We Are Nowhere Close to the Limits of Athletic Performance - <AUTHOR> http://nautil.us/issue/51/limits/we-are-nowhere-close-to-the-limits-of-athletic-performance-rp?ref=hvper.com <comment><USER2> > We find a similar story in the NBA with Shaquille O'Neal. O'Neal was the > first 7-footer in the league who retained the power and agility of a much > smaller man. Neither a beanpole nor a plodding hulk, he would have been an > athletic 200-pounder if scaled down to 6 feet in height.

That's not really true. Wilt Chamberlain was taller than Shaq, was a highly competitive track and field athlete in high school and college, was often the fastest player _on his NBA team_ , had the strength to pick up or throw around other NBA players sometimes with just one hand, and had an incredible vertical leap as well. And, unlike Shaq, he did all this playing every single minute of every single game.

Like Shaq, however, Wilt Chamberlain's dominance led to rule changes, including widening the key.

Shaquille O'Neal was undoubtedly more powerful than any other center of his era, and almost any center of all time with the possible exception of Chamberlain. He was also relatively lean early in his career, but especially after he went to the Lakers, he increased his strength and body mass at the expense of his speed and agility.

<comment><USER3> Also, Wilt & Shaq are generational outliers that are not in any indicative of your typical pro athlete. Shaq is a really bad example for the article to use as indicating any short of progress in sports performance. The current NBA isn't filled with Shaq-like players. It's guard dominated with a heavy emphasis on 3 point shooting.

<comment><USER2> That's a fair point. The current NBA is also incredibly weird and positionless; the current champions have a shooting guard who is slightly taller than their power forward and occasional center and a small forward who is even taller, and there's a generation of young players who are seven feet tall but have the skill set of point guards and wing players. If anyone is the predecessor of this style of player, it would be Kevin Durant, who is the style of lanky seven-footer who has been pushed out of the center position but developed wing skills to compensate.

The decline of the center position is really weird, though. The emphasis on three point shooting is driven by analytics--it turns out almost every player is more efficient shooting threes over midrange shots--so I wonder if a similar conclusion has been reached about the post game.

</comment></comment></comment><comment><USER4> Anyone who hasn't seen the Netflix documentary on Ben Johnson should watch it, yes he took steroids and got popped for it, come to find out he had been taking steroids all the time and the tests were easy to beat, the story goes he only popped positive because Karl Lewis snuck a contact into the testing room to spike Ben Johnsons water before giving a sample. Have any doubts watch the documentary and watch Karl Lewis when asked about it and his response, he doesn't deny it at all and suggests that if that did occur it was fair play.

As to Lewis himself being clean, again watch the documentary there were only about 2 runners in that era (regularly making the finals) who were clean, the athletes know better than anyone.

Objectively Lewis was a full grown man and out of no where his jaw grew, displacing his teeth and he got braces to fix it as an adult. Jaw growth and braces were indicative of the steroids used at the time in the 80's and was common place with the track stars, who prior to jaw growth had perfect teeth.

Even in modern times in track what gave Russia's state sponsored doping program away was the simple fact that non doped athletes would be doubled over from fatigue at the end of events and the Russians would be smiling not even out of breath, like the article suggests world class is world class and so like I suggest the athletes will simply be in the best position to know when something is out of the norm.

As to Bolt, what makes him special as a sprinter is his size, once thought to be a detriment (like the article says), but he wasn't/isn't a freak, it is more along the lines of self fulfilling prophecy. Take Russia and China for example where they just pluck kids from school who are identified based on certain physical traits and go into state sponsored athletic training camps. Moreover, When you were a certain size you were just over looked by everyone including the coaches and put into different events, now that Bolt has broken the mold, tons of kids more inline with Bolt's body size are/have been identified and given the proper support and coaching, so in the near future we will see more and more sprinters similar to Bolt's measurements. This will inevitably lead to new world records in the short term without the need for genetic modification or peds.

<comment><USER5> Just to point out, the jaw size increase is from human growth hormone rather than steroids. I recall seeing photos of members of the Santa Monica track club athletes (Carl Lewis's club) and 7 out of 9 of their top sprinters had braces.

