And for any general multiplier to work, people generally need to be on board.
For example: there is a difference between economic inequality and desperate economic inequality -- the first is a mere difference in ownership and control. The second is /also/ a difference in ownership and control but that leaves one party or group bargaining against their physical well-being. There is much said about mere economic inequality but, by leaving out the desperation factor, the public conversation is tied up in knots (e.g. "Well why don't we give everyone a million dollars?!" nonsense) and the real problem, desperation and the conditions that lead to that state, persist despite having the tools to potentially tackle it. But any single example -- a single mother that has to take two minimum wage jobs to feed her kids -- can be reduced away. She could just do x, y, or z and her particular problem would be solved and she'd still be economically disadvantaged but not desperate to the point of worrying about her kids starving. And the conversation ends. We are back to the inconvenience of a weak bargaining position which is also described by the phrase 'economic inequality' and it all feels like the same, well trod and religiously guarded ground.
I found that statement the most insightful of the essay. Helped me resolve some cognitive dissonance.
Whether there really are totally new things and not just existing things in new packaging depends on which level of abstraction you stop at with when analyzing. For example, at a very high level you could say that the Internet as a whole is really just a very advanced/efficient printing press. (And automation like the printing press or assembly line, just efficiently organized production.)
That level of abstraction may be less than helpful, unless there are insights to be gleaned from where the internet is going by looking at printing press technology. Their impacts on empowering the masses are similar, but they each encouraged/enabled network effects to consolidate much power (newspapers and goog/fb) and thereby effectively countering much of the effect.
It reminds me of expected value calculations: extremely low probability events of tremendously high impact could actually out-rate moderately probable events of moderate impact in terms of how concerned you should be with them. Assigning meaningful probabilities and impact values can be tricky though, which adds a whole layer of complexity and hand-waving to the problem.
This is where discussions of nuclear war, strong AI, nazi-oriented political resurgences, geothermal storms, epidemics, etc. can really go off the rails in my opinion: two people can separately evaluate "worst-case scenario" as very different realities, assigning very different intuited impact-values, and also assign very different probability values. Even if they think about these things from an expected-value perspective, a discussion between them becomes at least a 2-variable linear equation, and the odds of even understanding each other are stretched, let alone finding the same x and y and agreeing upon what that means for the actions we should take in response.
Graham's point here on the positive side though is a refreshing step outside of that domain. An idea recycled, if broadly applicable enough, only needs a hint of novelty. It gives me some hope for being able to come up with useful things.
A rule-of-thumb I've generally followed when brainstorming is "never write down the ideas". And if at all possible, try to forget them, good or bad. It inevitably forces me to re-think the ideas "from scratch". I've never been worried that an idea would escape me or that I would forget it, as I think the exercise of re-thinking ideas from scratch has helped me build a relatively solid mental model of the world. I feel that, with practice, this method of brainstorming has started bringing me to the solid / useful (general / surprising) ideas faster.
It has likely, over the years, added weeks or possibly months worth of time that I've spent brainstorming the same (general) ideas over and over.
When I was forced by my boss to teach designers brainstorming, against my better judgement, I instead made this slideshow summarising my frustrations and what I would suggest people do instead:
If the team is in charge as a group of doing the brainstorming, 99.999999% of the good ideas will come from non-team individuals who will be automatically shot down as "not your job" "work on your own team" and similar primate dominance games. If you brainstorm individually, that 99.999999% of good ideas has a better change of getting implemented. Groups hate outsiders (and by extension, their ideas), without a boundary there is no group.
Another internal politics problem is reward. Teams exist to funnel all success upward and channel all failure downward. Everyone knows if they actually have a solution its wasted on the team unless they're the leader. There are financial and career pressures for teams to fail so individuals can keep the fruits of their labor, so to speak. This can lead to very low team performance.
I've been told it's better live when I combine it with barely-contained frustration - turns out to be a very relatable experience for many.
I have been lucky enough to never have been in an organisation with a dedicated brainstorming team, but your description definitely sounds like how it would play out in reality. Thanks for sharing, now I know it's a red flag.
