We are having our album release show at Westbeth, 155 Bank St in the West Village, on Friday July 10th, 7pm-8pm. Super excited to play this music live!
Free to all, please come out!
@lennysan@clairevo@noamseg +1 on @clairevo's point, would also love to see explanation of this: "The most powerful retention lever in tech is also the most neglected."
I don't disagree, but, _why_ does the report say it's the most neglected? what specifically is neglected?
@GergelyOrosz I worked at a payments startup for a bit and our bottlenecks were 100% regulatory and around working with banking partners. Writing the code was the easy part. I'm a lot more inquisitive about the regulatory environment when I look at working for a company now.
@staysaasy Lots of people just prefer working in person. it's fine to just, you know, say that. Especially if you're the CEO and you started the company.
@staysaasy after 30 years in the business, most in leadership, I'm in the camp of "every CEO has biases and personal preferences, just please be clear about what yours are" vs trying to use "data" to back into what are clearly pre-existing, strongly held beliefs.
@clairevo this would be so so wonderful and refreshing. it's not like most people don't already realize this, it would be a lot better if leaders would just own it.
Sam Altman said the smartest scientists in AI are the ones who held the entire field back. The experts were the problem.
This is one of the most uncomfortable things he said all night.
Altman said the field was honestly held back by a generation of scientists who were too certain about what scaling would not produce. The people with the most credibility were the most wrong.
Then he explained why.
It was not about intelligence. It was about identity.
He said when you make your identity about a particular belief, that something will work or won't work, and then the data disproves you, you get stuck. You are too attached to the belief to let it go. You cannot see the truth anymore.
The smarter you are, the more confidently you defend the wrong position.
He pointed at the trolls who spent years saying scaling was a dead end, a fraud, a company destined to fail. The data kept proving them wrong. They kept repeating themselves anyway.
He called that a form of insanity.
Then he turned it around. He said it is a reminder in both directions. Including for the people who are currently right.
The lesson is not that experts are dumb.
It is that the moment a belief becomes who you are, it stops being something you can update.
(Watch the full talk on YouTube at Stanford Online channel)
@TheStalwart the thing about the tech industry is people like sounding smart, and people are generally good at seeing the general direction of where things are headed.
But the hard part has always been predicting the time scale: self driving cars were "just around the corner" in the 2010s.
@bernhardsson@schrockn I think it's underrated as a coarse signal but quickly becomes meaningless when comparing people that are generally productive.
money is the best score, hard to attribute revenue by feature/function but the better we can do that, the easier it will be to quantify impact.
@karrisaarinen same thing applies to work, esp creative+technical work: if people actually tracked how much time they spent, they would be totally shocked. Hint: it's way less than everyone thinks.
@karrisaarinen the other interesting aspect is how people actually measure hours: I'm a professional musician, and for years I've tracked my double bass practice in a very detailed way (using an app).
All my intuition about how much practice I actually did before this was very, very wrong