<comment><USER4> I'm to far removed from seeing the documentary, but they went into a little detail about the history of steroids or peds, and I definitely could be mistaken but I believe the ped of choice for these sprinters in the 80's was a horse steroid. Maybe some has watched the same documentary and can clarify.

Either way its obviously a side note and even if my memory serves correct, that's not to say HGH doesn't have a similar effect.

<comment><USER6> >horse steroid

They're all "horse steroids," generally, as veterinarians are a common source of grey/black market AAS. Winstrol was likely very common then, as was Deca- Durabolin and Trenbolone. Obviously good old-fashioned injectable Testosterone [insert ester here] was used as well.

As for HGH, I'm not sure it was all that common in the 80s, or really even now. The benefits for adult males are... dubious, to say the least; it's not like testosterone which we know how valuable it can be for athletic performance.

<comment><USER7> If a tested athlete used any of those compounds in the 80s they would have been popped for sure. All of those compounds have really long detection periods.

<comment><USER6> Watch Icarus or look into any of the state-sponsored avoidance programs. Your answers lie there.

Also Winstrol and Test Propionate (or Suspension) have short detection times, HGH didn't have a test until recently, and EPO was in the same boat.

</comment></comment></comment></comment></comment></comment><comment><USER8> We seem to be at the limit of the fastest fastball. [http://www.popularmechanics.com/adventure/sports/a6063/how-t...](http://www.popularmechanics.com/adventure/sports/a6063/how- the-105-mph-fastball-tests-the-limits-of-the-human-body/)

"However, even if the radar gun used last Friday gave Chapman 5 mph, his pitch still flirted with the maximum speed a human can throw a baseball, which Fleisig says is about 100 mph. Fleisig has found that adjustments to a pitcher's biomechanics, as well as better conditioning of the entire kinetic chain from the legs to the core to the arm, can improve a pitcher's velocity on his fastball. But he's discovered that as the pitcher approaches 100 mph, these tweaks and strengthening have diminishing returns.

"Another cause of the 100-mph ceiling owes to this: the amount of torque needed to throw in excess of the century mark is greater than the amount of force the ulnar collateral ligament (the elbow ligament Strasburg tore) can withstand before giving out, according to tests Fleisig has done on cadavers.

An addition quote from [http://www.nytimes.com/2013/09/17/sports/baseball/harveys- in...](http://www.nytimes.com/2013/09/17/sports/baseball/harveys-injury-shows- pitchers-have-a-speed-limit.html?pagewanted=all) .

"Fleisig, a biomedical engineer, knows what an arm can handle, and years of research give him the confidence to answer one of baseball's more intriguing questions: Is there a limit to how fast a human being can throw?

"His answer: Yes, there is.

"And, he adds: That limit already has been reached.

""Oh, there may be an outlier, one exception here or there," he said. "But for major league baseball pitchers as a group of elites, the top isn't going to go up anymore. With better conditioning and nutrition and mechanics, more pitchers will be toward that top, throwing at 95 or 100. But the top has topped out.""

<comment><USER9> Hybrid designer babies, splice in the ligament and fast-twitch muscle genes from a Cheetah.

This will work until DNA testing becomes part of the standard anti-doping screening.

<comment><USER8> Sure. And Cordwainer Smith mentions (in The Ballad of Lost C'Mell) that the cat underperson "C'mackintosh had been the first Earth-being to manage a fifty-meter broad-jump under normal gravity." At present what you mention is equally as science fiction as the nanotech predictions of the 1990s.

In any case, the author argues that "Athletic performance follows a normal distribution" and "The normal distribution we see in athletic capabilities is a telltale signature of many small additive effects that are all independent from each other."

I wanted to give a counter-example. Normal distributions don't have the hard cutoff that we've seen in pitching speeds.

Edit: "No other primate throws with anything comparable to human force. Chimpanzees, who are much, much stronger, pound for pound, than human beings, can throw, as any zoo visitor knows. But the best an adult male can do is about 20 miles per hour. A 12-year-old human pitcher can easily throw three times that fast." [http://www.nytimes.com/2013/06/27/science/evolution-on- the-m...](http://www.nytimes.com/2013/06/27/science/evolution-on-the-mound- why-humans-throw-so-well.html)

The hypothesis is that early humans, "around 1.8 million years ago ... [began] to hunt big game and needed to throw sharp objects hard and fast", or perhaps it was only "hundreds of thousands of years".

