Not only has Massimo Bottura's YouTube channel failed to rise to the top of (say) YouTube channels you find if you go looking for cookery content on YouTube -- it's failed to rise to the top of YouTube channels you find if you put "Massimo Bottura" into the YouTube search box. (I think its first appearance on the page when you do that is in 29th position.)

[EDITED to add:]

... having said which, I'm not so sure that's a bad thing. I took a look at a couple of his videos. One was (for me) practically unwatchable, consisting mostly of Bottura and (I assume) his family being annoyingly loud; I bailed after a few minutes of near-content-free video. Another was just an advertisement for some masterclass thing he's selling. I tried another video with some actual cookery in it and forced myself to watch all of it despite his annoying family, background noise, terrible camerawork, etc. I learned a bit, but if there was anything in it that revealed 3-star Michelin chef magic I missed it.

He may be a brilliant chef, but I don't think his YouTube channel is "the best" or deserves to "rise to the top".

One of the most interesting media experiments I know of is the Yahoo Media experiments:

1. "Experimental Study of Inequality and Unpredictability in an Artificial Cultural Market", Salganik et al 2006:

   We investigated this paradox experimentally, by creating an artificial ‘‘music market’’ in which 14,341 participants downloaded previously unknown songs either with or without knowledge of previous participants’ choices. Increasing the strength of social influence increased both inequality and unpredictability of success. Success was also only partly determined by quality: The best songs rarely did poorly, and the worst rarely did well, but any other result was possible.

2. "Web-Based Experiments for the Study of Collective Social Dynamics in Cultural Markets", Salganik & Watts 2009:

   Using a ‘‘multiple-worlds’’ experimental design, we are able to isolate the causal effect of an individual-level mechanism on collective social outcomes. We employ this design in a Web-based experiment in which 2,930 participants listened to, rated, and downloaded 48 songs by up-and-coming bands. Surprisingly, despite relatively large differences in the demographics, behavior, and preferences of participants, the experimental results at both the individual and collective levels were similar to those found in Salganik, Dodds, and Watts (2006)...A comparison between Experiments 1 and 2 reveals a different pattern. In these experiments, there was little change at the song level; the correlation between average market rank in the social influence worlds of Experiments 1 and 2 was 0.93.

This is analogous to test-retest error: if you run a media market with the same authors, and same creative works, how often do you get the same results? Forget completely any question about how much popularity correlates with 'quality' - does popularity even correlate with itself consistently? If you ran the world several times, how much would the same songs float to the top?

The most relevant rank correlation they seem to report is rho=0.93*. That may seem high, but the more datapoints there are, the higher the necessary correlation soars to give the results you want.

A rho=0.93 implies that if you had a million songs competing in a popularity contest, the #1 popular song in our world would probably be closer to only the #35,000th most popular song in a parallel world's contest as it regresses to the mean (1000000 - (500000 + (500000 * 0.93))). (As I noted the other day, even in very small samples you need extremely high correlations to guarantee double-maxes or similar properties, once you move beyond means; our intuitions don't realize just what an extreme demand we make when we assume that, say, J.K. Rowling must be a very popular successful writer in most worlds simply because she's a billionaire in this world, despite how many millions of people are writing fiction and competing with her. Realistically, she would be a minor but respected author who might or might not've finished out her HP series as sales flagged for multi-volume series; sort of like her crime novels published pseudonymously.)

Then toss in the undoubtedly <<1 correlation between popularity and any 'quality'... It is indeed no surprise that, out of the millions and millions of chefs over time, the best chefs in the world are not the most popular YouTube chefs. Another example of 'the tails comes apart' at the extremes and why order statistics is counterintuitive.

* They also report a rho=0.52 from some other experiments, which are arguably now more relevant than the 0.93 estimate. Obviously, if you use 0.52 instead, my point gets much much stronger: then, out of a million, you regress from #1 to #240,000!

