion, nod, and move on. Developing a deep appreciation for why you should disregard most predictions about AI is important to actually do the said disregarding.

Arnav Gupta:

But the truth is that these layoffs, even if they they are not because AI is replacing you, and even if they are some form of AI-washing. These layoffs are still because of AI. And these layoffs will continue till we learn to use AI. Till we learn to convert AI-tokens into outcomes and not just input. Till we learn to re-align the speed of "alignment" with the new speed of coding. And till we figure out, beyond our 2 good and 8 stupid ideas, 10 more ideas that we can chase with our increased productivity.

This is a very refreshing take on the layoffs in large tech companies. It’s the best take I’ve read on this.

Denis Stetskov:

Five to ten years from now, we’ll need senior engineers. People who understand systems end to end, who can debug distributed failures at 2 AM, who carry institutional knowledge that exists nowhere in the codebase. Those engineers don’t exist yet because we’re not creating them. The juniors who should be learning right now are either not being hired or developing what a DoD-funded workforce study calls “AI-mediated competence.” They can prompt an AI. They can’t tell you what the AI got wrong.

Ignore the click-baity title. This is a well-written and well-argued post on how the software industry might be hurtling towards a grim future, the kind of present that the West’s defence industry has found itself in as an unexpected war broke out between Ukraine & Russia.

Mo Bitar:

What we do is because the deal is so damn good, we change ourselves to make that deal acceptable.

And what I've figured out now is that I'm unwilling to change myself to make that deal acceptable.

I could feel the emotions as I watched the video. Well worth the time.