In either case, it appear that humans have specifically evolved for throwing, with most of the energy coming from the shoulders, not from long or cord-like tendons. Our genetics may already be near the optimal, with respect to single point mutations.

Not only might cheetah ligaments and muscles make little difference, they might actually be worse.

<comment><USER10> > In either case, it appear that humans have specifically evolved for > throwing, with most of the energy coming from the shoulders, not from long > or cord-like tendons.

that's not really true. as someone who can throw a baseball quite fast, you really want relaxed shoulders. tense shoulders are a great way to get injured.

from my experience throwing, most of the throwing power is generated from the hips. then it comes up your lats on your back which generates a whipping motion through the shoulder. you want this energy transfer from the hips to the arm to be as smooth as possible, hence loose shoulders. near the end of the throw, the triceps and then forearm engage to complete the whip. other than knowing this from throwing, it's pretty easy to know because these are the muscles that are sore when i haven't thrown in a long while.

<comment><USER11> Even someone without a practiced throwing motion can demonstrate the importance of the hips in the motion; just try throwing with arm only while standing flat footed.

</comment></comment></comment></comment></comment><comment><USER12> So we are getting better at finding those genetic outliers who continue to outperform at their given sport.

But this is becoming more and more detached from reality of the majority of us sitting inside the genetic bell curve.

Finding time in lives dominated by commutes, education and young families, finding sport that can be integrated into our lives, and building a society that encourages moderate athleticism should be a priority - shaving another second off a sprint does not it seems encourage millions to get off the couch - so we should invest in what does.

Otherwise sport is just another branch of the entertainment industry.

<comment><USER13> This isn't the whole story. High school track times are faster now than world champions 40 years ago.

<comment><USER14> I wouldn't quite go that far.

In 1936, Jesse Owens won the Olympics with a 10.3. Athletic.net[1] (which is not perfectly complete but close enough for reference) shows 33 high schoolers who ran 10.39 or better in 2017. So yes some are faster, but that's almost zero and 80 years later. None of these high schoolers have matched the 9.55 at the 1968 Olympics.

[1]: [https://www.athletic.net/TrackAndField/Division/Event.aspx?D...](https://www.athletic.net/TrackAndField/Division/Event.aspx?DivID=79871&Event=1)

<comment><USER6> >Jesse Owens won the Olympics with a 10.3

Jesse Owens also ran in terrible spikes on an ash cinder track. Jesse would threaten to break 10 flat if they used today's equipment with the very hard tracks in use today.

<comment><USER3> Owens also didn't have starting blocks.

</comment></comment></comment></comment></comment><comment><USER14> > Even the combination of an elite runner and anabolic steroids, though, was > not enough to outcompete a genetic outlier.

This ignores the (very likely) possibility that Bolt is also doping, albeit with today's designer drugs and not anabolic steroids. When testing catches up to today's drugs, we will look back at Bolt differently. He is definitely a "genetic freak" as they say, but there's more to it than that.

<comment><USER15> Indeed, Jamaica doesn't have strong anti-doping organizations and Bolt has teammates caught doping. I'd love to believe Bolt is clean, but I find it hard to give him the benefit of the doubt.

<comment><USER16> Same here. I really tried to believe that Carl Lewis was not doping, as he was one of my heroes as I grew up, but as the time passes I realize that he was most certainly doping. The same will probably happen to today's kids who grow up with Usain Bolt being their idol.

</comment></comment></comment><comment><USER17> When you have to rely on a one-in-a-billion genetic freak to make new records, we _are_ 'close to the limits'. When you have to have teams of scientists and coaches working to improve one individual just a tiny bit, we _are_ 'close to the limits'. It's not like you can pop a pill and run 100m in 5s, blowing away current records.

</comment><comment><USER18> This may be an unpopular opinion but I really want there to be leagues with no rules on performance enhancing substances just to see what the human body is ultimately capable of.

Michele Ferrari is pretty despised in the cycling scene but the research he was doing really highlighted what's possible with sports science

<comment><USER19> Every time this comes up, I need to ask.. who _decides_ to use this performance enhancement when the enhancement is applied to young children for maximal effect? That suddenly turns morally dubious, and we can't suppose that nobody would do that, because we know for sure that _somebody_ would.

