Hey HN, here’s the result of gathering as many tech talks as I could find and then trying a bunch of ranking heuristics to find one that produced reasonable results. I’m currently using the lower bound of each talk’s Wilson score confidence interval based on likes and dislikes.
I find good tech talks to be a combo of entertainment and broadening my toolbox of programming concepts. When I hit good talk I generally do a double take, “wha, I have not thought that way before.” There are definitely some good talks in this list.
There are a few great “Awesome Talks” lists that I’ve enjoyed perusing, but I’ve found that talk title intrigue does not seem to correlate with talk quality. So in lists of 50+ talks I have a hard time finding the “next best talk”.
I’m keen to get feedback on the site as is but also if there is interest in a “top tech talks” in the last month (or X unit of time) style of digest.
Hopefully there is a talk in here that gives you a double take.
Maybe these are mostly too new, or you have different (more practical, hands on?) definition of tech-talk - but from a quick look the only speakers I expected - and found - were Sandi Mets and Rob Pike.
If it's practical, I'm surprised not to see the js "wat" lightning talk (which I now can't seem to find...).
If it's more general "best of", I'd expect something like Guy Steele "growing a language" :
https://youtu.be/_ahvzDzKdB0
Alan Kay "doing with images makes symbols":
https://youtu.be/p2LZLYcu_JY
Or, if that's too long, the much more condensed ted talk:
"a powerful idea about teaching ideas":
https://youtu.be/Eg_ToU7m1MI
(Maybe that's not a "tech talk"?)
You're right those are all great talks (and fit in my definition of a tech talk). I just checked, and none of them are in my dataset, which I'll admit I'm surprised about. But they (and related ones) will make it into the next round.
The issue seems to be that they are not typically watched on youtube. For example, the "simple made easy" linked above is a low-quality pirate youtube copy, the proper place to watch it is here:
Is your dataset limited to only videos on youtube? The Fronteers conference has been publishing its videos on vimeo, and that includes some really "awesome" ones: https://vimeo.com/fronteers/videos/sort:plays
It is currently, but I'd like it not to be. One issue is my current ranking alg uses both likes and dislikes, but Vimeo only does likes, so I can't currently cross-compare between youtube and Vimeo without switching up my ranking alg. I'm curious about trying a version of my current alg that just uses likes and views though, which would be more portable.
You could also use "net promoter" scoring: fraction of likes minus fraction of dislikes. I don't think it has any theoretical basis but the NPS system [0] is fairly popular.
Yeap! Views are also done by promoters and detractors. Assuming one view per person you could get number of passives as: passives = views - promoters - detractors. Once you have passives, you can compute the NPS.
Do you know of some generalization that instead of just positive and negative ratings would work with real numbers? E.g. rating could be anything between 0 and 1.
Interesting, I like the simplicity of that. Do you have any info how to determine good initial values for the prior? In this example good values for pretend_up and pretend_down? Would it make sense to use average_upvotes and average_downvotes or values that have that ratio?
Values that have that ratio might be good, but I'm not sure about the magnitude because maybe the average number of votes is too high so that the prior overwhelms the data. The scores get pulled towards that ratio as you increase the magnitude. If the ratio is close to 0 it has the effect of downranking videos with few votes, and if the ratio is close to 1 it has the effect of upranking videos with few votes. The effect might be too strong if you use the average magnitude. It might also be good to set the ratio a bit lower than the average ratio if you want to rank conservatively.
Parametrising it like you suggest might make it easier to experiment:
ratio = 0.5
number = 100
pretend_upvotes = ratio*number
pretend_downvotes = (1-ratio)*number
You could even set ratio to 0, but I actually think it makes sense to rank 1 up / 2 down above 101 up / 200 down, because the latter is definitely bad whereas the former might be good.
You can either estimate the prior as part of a hierarchical model, or use empirical Bayesian estimation. I spoke last year about an example of EBE applied to music trends:
Too many people get hung up on the perfect scalable tech stack. Most people don't need to waste more time watching another tech talk. What they need is more business skills and how to make money.
I was about to complain that my PyOhio video about dot matrix printers was missing, but it is in the 2-month Python section.
So now that I'm ashamed of my ego... there were several talks that were much better from that conference and it is a shame they didn't get more views. Mine was picked up by Hack-a-Day so it got a boost, but many of the other talks were better in all kinds of measures like amount of content, social relevancy, etc... It sucks that we still don't have a good system other than view count!
Do you mean history outside of tech? Or history of (software / CS) tech? A lot of times my favorite talks are historical perspective (tech) talks, so I would also like to get more of those in there. A "history" topic filter would be sweet even on the talks I'm already searching but categorizing by topic is not something I've tackled here yet.
I mean "regular history". About ancient civilizations, bronze age collapse, Napoleon, the Russian revolution, things like that. It is a personal preference for me to listen to such talks, but I think there could be interest in many other topics as well. I have come to the conclusion that apart from literature, talks in academic settings are more likely to be interesting, compared with documentaries produced for television.
Cool. The hard part is collecting the list relevant talks, the easy part is ranking them. If there is a way to get the right set of academic history talks it wouldn't be that hard to go from there.
I haven't watched much historical lectures, but I do enjoy documentaries and historical fiction. Another idea I've kicked around is a site that organizes a bunch of historical documentaries and historical fiction into a geo-timeline visualization. And include the ability for people to comment on and discuss the historically accuracy of the films. But that's a different project...
One thing I wonder about ratings is, are you measuring a user's individual interests, or whether they think the content is good / bad / shareable?
And what do the users think they are ranking?
Personally, I'd rather be ranking for what interests me, so that I get more of that; but I feel most networks are trying to extract a different signal, and that this produces crappy recommendations and useless rankings.
True-ish. Since the formula uses confidence intervals[0] it does better with recent talks than a simple (likes - dislikes). But you're right, breaking into "all time" status is tough because there are a number of talks with many hundreds of likes and 1 or 2 dislikes.
In fairness, YouTube hasn't been around forever either, so I'm not sure the difference between the upload date and the talk date is actually surfaceable
Not on purpose at all, I've learned a lot from Uncle Bob. 50k talks is certainly not all of the talks ever, and there are many good talks not included in the 6 lists I've generated (which is a total of only about 230 talks). I'd like to add more filters to be able to hone in on top talks for different contexts.
50k is 50,000. Which is a lot of talks, but certainly not all of them. My abstract criteria for a talk being considered a "tech talk" is a live lecture given from the front of a room to a live multi-person audience with a subject matter related to computing. The 50k is just the number my hacky talk finder script found.
I find good tech talks to be a combo of entertainment and broadening my toolbox of programming concepts. When I hit good talk I generally do a double take, “wha, I have not thought that way before.” There are definitely some good talks in this list.
There are a few great “Awesome Talks” lists that I’ve enjoyed perusing, but I’ve found that talk title intrigue does not seem to correlate with talk quality. So in lists of 50+ talks I have a hard time finding the “next best talk”.
I’m keen to get feedback on the site as is but also if there is interest in a “top tech talks” in the last month (or X unit of time) style of digest.
Hopefully there is a talk in here that gives you a double take.
Enjoy, ~yaj