If you combine that with brainstorming being misused for identifying problems (instead of solutions to known problems) like I mention early on, things probably get even worse.
> Our species is the only creative species, and it has only one creative instrument, the individual mind and spirit of man. Nothing was ever created by two men. There are no good collaborations, whether in music, in art, in poetry, in mathematics, in philosophy. Once the miracle of creation has taken place, the group can build and extend it, but the group never invents anything. The preciousness lies in the lonely mind of a man.”
"Show HN: [Title]" with an explanation in the comments?
Not that think that what I suggest is perfect either, but it seems to be a bit better aligned with how ideation works.
Hope it will be of use to you all! :)
Anyway, I think get what you're saying with not writing things down: you're forcing yourself to start from the ground up, so the result matches the problem better. Having said that, I wonder if this isn't more dependent on how you note things down and organise your thoughts, because like others have mentioned here, I would have lost a lot of ideas if not for short scribbles.
I've found this phenomenon to reveal itself even more explicitly when attempting to explain some of my more complex thoughts in detail to others.
I think the benefit you are aiming for can be achieved by making an effort to revisit prior ideas with fresh perspectives and from different angles, and then later comparing and contrasting the different attempts.
Makes me feel I should write them down, and revisit/expand on them properly..
Ideas keep evolving. There was nothing new about the idea of a search engine when Google came into existence in 1998.
In 1945, Dr. Vannevar Bush wrote an article titled As We May Think:
> he urges that men of science should then turn to the massive task of making more accessible our bewildering store of knowledge.
In the 1960’s, Gerard Salton created and developed Salton’s Magic Automatic Retriever of Text (SMART). He also authored a book called A Theory of Indexing detailing his initial tests that search is largely based off of relevancy algorithms. Here’s a very interesting blog post titled Search Down Memory Lane by Tom Evslin who worked with Salton during this project:
Fast forward to 1990, a man named Alan Emtage created the first search engine known as Archie which retrieved a database files by matching user queries using regexes. Following the growth of Archie’s popularity, two similar search engines Veronica and Jughead were created and they started indexing plain text files.
In 1993, the first bot called World Wide Web Wanderer was created and then it was upgraded to capture active URLs and store them in a database. Then came ALIWEB (Archie-Like Indexing of the Web), which crawled meta information of pages.
There’re others including WebCrawler (1994), Lycos(1994), AltaVista(1995), Excite(1995), Yahoo(1995), Dogpile(1996), Ask Jeeves(1996).
This is just my superficial understanding of how the idea of search engines was born and has evolved over time. They were very different from Google, but they’ve similarities to how data is processed and analyzed today.
- Amazon wasn't the first online store.
- AirBnB wasn't the first short term rental website
- Netflix wasn't the first online movie portal.
- Apple didn't make the first cell phone or even the first smart phone, or the first music player or the first home computer.
- Tesla didn't make the first electric car.
Still, the one criticism that startup hear again and again is that "You are late - it's already there".
It was not an obvious idea at the time, simply because there weren't that many people on the web. It was around the time that SSL was being developed  -- so if you were much earlier you probably couldn't take payments securely.
There were probably mail order catalogs that had websites, but I think that is a different thing than a "web store".
Also, Netflix wasn't the first online movie portal, but I'm pretty sure they were the first people to make a business out of mailing DVDs! It's crazy that they started like that.
Afaik, they didn't really carry any stock when they first started. They were re-selling mail order books.
A while back there was a documentary about Amazon's early years. The part that everyone always quotes is the thing about using doors as desks. (Which struck me as silly, doors are expensive compared to many large, flat surfaces.) Anyway, the part that really stuck with me was that they had one favorite mail-order place, except that shop had a ten book minimum order. So Amazon would order the one book someone wanted and then nine copies of some obscure book about snails that was never in stock.
I think the value was the interface and ease of searching, and not inventory and retail operations.
So, I don't know that it was the first or not, but Bezos was certainly not the only one thinking about it at the time.
But you're right, Amazon was basically there at the beginning of online retail. A better example is YouTube. Many online video sharing sites had started and died years before YouTube was a gleam in Janet Jackson's pasty http://usatoday30.usatoday.com/tech/news/2006-10-11-youtube-...