</comment></comment><comment><USER20> I'm very excited to see genetic engineering allow amateur athletes who work very hard (often harder than professionals!) to to become good.

</comment><comment><USER21> > We're just scratching the surface of what genetic outliers can do.

That seems to be the crux of it.

Genetic outliers, yes. When I hear a phrase like "limits of athletic performance", though, I don't expect to read about genetic outliers, which, to me, are wholly uninteresting. The real limits of athletic performance if we mean genetic don't even end with humans.

Was hoping that this was going to be about people not fulfilling their athletic potential overall. This seems to be getting worse for the average person. I think we pay too much attention to genetic freakishness instead of the average, on many accounts.

</comment><comment><USER22> > By comparison, the potential improvements achievable by doping effort are > relatively modest. In weightlifting, for example, Mike Israetel, a professor > of exercise science at Temple University, has estimated that doping > increases weightlifting scores by about 5 to 10 percent.

Based on how blatant the difference is in other contexts (most obviously modern bodybuilding), I'm guessing that's actually the difference between people who got caught and people who didn't get caught, not the difference between doping and no doping.

<comment><USER23> We'll part of it is that what doping really let's you do is recover fast and thus train more. So in a lot of contexts it just reveals the limits of training more than the physical limits.

<comment><USER24> No, that is what people who make excuses for dopers, say about doping.

But the 1st order thing steroids will do is just make you stronger, immediately, by themselves, even if you don't train differently (or at all!)

The 1st order thing taking EPO or doing blood doping will do is just give you more aerobic endurance, immediately, by itself.

No doubt some 2nd order benefit may result from also being able to train harder / recover faster while using these drugs.

<comment><USER25> The misconception comes from the days when athletes stopped taking PEDs a month before competition to avoid getting caught.

</comment></comment></comment></comment><comment><USER26> Are they implying that Bolt isn't doping? Everyone at that level dopes. Everyone. So they are on an equal standing there. (source: there have been documentaries about this)

<comment><USER26> Nice job down voting. Just watch the documentaries. It's ridiculously easy to not get caught. Even if the whole government isn't aiding you (as is the case with russia). And the level at the top is just so tough that you have to dope. Every percent matters.

<comment><USER27> From the HN guidelines:

 _Please resist commenting about being downvoted. It never does any good, and it makes boring reading._

</comment></comment></comment><comment><USER28> Well I'm sure there will be continuous improvement, but it'll be a case of shaving off miliseconds I think.

The current crop of athletes have already essentially devoted their entire lives to eating/training etc just right so I think any further advances will be marginal. These aren't enthusiasts doing stuff on weekends anymore - they've got state level backing and large scale selection from a young age (see China).

(Above excludes possibility of genetic engineering obv).

</comment><comment><USER29> I think most advances will come from better materials. Faster balls, tracks, spikes, stronger shirts, etc.

<comment><USER30> the record book in swimming was obliterated by the LZR 'fastskin' swimsuit. 98% of medals won in swimming in the beijing olympics were won by athletes wearing the suit. 93 world records were set by athletes wearing the suit before it was banned. many of those records still stand

</comment></comment><comment><USER31> The fastest pitch is likely closer to 110 MPH given what Chapman has done. Take a clone of Chapman, but with gigantic hands, taller, and stronger.

And if the UCL is indeed the limiting factor, it's not hard to imagine a future where the ligament will be surgically enhanced via some kind of synthetic graft.

<comment> semi-extrinsic > it's not hard to imagine a future where the ligament will be surgically > enhanced via some kind of synthetic graft

I'm not convinced - biocompatibility is a bitch. Whenever someone tears e.g. an UCL or an ACL, there are no options other than transplanting in a human graft, either taken from the patient (often parts of the hamstring) or from a corpse.

<comment><USER6> > there are no options other than transplanting in a human graft

This isn't true anymore. Internal brace method is the most common advancement. There are other less ethical ones being done by select surgeons, too.

<comment><USER32> Less ethical?

</comment></comment></comment></comment><comment> Chiba-City I loved playing soccer and tennis. Heroes for little kids are nice. I grew up with some Baltimore Oriole playing families in Baltimore.

