Readit NewsI was in Switzerland last summer, in Glarus Alps, and walking around I found a sign that basically said that the reason why all the mountains around it were "smooth" in appearance is because during last ice age all of it was covered in ice, and the rock got smooth as the ice started to shift and slide over the course of hundreds of years. It said that only the highest peaks would be free of ice, and even then just barely - and all of those were above 2000m above(current) sea level. It's crazy to think that an ice age doesn't just mean "it's very cold" - it means there is enough ice to bury europe under 2 kilometers of ice. That's not survivable in any way, we would just have to move south somewhere - but like you said, even if it happens again it will take thousands of years to get to that point.
Not all ‘ice ages’ are the same.
A true ice age as you discuss is due to the distance we are from the sun. Unfortunately, we are in the opposite and the compounding effects of human induced greenhouse effect will doom us. It’s a bit like nature/nuture.
There is stuff we can control. How we handle our species and our home, the earth.
They could store a normalised, hashed version of your data and use it to filter any incoming datasets. But, of course, why would they?
Exactly! One important thing LLMs have made me realise deeply is "No information" is better than false information. The way LLMs pull out completely incorrect explanations baffles me - I suppose that's expected since in the end it's generating tokens based on its training and it's reasonable it might hallucinate some stuff, but knowing this doesn't ease any of my frustration.
IMO if LLMs need to focus on anything right now, they should focus on better grounding. Maybe even something like a probability/confidence score, might end up experience so much better for so many users like me.
It's very useful if you have the knowledge and experience to tell when it's wrong. That is the absolutely vital skill to work with these systems. In the right circumstances, they can work miracles in a very short time. But if they're wrong, they can easily waste hours or more following the wrong track.
It's fast, it's very well-read, and it's sometimes correct. That's my analysis of it.
Of course it is mind blowing for them.
I don't think his name has ever come up in all the histories of this—some Lockheed policy about not letting their employees be publicly credited in papers—but he's got an array of internal awards from this time around his desk at home (he's now retired). I've always been proud of him for this.
Metrics enable the ability to aggregate concepts into some kind of meaning.
Meaning can then have alerts associated to them.
You cannot create metrics on things you don’t know, which is why logging is the base.
I cannot stress the importance of understanding atomic movements.
The cost is high but not as high as the cost of not knowing.
The recruiters all had LinkedIn paid accounts, and could access all of this data on the web. We made a browser extension so they wouldn’t need to do any manual data entry. Recruiters loved the extension because it saved them time.
I think it was a legitimate use. We were making LinkedIn more useful to some of their actual customers (recruiters) by adding a somewhat cursed api integration via a chrome extension. Forcing recruiters to copy and paste did’t help anyone. Our extension only grabbed content on the page the recruiter had open. It was purely read only and scoped by the user.
So when pay the highest scraper, it’s ok! Same data, different manner.