Remember this was well before Chrome came out, and Firefox was still nascent. So a lot of people were using IE.
I think Flash was already starting to fall out of fashion by then, but they realized there was a valuable technology deployed in it (video codecs).
Doing it right matters more than doing it first.
Google is a giant now, and has made the search engine market both mature and saturated (along with its competitors). Before Google came along, there were several other search engines, but the market wasn't at all saturated. It was much easier to enter that market with a well placed innovation in searching while the market was primed to grow even larger among a set of competitors who had not dominated it yet. The market was large enough that an innovative company would capture first time users and spread itself organically among them, eventually stealing them from other engines in the process.
Conversely, the search engine market has become saturated. To start a new search engine, you'll need to steal users from an existing search engine, because there is virtually no one who doesn't already use one. As a basic concept, it's extremely difficult to differentiate on the core idea of a search engine. You will not beat Google just by offering a new technical innovation, you'd likely have to beat Google by adding search innovations to a novel platform that is emerging to challenge Google before they capture that platform as well. That sort of combination would offer a new fertile market that hasn't been saturated. As an example, a search engine for applications would have been a legitimate threat, had Google not already developed it for Android and Chrome with Apple competing.
You can trace the origins of the ANN to the 40s and 50s. Since then, statistical ML has come into vogue a few times, but not like today. Phones and other data sources (plus the algorithms to properly deal with all the data) have ushered in our current renaissance.
I remember when I was a kid, you had huge binders of photo albums, and the total number of pictures that a family might own numbered in the hundreds. Now I take that many photos on a week-long vacation, or sometimes just in ordinary life, and my cloud backup has maybe tens of thousands. Multiply that by a billion cell phones and that's a lot of images out there.
Freedom of information.
Pervasive media piracy.
State level hacking.
Technofascist dystopia in general.
Smartphones (also enables vastly cheaper batteries and drone components).
Really neat, simple, iterative algorithm.
General and bland would be as akin to "analytic a priori". All bachelors are unmarried, that sorta thing.
Specific and surprising would be like "synthetic posteriori". Such and such plant is blue and grows in the Himalayas.
The real gold would be in the "synthetic a priori" findings. Blending the generalness of logic with the newness of empiricism. Like figuring out geometrical laws from observing nature. New information AND far-reaching implications.
Am I on to something here?
"While some trivial a priori claims might be analytic in this sense, for Kant the seriously interesting ones were synthetic."
[T]he more general the ideas you're talking about, the less you should worry
about repeating yourself.
When it comes to an idea, I believe that the broader I present the idea, the easier it is to start a conversation, because others are more likely to show interest, and eventually reach the point you find a focus point. However, I still repeat myself, because I wouldn't invent a whole new dialogue next time I bring up the same broad idea with another person.
On the other hand, I feel developing a product (startup or not), the more general the idea is, the harder for me to explain my ideas concretely, much like films have leading roles. The ideas present by the film can be broad, but you don't want camera rolling on 200 actors in 1 hour 30 minutes, would you? Your message can be interesting and novel, but I am going to be lost.
But yeah, on HN topics like "I quite FB", "security is hard", "Google is evil", etc are common here, but I still comment on those topics when I feel like to. My responses are usually similar, but I might add new thoughts, or rephrase what I had written before. I called this introspection. I believe we are not comfortable repeating ourselves, because we want to be interesting and original, but we still have the urge to try to perfect our speech the next time someone asks.
I am saying: I get nasty ineloquent on days I'm zoned into coding. Almost like I'd rather not say than say anything I judge to be imprecise.
Like this post.
ak, I believe you may have just written something moderately insightful. Anyone else?
Written language and code can afford the verbosity, because you can always review the earlier points to see how they tie in, but speech should be short and succinct, IMO.
I believe this is similar to (but not exactly) what is meant by "circumstantial speech" .
That said, the wikipedia article seems to indicate that what I'm trying to describe is similar to circumstantial speech, but actually isn't:
"Some individuals with autistic tendencies may prefer highly precise speech, and this may seem circumstantial, but in fact it is a choice that posits that more details are necessary to communicate a precise meaning, and preempt more disastrous ambiguous communication."