But why would anyone care? we suffer fools dumping taxpayer dollars into ludicrous athletic programs for lesser colleges and mostly empty new stadium sky boxes for corporate lobbyists.

Passive viewing of sports and entertainment is dull. Attentions and dollars are better devoted to efficient live musical performance. So many of my fellow DC software engineers turned out to be talented instrumental musicians. I presume that early ambidextrous and symbolic training cultivating skilled code slinging applied mathematicians is not coincidental.

My consulting firm did some work in drug discovery. We were already tapped out on brute force discovery by the 1990's. Elective medicine seems indefensible feeding kids synthetic food and leaded water.

Encouraging kids to suffer supersized heroes on drugs beating dogs and women is unwise. My own mathlete kid watches ZERO TV And loves Aikido.

Has demographic crisis, boredom and research attentions wasted on militaries driven good people mad?

<comment><USER33> Is Aikido better than sports? A lot of it seems to be based on a ton of bullshit. Imaginary feats of mystical founders and delusions that you can actually use it in a fight.

</comment></comment><comment><USER34> No probably not, but the overwhelming majority of developed world populations (USA leading in particular) are getting far less athletic and far more obese, which is certainly a limit on athletic performance.

<comment><USER35> Not really. More and more people know how to avoid getting fat, thanks to the internet. I'm 21 years old in a western European country and barely anyone my age is overweight, and a sizable minority even has a professional athletes body from working out.

<comment><USER36> Obesity is heavily correlated with poverty.

As inequality around the world grows, so will obesity, so at median, people will get less fit, while the outliers will become more athletic.

<comment><USER37> I hate to say it, but correlation is not causation. Unless you can provide some studies that show people who get rich e.g. from lottery winnings, also lose their weight and vice versa with proper controls for depression and the like there is no reason to believe that an increase in economic inequality will lead to an increase in obesity.

<comment><USER38> The lottery winner sample is a bad one because the argument about poverty causing poor health behavior is an overall lifestyle problem and not just a resource one.

Children who grow in the upper middle class or upper class will grow up with access and encouragement to participate in physical activities, parents who are better informed and able to construct healthier eating habits and the resources and cultural permission to use mental health professionals as needed.

Winning a 100 million jackpot after growing up poor can't change that.

</comment></comment></comment></comment></comment><comment><USER39> Re Freeman Dyson's prediction - actually we already directly convert energy from sunlight, using the chlorophyll we eat, believe it or don't. We just don't make that chlorophyll.

Amazing Discovery: Plant Blood Enables Your Cells To Capture Sunlight Energy Posted on: Tuesday, May 12th 2015 [http://www.greenmedinfo.com/blog/chlorophyll-enables-your- ce...](http://www.greenmedinfo.com/blog/chlorophyll-enables-your-cells- captureuse-sunlight-energy-copernican-revolution)

<comment><USER40> That article gives off a vibe of complete nonsense.

<comment><USER8> I'll add to that. Even if humans could convert sunlight into energy as well as plants (they can't), we would only be able to generate about 15 kCal/hour. [https://hplusbiopolitics.wordpress.com/2008/08/12/photosynth...](https://hplusbiopolitics.wordpress.com/2008/08/12/photosyntheti- people/) . That's well less than 1/10th of what we need just for basic metabolism.

Of course, we aren't covered with chloroplasts, not even close. So we're talking at best a teeny-tiny amount of what we need to live. There's very little reason for evolution to conserve these pathways[0]. Especially since we know that people can survive and be healthy on a meat-only diet in the arctic, where they are covered in clothes. This includes western Europeans who have not had any genetic adaptations for that climate or diet.

[0] The photosynthetic systems must not be digested, must be transported through the blood to the whole body, make it through the cell walls to get to the mitochondria, be maintained at the right concentration, with some way to excrete the waste products.

<comment><USER41> Relevant [what if] xkcd: "Green Cows" [https://what- if.xkcd.com/17/](https://what-if.xkcd.com/17/) It's a similar analysis, but it uses cows instead of humans.</comment></comment></comment></comment>


Why Johnny can't hypothesize: A discussion about math and science education - <AUTHOR> http://www.scientificamerican.com/blog/post.cfm?id=why-johnny-cant-hypothesize-a-discu-2009-10-26

<comment><USER2> This article is way off, on so many things.

