9,674 karma · joined August 1, 2011
When we start using big datasets where n went into the tens of millions we kinda stopped bothering because margins were so small it was effectively certain you found the mean of some range. However I think in that time we forget what confidence scoring actually is and how quickly multiplied alpha can balloon on you.
But it's still interesting to consider why he chose those particular devices.
I was fairly surprised when his son wrote a novel that felt like a generic, bland robots run amok storyline that happened, more or less, because one guy/titan "ruined a good thing" by telling his AI to run in permissionless mode.
A good shorthand is that unless a doctor has positively identified something through imaging or biopsy do not trust them when they tell you what something is or what to do about it.
If you aren't sure how best to advocate for yourself, use AI to help figure out what tests and referrals to ask for. You might feel like a jerk, but don't expect anyone to care about you more than you do.
My advice is to not get too hung up on skeuomorphic language being used to illustrate a principle. Metaphor happens all the time.
I believe you're mostly thinking of version history though. There’s plenty of other reasons to have source control we still need, like guarding against racing writes or continuous integration to ensure correctness. Even some industries require version history for compliance reasons.
I do love how AI is challenging us to rethink our tools though rather than blindly reaching to git for every project.
The importance of the pivot is that you're going into a field without preconceived ideas about how it's done, which allows you to learn and grow as the field adapts to AI. That was my experience pivoting away from web dev in the early 00s, anyway.
In general, it is not a good strategy to expect people to make things easy for you. "LMGTFY" has a long history. Rather than get so bothered that you make an HN post and double down in comments, better to develop the muscle memory to look it up and move on. This is about more than just acronyms but all problems life throws your way, which is why I ask: do you want to feel wronged by this blog post not explaining CI, or do you want to learn and move on? No one else in life is on the hook to educate you. If you think this blog post is an offender, try reading an academic journal.
I'm merely trying to impart advice I wish I heard in my 20s, so take it how you will. I wish you luck in your career.
The very specific rules of the problem are that you are evaluating one person on a single metric, and you must choose to hire/reject them before viewing the next. You must know in advance how many people you will be evaluating. This is why it's the "secretary problem." You're interviewing 10 candidates and only evaluating them on typing speed. Once you see their typing speed you must hire or reject on the spot. The optimal strategy is to always reject the first 37% of your sample candidates, then hire the next candidate to beat their score (or hire the last person you interview if none beat them).
In college, we joked that this is optimal dating strategy, because dating still kind of works this way. You decide how high you're willing to go on your body count, and then use this strategy to decide who to settle down with.
As you describe it, (A) does not apply because it isn't about "the best person in the world" it's about the candidate sample you have. (B) doesn't apply because this is a post-hire rejection. You can keep your candidates "warm" and interview the entire batch, then decide among the batch who you want to hire, or not hire and continue.
It's a nice idea, but there's probably a better optimal stopping model than secretary problem for what you're doing.
I don't think what's happening is a uniquely AI phenomenon. If it wasn't AI, it was going to be something else. The ground is always shifting beneath you. It's happened to me in multiple fields through my career. You adapt or you pivot. Like a startup.
For many people who feel negatively affected by AI, my advice to them is to do what I did when my professional disciplines changed to something I didn't recognize: pivot. The great news is that AI makes it really easy to be a beginner in a new adjacent field.
I mention all this because modern hiring is nothing like the actual Secretary Problem, which is about when to stop given unknown information on future samples and a known retry limit. No one hires that way anymore, so I don't feel like the author side-stepped anything about it. I guess that doesn't matter, but it irks me as someone who's spent time on optimal stopping.
Do you want to be right, or do you want to learn?
The worst offenders release the source but with gotcha licensing, wait for the enterprise to use it, then detect their usage and go in demanding payment or be sued. This happened to my team enough times to be a pattern.
It's the only explanation I can see when it's obvious to any student of history this is going to backfire. It doesn't take much imagination to know how such a governing body will be abused, and I'm sure it will only get wilder in ways we can't imagine right now. Dario does NOT know what he's creating, and for once it's not AI.
I say this because I feel the same thing as you when I go back, and I really want to like it.
https://x.com/SebastienBubeck/status/2097379411691516310
https://x.com/sama/status/2097385167002415140
I tend to believe OpenAI on this. Their stated desires seem rational, and Buckmaster's account makes them sound like cartoon villains. It sounds like there may have been some things lost in translation along with some bruised egos. Seems like the most plausible explanation for what Buckmaster is claiming.