Does anyone know of a more accurate term for this?
A page of text is not meant to compete with the "classics", so if that's what you're looking for you shouldn't read this site at all.
This goes on to my same discovery: Life itself is a constant process of incremental trial and error builds-up. Over a few billions years, you get something out of it (human being playing snapchat)
If you keep counting from 0 to an infinitely large number, at some numbers you'll "discover": Windows 7, Windows 7 Korean Language, Microsoft Office, OSX, and every other game that human designed and developed. Plus a bunch of other software from alternate realities that compile on our machines. Cool.
The process the human are doing is not much different (albeit one can argue that it is much more efficient than stupidly counting) "Everything" is already there. The new Audi A4? It was already "possible".
If there is one thing that will change the future, it is our discovery of the link between "abstract" and "real" concepts. They share some important points that I'd not be surprised that "real" and "abstract" are the same thing/continuum. Like space and time.
A nice addition to the thought that, theoretically, even if you can find the Windows 10 source code by counting all integers, you can't actually do it within the lifetime of the universe without a smarter algorithm.
You can always find the successor of a given integer, but there's not really an analogous process for human discovery, where it's easy to go in circles. The process really is that different.
Are there theoretical situations where random searches are guaranteed to be complete on infinite spaces given "infinite time" (probability of finding solution approaches 1)?
It might have been easier to understand if bound to real world examples.
People often think that a field has been 'picked clean' and conclude that either no further progress is possible or that further discoveries are going to be rare and incremental.
e.g. "the future truths of physical science are to be looked for in the sixth place of decimals" -- Michelson, 1894
But there are always deep problems and this implies that unlimited progress is possible. The really big discoveries can happen at any time and are of an unpredictable nature, not least because they affect multiple fields. They leave behind plenty of smaller problems for everyone to pick up.
The advice I give which has produced the single biggest deltas in outcomes is "Charge more." It is so simple that I could literally print it on T-shirts and wear it to any event which discusses pricing. People know it is my catchphrase and sometimes I get knowing laughter when I say it...
... and then a few minutes later they've agreed to try charging more, despite having an accurate model which suggests "Hah, I bet when we ask Patrick about our new pricing he is going to ask us what it is, think about it for less than five seconds, and then suggest charging more." They knew what I'd say before I even got in the room, but even the tiniest marginal connection to their own pricing grid / customers / data pushes them to actually try it.
I was hoping for an example, but your example of repeating your catch phrase doesn't quite fit imo. There's no variation. Is there a variation of your catch phrase or message you're not mentioning here?
That's what happened to many of the ideas presented by Daniel Kahneman in Thinking, fast and slow. He obviously aimed for "general and surprising" but accepted as solid results the outcome of lone, irreproducible experiments.
We (our current culture -- it wasn't always like that) love originality and "surprises", but as a rule, the more surprising the result, the more scrutiny it should withstand.
In your example, perhaps the most lasting value of priming studies is a much greater understanding of how p-hacking actually misleads us. Everyone knew that it could in theory, but it was general and surprising that entire fields could have an apparent scientific consensus entirely based on p-hacking and file drawer effects.
> there is a special irony in my mistake because the first paper that Amos Tversky and I published was about the belief in the “law of small numbers,” which allows researchers to trust the results of underpowered studies with unreasonably small samples. (...) Our article was written in 1969 and published in 1971, but I failed to internalize its message.
We simply want to believe.
I guess all I can do now is hope that whoever is listening can see the value in incremental change :)
Stop being anxious, go out in the world and see what your ideas are worth.
- Capitalism would define their value on how much you'd earn from these ideas.
- Writers would value them based on how many readers buy your books.
- Developers would value them based on how many contributors your open-source projects has.
- Or die and keep your diary and maybe in 50 years you will turn out to be the genius who saw the future.
But still - none of that absolutely requires anyone to be anxious.
This implies that anxieties themselves have no causes.
> Stop being anxious
I'd like to see your advice on other things. "Stop being sick!", "Stop being afraid of spiders!", "Stop being introverted!"