Sigh. To make something work in a competitive world, you need to make it work on all the relevant metrics - at least "good enough" on all of them, and better than the competition on some of them.

Suppose you offer a product that's measured on 4 metrics (imagine: quality, speed, price, size, ease of use, beauty, weight, ...), A, B, C, D.

Some potential customers will weigh some metrics more heavily than others. Some will ignore some metrics completely. But in general you need to do at least 5/10 on all of them and better than that on some of them.

Metric A: 7/10

Metric B: 8/10

Metric C: 2/10

Metric D: 10/10

That's a losing product. It's fantastic on D, but bad on C, and that kills it for most customers. Maybe there are a few people who don't care much about C and will love the product. But not many.

That's what happened to Massimo Bottura (C was production quality). You're the weird customer who doesn't care about C and notices mainly D. 

Probably that's what happened to your startups.

Sorry - it's tough. But that's the reality.

---

Added: Of course the same is true for other competitions, for example mate selection. Happily most people are only looking for a single mate, so it's not that difficult to find somebody who values D a lot, C hardly at all, and also measures well on your own preferred metrics.

It's not that easy for a startup or a YouTuber, who need numbers.

I agree that often the best don't rise to the top, but you have bad examples here.

You are confusing expertise in different domains: just because one is exceptional in something, it does not follow they are good at teaching it or making videos of it.
This is especially apparent in Bottura's channel. He might be the best chef in the world, but his youtube content is mediocre.

My core point is that there are people like DHH, like Massimo, who should be getting way more views on their videos, given the quality of the content they're producing and what they've done to promote that content. Do you disagree with that?

What do you mean by "... who should be getting way more views... ...Do you disagree with that?" (To provide context around my thoughts as I write, I'm thinking of the phrase "the purpose of a system is what it does".)

I'm thinking there's at least two meanings with at least two different ways to interpret. 

First, you could mean "I have an understanding of the system that leads me to expect a different distribution of popularity by viewcount. I have an understanding of the system. Good content -> high viewcount. It should do this. It does that. Do you disagree?" 

Second, you could mean "I have an understanding of meritocratic justice such that the distribution of popularity as judged by viewcount is unfair. Good content -> high viewcount. Life should be this way. It is that way. Do you disagree?" 

If neither of those hit the mark or if anyone has alternatives, I'd like to know.

For the first interpretation, "do you disagree" can't really be applied to your understanding of the system. You understand it the way you do. I suppose a similar question that might be more appropriate could be "How might the system differ from my expectation such that I am surprised by this behavior?" A brief response to that question would be something along the lines of YouTube's purpose having to do with money, algorithms to keep people viewing and clicking on ads, what makes something viral, etc...

For the second interpretation, that might be a long-winded philosophical topic that I expect could be summed up with "Yeah... that sucks."

Without commenting on the rest of your point, this part:

If my quality is, say, a 7/10, my level of success should be somewhere in that ballpark. Maybe the market would be inefficient and I'd only reach a 5/10 or a 4/10. Or maybe I'd be lucky and reach an 8/10 or 9/10.

is something I don't think you should necessarily have expected from a market to begin with.  Assuming that your startup was in a scalable field (e.g. a software company as opposed to a restaurant) with an efficient market, what you expect to happen is that quality 7/10 should lead to success 0/10 - there is no reason that anyone would buy from you when they could instead buy from a 10/10.

In reality there are lots of reasons this isn't quite the case.  Maybe your product is 7/10 overall but genuinely the best in the world for certain specific users/use cases.  (C++ and Python both continue to exist).  Maybe the market just isn't very efficient and some people end up buying inferior products.  (PHP also continues to exist).  But on the whole expecting a 7/10 product to experience a 7/10 success is not actually what you should expect to see.

