We have traditionally provided reassurance to patients with a borderline anemia. This new prospective data from >500,000 people challenges that lack of concern, indicating an increased risk of all-cause mortality @AnnalsofIM

I walked into gym this morning, tired and not really up to it. As I entered a fit looking guy walked into the elevator , he was smiling and excited about the session. He was borderline glowing…. As I looked down I noticed he had one leg, his other was amputated due to cancer. I was reminded again that it’s all about perspective. Be grateful. For everything.

So I spent much of today trying Jev. It’s radically cheaper. But it made too many false admissions / unacceptable answers to work for SaaStr Connect, at least for now: -$0.064 for 600 judgments against roughly $5 on Sonnet - Input priced at $0.042/MTok, output free - Roughly 90× cheaper on identical inputs. Agreement: 200 borderline-weighted pairs: 59.5% agreement. 200 random pairs: 67% agreement. Against a blind third-model referee on the random set: Jev 70.5% accurate, Sonnet 77.5%. So on the surface, it looked great. At first. But they failed differently: •Jev: 47 false admissions out of 148 negatives (32%), 2 false rejections out of 52 positives •Sonnet: 20 false admissions (13.5%), 15 false rejections Jev unfortunately lets too many weak answers (candidates) through. A 32% false-admission rate is too high.

wtf did they do to astra??? it's suddenly acting like gpt-3.5 for me, like genuinely to the point of being unusable. doesn't understand intent properly, output quality has dropped, and it feels it has borderline 0 context lmao