Brilliant. I think YouTube has arrived at the same algorithm - it picks the videos I watched yesterday to recommend today.

Well to be fair that's how all employers also hire.

If you did a good job at the last company you'll probably do a good job here.

If you did a good job yesterday, you'll probably do a good job today.

For the most part they are usually correct.

I hope you are joking since the industry collectively knows how much employers/interviewers value algorithms-based coding interview, which doesn't correlate strongly with performance. Even if you are talking about senior positions where they don't matter, then you should know that people hire someone they know+like who did decently well, rather than the truly best on the market.

That's SF/Big Tech. The rest of the world basically works like the stated algorithm.

The coding interview comes usually after they vet your resume, any profiles, get you talk to an HR, and potentially check your references.

Even the coding interviews are just a signal against overall performance given a short amount of time. It's only a sample of data, but if you did your interview right you should be able to protect some against bad people getting very lucky. Just like driving a car; bad drivers tend to stay pretty bad, and good drivers tend to stay safe. Even though there's a lot of ways to define what is a good driver, there's clearer ways to define what is a bad driver, and if someone was a bad driver yesterday they are still probably a bad driver.

well, that's the thing though - coding interview is pretty much a yes/no thing. What rank you get is typically based on "what rank do you have now?" and "how much do we respect your current employer?"

I remember reading Steve Jobs used a "different" technique to figure out if someone was good.

He would go around to people and say "I heard Joe sucks". If the people strongly defended Joe, he was probably pretty good. If nobody stuck up for him, Joe might indeed suck.

Probably everyone would be silent as well if someone said "Steve Jobs sucks". This anecdote is meaningless TBH.

Completely ignoring the depth of your subscriptions as well. Amazon music was much better for me. Even Google music just repeats.

Seriously. Why would I want to watch a video that I've already watched (unless it's music maybe)?

They have a lot of videos. You're statistically unlikely to care about any randomly selected one. By watching a video, you establish that it's interesting enough for you to watch. It's much more likely that you'll want to rewatch it than that you'll want to view a random video.

I'm only half-joking here. To me, YT algorithm seems to be a mix of "show random videos you've already watched" + "show random videos from channels and users you watched" + "show the most popular videos in last few hours/days/weeks". It's pretty much worthless, but what are we expecting? Like all things ad economy, the primary metric here isn't whether you like the recommended content, or whether that content challenges you to grow - it's maximizing the amount of videos you watch, because videos are the vehicles for delivering ads to you.

I prefer a user driven random walk. Like a multi-arm bandit over a hierarchical graph instead of a stuck-in-local-minimun + noise recommender. But no one does it.

Years ago, there is an app stumble upon. I always find it engaging. Hard to get bored.

Im guessing things like 5 year olds watching the same video 300 times randomly on their parent's account has irreversibly tainted the Googletron into thinking people like to watch the same video over and over again.

Hundreds of times I have told youtube im not interested in a recommended video that i have already watched, seems to be completely ignored.

Why wouldn't you? Do you never re-watch a film or re-read a book or re-order the same food at a restaurant, or re-drive the same route to work?

I often watch the same video that I've already watched, many times music, many times comedy, many times something I want to link to another person but end up watching some/all again as I find it, often if I remember it being interesting (e.g. a VSauce video or a Dan Gilbert TED talk), sometimes if it was a guide or howto that I want to follow - e.g. a cooking instruction.

Music is probably the main driver, but I've definitely clicked some recommended videos from a channel I'm subscribed to with infrequent long uploads.

I have a friend who lived in San Jose who just wrote the forecast on his whiteboard and left it there, because it never changed. It was funny, because he came from Minnesota where the weather is never the same two days in a row.

Ha! I came here to say something similar. Here in San Jose, the weather tomorrow will be the same as today, most of the time. My joke when I lived in Minnesota was: "If you don't like the weather, just wait 10 minutes. It will be different."

Gotta say though, I don't miss my slow blower even just a wee little bit.

To be fair San Jose weather is heavily biased towards sameness.

Yes, but why did all the 'smart' people using models and training networks get a worse result? A condemnation of modelling, to be sure.

Using a markov chain with your stochastic matrix set to I...

Using “a I”

AR(1) models are commonly employed to model time series, and the "same-as-yesterday" model is the case where the AR1 coefficient equals 1. There is is some mean reversion in seasonally-adjusted temperature, so an AR1 coefficient less than 1 should work better.

Just showing a customer's previously viewed items accounted for 85% of the "lift" credited to the recommendations team I worked on.

What about Benjamin Franklin's moving weather?