If your anxiety is so strong that you can't do those things, then get therapy! It changed my life, and a good therapist can change yours as well.
Share your experience but don't tell others that your way will work for everyone.
In any case, you are wrong about the cause of anxiety. That might be a cause of it, but there are plenty of other causes. See in particular the "medical causes" section of http://www.mayoclinic.org/diseases-conditions/anxiety/sympto...
It can be a symptom of an underlying illness.
"Oh, you mean all I need to do to fall asleep, is just close my eyes and go to sleep?!"
In all seriousness, I mean, who doesn't have anxiety, right? If someone broke into your house, you'd start feeling anxious.
I focus on building things, on going outside and being happy.
And yet people still don't buy my product or offer me a job ^.^
If that doesn't make anyone start wondering what might be wrong, then I'd like to know more.
I'd start feeling murderous.
Namely NYC and Boston, especially if you are using a gun.
It's a shame that a lot of these jurisdictions are also "where the jobs are".
Fortunately, we are much more likely to be affected by so many other dangerous things rather than home invasion that there's just many things to be anxious about ^.^
I believe the key is figuring out when your view is unique. What I have been doing is asking people questions on their view of a problem or something I am thinking about and looking at the deltas there. I have not thought about it with the term delta. Maybe looking for deltas would be another addition to the toolkit when searching for insights.
I prefer to use the term contradictions. Sometimes that leads you to further insights.
People tend to forget that ideas are worth nothing. It's not that hard to build a model of the world which would be parametrisable for any possible outcome.
Then those parameters would be defined by your experience, which requires you to get out of your mind and earn on the outside.
1. The thinking/insight/ideas is in pursuit of proving my own special nature
2. The thinking/insights/ideas are purely theories and have no practical application
Notice that the word "problem" was used. What is meant here an actual problem that I am trying to solve with actual practical implications.
Let me clarify what I mean, using concrete examples:
In product development/startups/business space: "My customers are telling me their problem is X, but what they are doing or how they are doing it is Contradictory. Why is this?"
"Two customers have completely different and contradictory views on what feature/problem is important to them, why is this?"
The actual purpose is to understand your customer better so you can cater for what they actually need.
This part is confusing, can you clarify what you mean:
"Then those parameters would be defined by your experience, which requires you to get out of your mind and earn on the outside"
Right now I would say that I have some insights that I feel are really unique and interesting, at least to me, and maybe a few friends.
However, they aren't monetizable to fans or marketable to employers. This has been fairly evident to me after a year of youtubing and twittering and twitching and etc.
So, even though I enjoy it, I really start to question if my ideas are actually that great, or if the addressable market is just not very large.
Good luck !!! :)
- Obtain a large dataset of observations related to a phenomenon of interest (eg English text, bioimaging data,
economic reports, car-mounted camera recordings, etc)
- Develop a theory of the phenomenon, or revise a previous theory
- Build the theory into a lossless data compression program
- Score the theory by invoking the compressor on the dataset, taking into account the size of the compressor itself; lower codelength is better.
- Adopt or discard the theory as appropriate and return to step #2.
I believe that this is a valid variant of the traditional scientific method, in which data compression takes the place of experimental prediction. In Graham's terms, this idea is a small delta of novelty, but since it refers to a predecessor idea of tremendous significance and generality, it could be very important. The book is available here:
I've spent a few years pursuing this methodology in the domain of English text. The result is a sentence parser, which works quite well, but was built completely without the use of hand-labelled training data (eg the Penn Treebank). You can check out the parser here:
I'm always happy to talk to people about these ideas, ping me at daniel dot burfoot at gmail if you're interested.
Do you think this approach would work for something, let's start simple, like ballistics neglecting rotation of the Earth and drag? If you fed in thousands of starting velocities and angles, and the resulting distance traveled, will this process end up with equations of motion that are as compact as can be found in first year physics?
What this describes is a method for testing theories, not generating them. You still need to study the data to try and properly analyze it so you can understand the rules yourself, or at least be able to see the edges of them.
Now if you could find a way to generate moderately accurate equations automatically by analyzing the dataset, I think that would be a real leap forward. Is there a related mechanism to the one presented by the parent which could be used to generate theories?
