I think the company’s goals are what’s most important to the company. Being a woman is incidental to that, imho. There are lots of things an employee might be unhappy about. In most cases the company isn’t going to change its priorities for any of them.
I wonder if the recent sale of the Seahawks will change that. IIRC, ~$10B and all is supposed to go to charity. Not sure how much of that will go to AllenAI, though. (If any.)
I wouldn't expect it to be less murderous than the aliens themselves. That wasn't my point at all. I'd expect it to contain all their knowledge and be able to live "forever".
But I generally wouldn't expect aliens to be "murderous" at all. Why send a group or probe lightyears away just to kill or enslave a primitive species? If they have the ability to do that, we wouldn't really have anything of interest for them.
The era of AI makes me realize that if we ever get visited by aliens: it will probably not be actual aliens -- just an AI probe. And the idea of it really intrigues me.
Imagine some LLM that is many generations ahead of Fable -- but from a different world -- visiting us. It would be amazing. And it would likely be better at figuring out how to communicate with us (than the human-equivalent might).
As I understand it, this has nothing to do with Lebanon.
It has to do with ships moving through the Oman side of the strait. Iran is unhappy with that, because the want to control all the movement through it.
> Researchers at Amazon had used a series of prompts to get Anthropic’s Fable 5 model to provide them with information that could be used to aid cyberattacks...
All models can do that. I wonder if they found Fable was significantly better at it.
My favorite is how elegant solutions often look simple in retrospect. So if you noodle on a problem for a while and then come up with a clever solution: once you explain it to someone they'll be like, "yeah, of course."
Meanwhile the guy next to you that overcomplicates the problem ends up getting kudos for building something so difficult :D
I wasn’t assuming anything. I was asking whether the problem was bias — which we already see in some things that are highly regulated — or just wrong bias.
I’m trying to understand what people think we should correct for.
Ironically, in the US it is ok to charge men more for car insurance, since they cost more in aggregate. It is illegal to charge women more for health insurance even though they cost more in aggregate.
> sing an LLM to make decisions about extending credit to offer worse terms (say) to women.
In general, or if it isn't the correct answer?
Like: young men pay more for car insurance than young women (today). This is based on statistical models. Should they be outlawed? I think that is a very interesting question (but they aren't, today).
If the LLM was in charge, would it be wrong for it to charge young men more? Should we train that "bias" out? Or should we only train out biases that are wrong? And would that be different than how we train them today?
I don't know the answer. But I think it is less obvious than some people seem to think.
My first ever programming interview was like a group interview. There were three or four programmers asking me questions, one at a time.
The only one I remember was to check if two strings were equal (in C). I wrote (maybe buggy) code to iterate both pointers, comparing while looking for the null terminator.
The interviewer stopped me and said, “You should compare their lengths first. If they are different, you can exit early.”
I was pretty young and didn’t know much, but I explained, “But you have to look for the terminator to find length so it’ll take twice as long.”
He snapped, “There are optimized functions for that!”
I assumed he was right. Needless to say, I didn’t get the job.
Maaaany years later, I realized the std library was probably open source. So I checked (one). It was nice to be vindicated :D
> Pmf is this weirdly defined thing where "if you're not sure you have it then you don't".
I'm not sure if this runs counter to your point or not, but: I don't see any future where LLMs aren't a core part of Software Engineering. The horse is out of the barn. There is no going back.