maroonblazer

Here's a sample:

"Space Fleet Commander Brad Brad sat in silence, surrounded by a slowly dissipating cloud of smoke, maintaining the same forlorn frown that had been fixed upon his face since he’d accidentally destroyed the phenomenon known as time, thirteen inches ago."

https://www.bulwer-lytton.com/2019

https://news.ycombinator.com/item?id=42913575

So, I think the analogy, at least for those people, holds.

It's not focused on tech, but occasionally touches on policy issues that are tech-adjacent. It's a refreshing, often insightful, and usually very funny take on current events. The author is a former writer for the HBO show "Last Week Tonight with John Oliver".

https://www.youtube.com/watch?v=fEpaq332pmI (just a snippet of the intro, with Serling's iconic introduction)

The app presented the option of prompting additional models, including Gemini Flash 2.0, one I'd never used before. It gave the best response and was surprisingly good.

Curious to know how Chorus is paying for the compute, as I was expecting to have to use my own API keys.

I'm not much of a football fan, really only following my local team and one other. But now I watch the highlights of almost every other game on YT.

Larry McEnerney's (U of Chicago) "LEADERSHIP LAB: The Craft of Writing Effectively"

This caught my eye. What does it mean to listen 'passively'? Meaning it's just 'on' in the background? I.e., you're not paying attention to the content? If so then it would seem you're not interested in hearing what the speakers have to say, which then begs the question of why 'listen' to podcasts in the first place?

I presume you're referring to this one: https://www.xbox.com/en-US/power-on#watch

Thanks for sharing.

Did you need/use that functionality?

>The book is not without its weak moments, although they are few. One in particular which I recall is the treatment of A/B testing. Essential to any hypothesis testing is the matter of how to reduce the sampling mechanism to a simple probabilistic model, so that a quantitative test may be derived. The book emphasizes one such model: simple random sampling from a population, which then involves the standard probabilistic ideas of binomial and multinomial distributions, along with the normal approximation to these. Thus, one obtains the z-test.

>In the context of randomized controlled experiments, where a set of subjects is randomly assigned to either a control or treatment group, the simple random sampling model is inapplicable. Nonetheless, when asking whether the treatment has an effect there is a suitable (two-sample) z-test. The mathematical ideas behind it are necessarily different from those of the previously mentioned z-test, because the sampling mechanism here is different, but the end result looks the same. Why this works out as it does is explained rather opaquely in the book, since the authors never developed the probabilistic tools necessary to make sense of it (here one would find at least a mention of hypergeometric distributions). Given the emphasis placed in the beginning of the book on the importance of randomized, controlled experiments in statistics, it feels like this topic is getting short-shrift.

Can anyone recommend good resources to fill this alleged gap?

How do we solve the "waste" problem?

One side poses a question that the judge or jury needs to answer. The other side then responds with: "The question we really need to answer is...". I.e., "You're trying to solve the wrong problem. Let me show you the real problem that needs to be solved."

Reframing the conversation is offensive communication.