I wonder about the accuracy of the rest of the article.
656 karma · joined June 23, 2014
I wonder about the accuracy of the rest of the article.
"I noticed the following facts about people who work with the door open or the door closed. I notice that if you have the door to your office closed, you get more work done today and tomorrow, and you are more productive than most. But 10 years later somehow you don't know quite know what problems are worth working on; all the hard work you do is sort of tangential in importance. He who works with the door open gets all kinds of interruptions, but he also occasionally gets clues as to what the world is and what might be important."
Each of those little interruptions is a clue about the wider state of the world (codebase / APIs etc). AI offers a shortcut, but it does not provide the same mental world-building.
Or to phrase it another way, there must examples of the technique that you want to "generate" in the training set otherwise the horrifically overfitted model cannot work.
Probably a little bit too cynical but this is my experience asking LLMs "unusual" questions.
So far everything seems to work - although the machine has a strange glitch. Processes randomly die, but only if they have a render surface. Typically it happens to factorio or to the steam ui component, which are both incredibly stable.
the aaa games industry is struggling (e.g. look at the profit warnings, share price drops and studio closures) specifically because people are doing that en masse.
but those 90s games are not old - retro has become a movement within gaming and there is a whole cottage industry of "indie" games building that aesthetic because it is cheap and fun.
But the company is a major defense contractor and it was very unusual for them to be involved in humanitarian work. So it made sense to question the requirements after a less generous reading. Detecting mostly occluded humans in a highly cluttered and destroyed urban environment has other use cases. They got as far as "highlighting the survivors with a laser designator" before I started to ask some very pointed questions and start discussing the ethical considerations of us helping to build a system to kill people.
I was asked to leave.
After that meeting the potential collaboration was rejected and it never came up again. The company continued shopping around other places to get help building their "earthquake rescue system".
Never get distracted. Always question the purpose of work. Consider ethics.
Getting another job can be a pain. Living with knowing what you helped to build would be much harder.
This result seems to tell us less about the power of the training approach (in absolute terms) and more about how amenable the chess game tree is to those two approaches (in relative terms). What I would take away is that a reasonable approximation of that tree can be made in 270M words of data.