You sound like you are laying blame at the feet of companies following employment laws when you should be complaining to the government that makes the employment laws the company is abiding by.
The safest version will still be better overall regardless, by definition. It is also a better future for most if it is inevitable that the war department is going to use a less safe alternative if they can't use the safer one.
The safest version will be the one most effective at killing dissenters without killing regime personnel. So yes, it will be better, for the people controlling the killbots, not for their victims.
Yea I know. I once went into MBTI in the vein of "it's not scientific but can I learn something useful out of it?" I tend to test close to ENFP/ENTP. I can notice tendencies of both in me. Then I went on the ENFP subreddit as I suspected many had ADHD and simply asked in a poll. A lot of them said that they did, as I suspected as I'm subclinical myself (and it becomes clinical real fast I even just sleep for 6 hours on one night).
So I learned that you can definitely glean some insights from it. One insight I have is: I'm a "talk out loud thinker". I don't really value that as an identity thing but it is definitely something I notice that I do. I also think a lot of things in my mind, but I tend to think out loud more than the average person.
So yea, that's how pseudo science can sometimes still lead to useful insights about one particular individual. Same thing with philosophy really, usually also not empirically tested (I do think it has a stronger academic grounding but to call philosophy a science is... a bit... tricky... in many cases. I think the common theme is that it's also usually not empirically grounded but still really useful).
Specialized research AI agents are coming at which point we'll have numerous LLMs running and verifying experiments and creating a higher quality text corpus than the 2014-2020 halcyon, which is then used for other LLMs to be trained on.
It will be the reverse I suspect. Eventually we will see that LLM quality is lower when it is training data from 2014-2020 and will chalk it up to human limitations and the data not being written with a laser-focused goal of training better AI.
I feel like all the BS we were taught about architecture design principles multi-AZ, failover strategies, graceful degradation etc was gaslighting us all into thinking any of out work on it actually matters.
This isn't true, but it feels like this when the entire engineering world order seems to actually run on single-point-of-failures where one CEO just messages another when some 3rd party is down. And reputational risk here is completely safeguarded because as long as everyone is down you are fine. Use a service everyone uses and it goes down = no reputational risk. Use a more robust architecture and make some mistake = massive reputational risk and everyone asks why you don't use what everyone else uses.
reply