 _Why are U.S. children so far behind in science and math compared with those in other developed countries?_

Because the US has fewer high performing Asians and more low performing Blacks/Hispanics than other developed countries. That's all there is to it.

[http://super-economy.blogspot.com/2010/12/amazing-truth- abou...](http://super-economy.blogspot.com/2010/12/amazing-truth-about-pisa- scores-usa.html)

 _Convincing star college scientists to enter the field of K-12 education can be a hard sell, especially when comparing salaries of public school teachers with those elsewhere in the science industry._

I don't know exactly what the "science industry" is, but in general this is bunk. K-12 education is paid vastly better (in terms of money and job security) than most scientists. Perhaps tenured profs do better, but most scientists are not tenured profs.

<comment><USER3> In case you didn't realize, that sounds incredibly racist.

<comment><USER2> That's why I like HN. I can make a factually correct statement with conclusions that are politically incorrect and not be accused of harboring racial bias or animosity towards people of other races.

However, in the interest of honesty, I will admit to racism in one arena completely unrelated to the discussion here - I prefer dating dark skinned women to light skinned ones.

<comment><USER4> I'm still not sure how to interpret your original post. Are you claiming that the source of the achievement gap is somehow inherent in "race"? Or are you simply pointing out the correlation to race, without making claims to its source (allowing for the actual source to be something else like income level)?

<comment><USER2> I'm claiming that either race directly, or something correlated with it, explains a large amount of test score variation. And once you correct for this, the US scores very well.

Also, should have linked to this post comparing Asian Americans to Asians.

[http://super-economy.blogspot.com/2011/01/how-well-do- above-...](http://super-economy.blogspot.com/2011/01/how-well-do-above- average-american.html)

</comment></comment></comment></comment></comment><comment><USER5> What a surprise, another article that blames the teachers. They are not the problem, the PARENTS are the problem.

The parents are the ones who think that the only place to learn is in school, and everywhere else you can play gameboy. The parents are the ones who think "being intellectual" is a bad thing and you should be playing football instead. The parents are the ones who opted-out of paying school taxes when they didn't have kids. The parents are the ones who don't make sure their kids are studying. The parents are the ones who yell at the teachers if their kid gets an F, instead of yelling at the kid. The parents are the ones who have driven all the good teachers away from teaching, or have beaten-down the ones who stayed.

You don't have to wonder why so many teachers have a standing appointment at happy hour every day.

</comment><comment><USER6> I think one of the comments on the original article sums up my thoughts:

      "Why? You don't think the fact that a majority of the US

population is superstitious, and teaches their offspring that the world is the pet project of a master magician might have anything to do with it?"

<comment><USER7> It's only going to get worse. Just look at all the efforts to stop evolution from being taught in schools, and, in at least one state, to make it illegal for teachers to grade answers as incorrect if the answer is supported by the religious beliefs of the student.</comment></comment>


Ask HN: How do you take positive and negative feedback neutrally? - <AUTHOR> It is something that you hear often - don't get too comfy with positive feedback and don't get too dejected with negative feedback and just use them to improve your product/startup. But how do you do that? Is there a special process that you follow in order to achieve it? Or is it something that you master over time and practice - kind of like meditation? <comment><USER2> I think actively trying to suppress a response to negative or positive feedback will have the opposite effect, just to get that out.

Framing feedback as an opportunity to improve and better yourself/your company, be it toning down something bad or ramping up something good, as opposed to a method for self-validation could help.

You could also look at it from two perspectives. From one perspective, feedback promotes improvement for the good of the company. In this light, negative feedback could be demotivating. The other perspective, preventing your company from declining in quality or regressing, could improve your motivation in the face of negative feedback and perhaps even prevent you from getting complacent with ample amounts of positive feedback.

Since you mentioned meditation, one way to improve at handling negative and positive feedback is to be mindful about it by accepting the feedback for what it is and also accepting your feelings towards it. In fact, meditation can help towards this. This can allow you to take a step back and analyse where to go from here as opposed to extremes of emotion clouding your judgement.

I think it still stings, especially if you invest a lot of yourself into your product. Like anything, it is a skill and it does improve with practice, especially deliberate practice.