There is not going to be any universal and practical algorithm for automatically generating the theories, at least in the short term. But you can think about algorithms that apply to particular domains. For example in my field of text analysis, you can imagine techniques for automatically inferring grammar rules from a large quantity of text. Some such methods already exist, but have not been pursued extensively.
We could also develop algorithms for inferring equations of motion from astronomical and celestial observations, as the parent mentioned. The compression principle wouldn't give you the real Newtonian equations, but it would correctly identify them as being superior to other candidates. But this would be a bit of an academic exercise, since we already have the Newtonian equations and relativity. What's more interesting to me is an attempt to build modern astronomical theories (eg about black holes, the Big Bang, cosmic inflation, dark energy, etc) into a compressor that will apply to an astronomical data set like the Sloan Digital Sky Survey. My guess is that such an attempt would reveal important shortcomings in the theories, or perhaps highlight regions of space that confound the theories.
Regularities in data/predictability of data?
The problem is that the facts which led to the success of the business are not the same thing as the best insights a founder can come up with about why it succeeded. The latter is subject to an incredible amount of confirmation bias and the simple desire to tell a good story—in fact you have to do that to get investment.
In reality, novelty of ideas is meaningless, because the massively overwhelming majority of ideas in the world never get executed on. Even within contexts where people and companies have the means, most ideas—even good ones—don't get executed on because they conflict with other ideas and don't win the battle for resources.
What matters for an idea is execution and context. If you bring the right resources: skills, connections, go-to-market strategy, smaller supporting ideas, and it gels with the current zeitgeist of whatever market you are in, then it can get some traction. From there you learn and gain more insights which can be leveraged to scale up. You do this over and over again, and if you are lucky you can make an 8, 9, 10-figure company.
By the time all this happens you'll have some tremendous insights, but they will be specific to the context in which they were gleaned. The "generality" we observe of these insights is just a result of our pattern-matching and story-telling brains. The "surprisingness" comes after the fact to varying degrees based on existing preconceptions and perhaps how the world has changed over time. In other words, I don't think there is such a thing as a hugely valuable insight per se, rather this: we have insights, we believe in them to varying degrees, and based on how well it maps to our actions and their results, we later declare the "value" of the insight.
"An audience finds a proposition ‘interesting’ not because it tells them some truth they thought they already knew, but instead because it tells them some truth they thought they already knew was wrong."
The most valuable insights...
Toward the end:
So it's doubly important not to let yourself be discouraged by people who say there's not much new about something you've discovered. "Not much new" is a real achievement when you're talking about the most general ideas. Maybe if you keep going, you'll discover more.
I really feel like Paul is conflating valuable and novel here. When you create something that solves someone's problem, who cares whether the ideas behind it are novel or not?
Like, I'm not sure what he's trying to get at.
If Paul Graham writes an essay then that is relevant to Hacker News so it should be upvoted regardless of whether it is shit.
Hacker News is not some game where people compete to create content with maximum merit. It is a source of new content relevant to this community.
The reasoning goes like this: X is described like a good thing and a lot of resources poured in it. But there are documented failures of X - are they spurious or causes by X not actually doing what is advertised?
More often than not the working answer "it probably doesn't work" which is often "a thing you can not say" due to general consensus, good feelings and above mentioned amount of resources poured in X.
PG, I see what you did there. The rest of the essay is just a setup for this single paragraph. This is your own small delta of novelty. Well done.
It reminds me that creating something more general is harder than creating something specialized for a specific problem. For programmers this seems to be obvious, but for others this is counter intuitive.
Philosophically this statement is false.
Mental health wise, it's a lot nicer to keep in mind than the truth of reality that you reside within.
(Malthus was partially ;) mistaken.)
There should be a twitter account that just summarizes rambling think pieces.
What he meant was F=ma combined with other formulas that make use of F, make up a system that's surprisingly useful while remaining simple to use.
I imagine you already knew that.
