7,455 karma · joined August 25, 2016
The targeted term must be something that is clearly human made, something that sounds undeniably bad and something that is easily understood by everyone at first glance:
_War on Pollution_
Nature is good, pollution is bad. People who pollute are _obviously bad_ and they do bad things. Pollution is wasteful and ugly. Yuck!
Also it's more general than climate change. Ocean plastic is also bad. Chemical, electronic and light pollution etc.
The people who think of chemtrails and 5g waves. They really hate pollution so much, they see it everywhere. Give them a war that they can join in.
For example they tend to be more stable during crisis, because workers tend to vote for lowering salaries/benefits temporarily rather than doing layoffs. So they retain talent better. But they also tend to have difficulty to grow quickly, for obvious reasons.
Besides full on coops, there are also plenty of examples that are hybrids (partially worker owned).
> they would get their face eaten by other more efficient and ruthless corporations
You're possibly of assuming that a company needs to have an adversarial relationship to their workers in order to be competitive. I don't think that's generally true. This approach has advantages in specific situations, but disadvantages in others.
Based on what I understand about how the former works, I would assume that the latter has the same properties and failure modes.
The obvious optimization for the case presented would be to generate all the summaries on a server instead of in the client. Then the totally used compute would scale with the number of articles instead of number of users.
But I somehow managed to have a regular schedule and now I start to sleep at 00:00-01:00 very often, sometimes even earlier.
No idea how I managed to do that. I guess I just did improve many small things, like getting rid of bad habits, being more content, appreciating sleep more, prioritizing things differently.
I wish everyone good, healthy sleep.
I‘ve noticed that some projects have „Claude“ as one of their top three contributors.
If that’s the case, then it’s not necessarily a problem with Azure itself.
Here, something that looks like the thing is a strong signal, as long as the probability is high enough to be useful.
Remember Netflix‘ chaos monkey?
Do you have a similar experience when walking or running (deliberately)?
Walking, dancing or manual labor (for example gardening or cleaning) can all be done in a meditative way.
But these are likely different types of meditation that have different effects. Even just a calm, sitting meditations might be vastly different from another, depending on the meditation object.
Of course there are people who lean into specific types over the others as you describe, but I think many of these activities share a common core and experience.
However, they are still useful in these cases if you know the above and use their output as a starting point to think and ask questions.
But there‘s something psychologically powerful happening with the interaction of AI. I think we overestimate our ability to be rational and underestimate how essily influenced we are.
I feel like this is a very profound insight.
Of course processes like this can become about the immediate utility. Reviewing is then checking work so, it can be merged and used.
But the process is more about us than the code. And we lose the deeper part when we only care about the superficial one.
It's in a field that I have little experience with (Information Retrieval). So there is obviously prior art that I could learn from or even integrate with.
This article motivates me further to learn things by focusing on building my own and peek into prior art as I go, when I'm stuck or need ideas.
Recently a Clojure documentary came out and the approach of Rich Hickey was seemingly the opposite: Deep research of prior art, papers, other languages over a long period of time.
However, he also mentioned that he made other languages before. So the larger story starts earlier, by making things and learning from practice.
Maybe that's also the bigger lesson: Don't overthink, start by making the thing. But later when you learned a bunch of practical lessons and maybe hit a wall or two, then you might need that deeper research to push further.