</comment><comment><USER3> Most positive feedback is basically fluff. I am kind of a Shirley Temple-esque personality and I have a long history of attracting gushy positive attention and it has been enormously problematic. It almost never tells me anything useful about what I am actually doing right. In fact, it tends to suck the oxygen out of the room and make it impossible to have any kind of meaningful discussion about anything.

But, then, Ford supposedly said that if he listened to customer feedback, he would have been trying to build a faster horse. So, I will suggest a high percentage of people will not have good feedback for you, period. Even most people with the problem won't understand the problem space well enough to give good feedback. This is part of why metrics are so popular. Over time, I have become less focused on what people say and more focused on moving certain numbers. Is it getting me traffic? Is it improving the bottom line? Etc.

Most negative feedback is equally emotionally driven and uninformative. If people react very negatively, it can be useful to know that you are doing something seriously wrong, but it probably won't tell you _what_ you are doing wrong.

A couple of things are really useful and you won't see them often:

Statements quantifying relative or subjective value, i.e. "This works better/worse for me than (other thing)."

Statements quantifying absolute or objective value, i.e. "I need a thing that goes X speed and yours is the only one that does that" or "I need a thing that goes X speed and yours does not do that so it has no value for me." Or even "You have a typo/grammatical error/etc"

When I paid insurance claims, we were taught to evaluate red flags and refer things to the fraud department if there were enough suspicious indicators. A lot of that has to do with context and patterns of behavior. I already focused a lot on patterns of behavior, but working there firmed up some of my understanding of how to do that well. Some people will talk trash about you but use your product anyway. Others will say glowing things and not give you a dime. Actions always speak louder than words. Don't let their words distract you overly much.

</comment><comment><USER4> I don't think there is any special process other then realizing that most feedback is personal and such should be taken. For example let's say you make a blue ball. You like it. blue is your favourite colour. Then someone comes around and tells you it's terrible because it should be yellow. Other will tell you it's nice. They are all expressing their opinion and it has as much value as yours. Once you start collecting a lot of feedback you can maybe start to think that your opinion being only in a minority might not be the best choice.

There are extremes in everything and also some people give strong negative feedback because they want to see an improvement, some give good feedback because they don't want to make you feel bad. You need to think about it, put in perspective to what you think and try to extract only the relevant information.

</comment><comment><USER5> "Yeah, well, that's just, like, your opinion, man." © The Dude

Seriously, just try to look at the opinions critically, and even more so at your reaction to them. If you see yourself too involved, stop and think, why are you so winded-up about something someone said.

</comment><comment><USER6> >But how do you do that?

It boils down to keeping your identity small ([http://www.paulgraham.com/identity.html](http://www.paulgraham.com/identity.html)), which may or may not be truly possible in practice for humans who do not lead a monastic life.

</comment><comment><USER7> Separate the negative or positive aspect of a piece of feedback ( its polarity ) from its content.

Any feedback that is content-free ( purely positive or negative ) gives you no inspiration for an opportunity to create an improvement.

Any feedback that possess content ( regardless of its polarity ) gives you inspiration for an opportunity to create an improvement.

You control your reaction. If you choose to be open to being inspired by the possibility of an opportunity for creating an improvement, then you can also choose to meet that opportunity, reflect, and create an improvement that may work for you.

Feedback from someone other than you is not a necessary condition for this type of improvement, tho it can contribute, and it is often available and being offered to you.

If you choose to focus on the polarity of the feedback ( and get carried away with how "good" or how "bad" you interpret it as ), you may get in the way of focussing on the content.

Another way to think of it is that there are some very smart experts, who know exactly the kinds of things that could go wrong with whatever you are trying to achieve, and so there feedback can contain lots of relevant content, and it may just so happen that they, for whatever reasons owing to their own personalities, mostly express themselves from an adversarial point of view, and season their content with a lot of negative polarity.

Maybe that is kind of like Indiana Jones, in how the secret treasure always lies at the end of a cave of boobytraps and dangers. All those things are distractions, and if you navigate them correctly, you can slip past them, and get the treasure, and make it out with your head ( and hat ). If you lose your head, owing to the distractions, then that's your choice.

You can see separating the polarity of the feedback from its content as an opportunity to choose to either focus on what you are achieving and ignore and slip past distractions, or to focus on ego games and pretending others are wrong and you are right. Neither of these is right or wrong, tho one may work for what you want to achieve more than the other.