If you're acting as an editor, you can phrase your point better. if you're merely nitpicking for things to 'gotcha' someone - I assure you that's not a smart longterm strategy :)
The simple things are good to be reminded of, on a regular basis, that's why :)
And it is certainly not surprising that amateurs in general forget that F = ma is only valid if the mass does not change. The more general expression is F = dp/dt, where p is the momentum. But this, of course, is also only valid in inertial systems. It's not really important to the article but it does kind of annoy me that he uses the most special case of an expression in an argument about it being general.
He could have actually made the point about generality by comparing this expression to the most general one for the force (in a frame of reference that accelerates). That would have also shown why generality can quickly become infeasible in practice. If he knew how many approximations people make in the real world, not because they want to, but because they HAVE TO, his worldview might be a different one.
I feel like he's trying to make a point about a very specific scenario but doesn't mention it explicitly. Instead he tries to be general and therefore fails to understand that his view doesn't actually apply in general.
Hence, if time dilation exists (under increasing levels of gravity) "black hole" cannot form in any finite time. Since there are many massive bodies in our universe, solution to problem is not applicable.
So, in that context, "black holes" ARE GOSSIP!!!!
Let the "GOSSIP" wars commence.
Other than that, I think you make some very salient points, especially about the approximations that we make and the validity of those approximations to the specific applications/situations being studied.
However, I would not call it gossip since, by your reasoning, anything could be gossip then. I understand gossip as being something unimportant but the Schwarzschild solution was a major milestone in the understanding of general relativity. Moreover, all scifi movies considering wormholes and such, can be traced back to the usual visualization of the black hole distorting space time. Pretty consequential discovery I'd say.
Much as I like good SF (and even mediocre SF), I believe there is enough evidence to say that our understanding is very incomplete and that GR (though it give some good approximations in general) may be a complete furphy.
Our problem at this time is that any time conflicting evidence comes up. it tends to get either buried or ignore or those bringing it up get ad hominem attacked.
If the evidence is obviously incorrect then it should be a simple matter of showing exactly how it is incorrect. My observations of the actions of the proponents of GR are that they tend towards dogmatism and and not discussion, ridicule and not rebuttal.
If odd things are found, then the prevailing theory (in this case GR) should be able to fairly handle these discrepancies.
There are no "stupid" questions.
PG sometimes meanders into actual meaning. But the likes of Tim Ferris or Seth Godin absolutely excel at this drivel.
This (a very basic 400 word essay/post) needed "drafts" and 3 people going through them?
I like some of PG's essays, but this one just has a couple of trivial insights.
My point was different: several drafts and editors were needed for this tiny and banal result?
It's like seeing someone ordering a $10,000 AGA cooker, buying all kinds of spices, herbs and fresh ingredients, amassing several Kitchenaid appliances, getting into an apron and a chef's hat, and then proceed to make ...a grilled cheese sandwich.
That's only for when you actually distill complex ideas into simple expression. E.g. explaining a complex subject in a succinct and simple to understand way, like Feynman's lectures.
A mere simple expression of something banal to begin with shouldn't take lots of work, the same way writing "The sun is hot, we should better not walk on it" shouldn't.
I can understand if he were to write an opinion piece for a major newspaper. Or perhaps having Jessica give it the once over. Or another person with no need to acknowledge or thank them.
And it's certainly not representative of the world that the rest of us operate in when posting comments here on HN. You know the downvotes and gray out comments when someone doesn't like what we have said or doesn't agree with it.
How about an essay on why he has people read his essays before posting them?
One other thing. I don't think honesty requires someone to even give thanks like he does. I think that detracts from the essay and doesn't add to it. There is no requirement to give acknowledgement in that fashion if you are getting help in that way. Assumes the help is minor if the help is major you have to question why someone even is writing essays.
Lastly, I think this sets a bad example for younger people on the way up. The reason? You have to learn from your mistakes and from the brutal honesty of people and how they react to what you say. While this is not importantly to PG (he has already made it) I think constantly having others 2nd guess what you do is not the path to being able to think on your own feet.
 Like he is a world leader, or a corporate CEO, and has to tread carefully for fear of a bad outcome from his words.
However, there's nothing wrong with having trusted friends read your work. In fact, it shows respect to your readers, especially if you have a megaphone as PG does. Thanking your editors is polite and that is something we could use more of.