The meritocratic part is the best are significantly more likely to rise to the top, real world is best thought of as a stochastic place, full of imperfect information and surprises.
Being the best at content creation is not the same as being the best at YouTube: size of one's target demographic matters, the ability to self-promote matters, ability to network matters, ad-friendliness of content matters... Akin to evolution, the system does not select the *best* creators in the conventional sense of creating the best videos, being the best at writing and so on. In fact, one might argue for the opposite being the default.
The selection criteria are messy, the variance in outcomes is significant, the variance in perceived selection criteria even more so. 
My takeaway is that one should be lucky and avoid being unlucky, while trying to stack the deck as much as one can in order to manipulate variance.
 

Quantity/frequency matters.

Algorithms should minimize the chance that initial luck (bad or good) leaves a lasting effect on end popularity.

Really great, accessible stuff pumped out regularly will eventually rise.

Funny enough, I've recently been contemplating asking a question here on LW like "what actually-quite-good youtube channels are out there?" precisely because I suspected there were a lot of hidden gems like you mention! I didn't get around to it, though, perhaps because watching youtube feels low status so I felt like it would be embarassing to visibly put effort into optimizing my youtube-watching.

Anyway, there are a few reasons why I thought this was a priori plausible:

1. First and foremost, I see this as an example of the tails come apart (ie Goodhart). Even if quality and reception are very highly correlated, you should expect the top of the two to be different, based on noise alone. But maybe that's not satisfying: what's driving the noise? Why isn't reception exactly proportional to quality?
2. A big factor here, for a lot of cases, is going to be network effects. Small fluctuations in popularity don't get corrected, they get exacerbated. Two people can release similarly great videos, and the fact that one gets its first views from the right people (who show all their friends) can snowball into a big lead. And this can snowball into making one channel a huge success while the other practically-equivalent channel is lost in obscurity.
3. But there are also going to be a lot of "noise" factors that aren't random at all. EG, how clickbaity a video is. Out of two similar videos, if one is a little more informative but the other is a little more clickbaity, I expect the clickbaity one to do better.

The third point means we could see the tails come apart to a very high degree, even if there's no noise in the system at all. To possibilities like #3, you respond:

I want to focus on my core point here. DH6, not DH5. You might be able to make points about how being brilliant doesn't necessarily make you good on camera, or about how marketing and promotion matters a lot, or about releasing videos on a consistent schedule, or about how maybe they're not producing the types of content YouTube viewers want to watch. Some of those might be fair points, but do you think that they refute my core point? My core point is that there are people like DHH, like Massimo, who should be getting way more views on their videos, given the quality of the content they're producing and what they've done to promote that content. Do you disagree with that?

(I don't disagree at all, but) I think you're implicitly assuming something like: even if DHH is a little less clickbaity than competitors, this should only translate to a somewhat cooler reception. This is reinforced by your expectation that:

If my quality is, say, a 7/10, my level of success should be somewhere in that ballpark. Maybe the market would be inefficient and I'd only reach a 5/10 or a 4/10. Or maybe I'd be lucky and reach an 8/10 or 9/10.

But reception can be highly nonlinear, perhaps closer to exponential. So, at the upper ends of quality, small differences in quality lead to very large differences in reception.

We could see something like:

Quality      Reception

1/10          0/10

2/10          0/10

3/10          0/10

4/10          0/10

5/10          0/10

6/10          0/10

7/10          1/10

8/10          2/10

9/10          5/10

10/10          10/10

Again, even without randomness, in a system like this you could see the effects you're describing.

I watched a few of the DHH, Eric Normand and Be a Better Dev videos. DHH's videos are very good, actually I was sucked into watching a couple, but he doesn't have very many. Also, your link points to his old channel, and now all those videos are https://www.youtube.com/playlist?list=PL9wALaIpe0Py6E_oHCgTrD6FvFETwJLlx, although he only did one more in that series. The couple Eric Normand videos were pretty good, I could imagine that there are really good ones somewhere in the feed. For Be a Better Dev, the videos seemed pretty low quality, very focused on learning AWS-specific technologies. It gave me the impression that he was just following traffic for what to talk about, the exact opposite of DHH. It's the equivalent of YouTube blogspam.