If your goal is what you are trying to achieve and that is what the feedback is about, the more you focus on content, and the less you focus on polarity, the more you are focussing on things that work to contribute to that achievement.

If you feel this may not be easy, then you can choose to see __that__ as an opportunity to create an improvement in focus.

</comment><comment><USER8> I try not to let positive feed go to my head by focussing on people better than me and knowing how much room there is for improvement. I try to take negative feedback as a gift pointing to the right improvements to aim for.

<comment><USER9> Right on about that. I'm a writer. Getting feedback is essential for me to generate useful docs. Getting a negative item is wonderful since that makes the doc more accurate.

I more or less ignore positive feedback, other than to thank the reviewer.</comment></comment>


Ask HN: What are the best books on startups? - <AUTHOR>

I saw this list (http://bit.ly/go7yE4) and wondered if there were any others. Not how-tos like four steps to the epiphany, but more general reading, maybe case studies, or theory, or something fun like that. What are your recommendations? <comment><USER2> The book I've learned most from is _Founders at Work_ : [http://www.amazon.com/Founders-Work-Stories-Startups- Problem...](http://www.amazon.com/Founders-Work-Stories-Startups-Problem- Solution/dp/1430210788).

<comment><USER3> I feel like in the interest of full disclosure, it should be noted that this is pg's wife's book.

I second the recommendation, however ;)

</comment></comment><comment><USER4> Hmm... a few that jump to mind for me would be:

The Art of the Start - Guy Kawasaki [http://www.amazon.com/Art-Start-Time- Tested-Battle-Hardened-...](http://www.amazon.com/Art-Start-Time-Tested- Battle-Hardened-Starting/dp/1591840562)

Outside Innovation - Patricia Seybold [http://www.amazon.com/Outside- Innovation-Customers-Co-Design...](http://www.amazon.com/Outside-Innovation- Customers-Co-Design-Companys)

Unleashing the Killer App - Larry Downes & Chunka Mui [http://www.amazon.com/Unleashing-Killer-App-Strategies- Domin...](http://www.amazon.com/Unleashing-Killer-App-Strategies- Dominance/dp/1578512611/)

Wellsprings of Knowledge - Dorothy Leonard Barton [http://www.amazon.com/Wellsprings-Knowledge-Building- Sustain...](http://www.amazon.com/Wellsprings-Knowledge-Building-Sustaining- Innovation/dp/0875848591/)

The Innovators Dilemma - Clayton Christensen [http://www.amazon.com/Innovators-Dilemma-Revolutionary- Busin...](http://www.amazon.com/Innovators-Dilemma-Revolutionary-Business- Essentials/dp/0060521996/ref=pd_sim_b_5)

Crossing the Chasm - Geoffrey A. Moore [http://www.amazon.com/Crossing-Chasm- Geoffrey-Moore/dp/00605...](http://www.amazon.com/Crossing-Chasm-Geoffrey- Moore/dp/0060517123/ref=sr_1_1?s=books&ie=UTF8&qid=1297570515&sr=1-1)

The Startup Game: Inside the Partnership between Venture Capitalists and Entrepreneurs - William H. Draper [http://www.amazon.com/Startup-Game- Partnership-Capitalists-E...](http://www.amazon.com/Startup-Game-Partnership- Capitalists-Entrepreneurs/dp/023010486X/)

Some of these aren't necessarily _about_ startups, but I think they all have something valuable to offer. YMMV.

</comment><comment><USER5> I don't see this here yet, but I really enjoyed all of the stories in Founders at Work (<http://www.amazon.com/gp/product/1590597141>).

Not sure how helpful it will be, but it is definitely a source of inspiration, and also possibly examples of how things can work. Either way, once I picked it up, I couldn't put it down.

</comment><comment><USER6> <http://steveblank.com/books-for-startups/>

</comment><comment><USER6> The tipping point [http://www.amazon.com/Tipping-Point-Little-Things- Difference...](http://www.amazon.com/Tipping-Point-Little-Things- Difference/dp/0316346624/ref=sr_1_1?ie=UTF8&qid=1297564819&sr=8-1)

<comment><USER7> I respectfully disagree. I find Gladwell's books to be somewhat unsubstantial.

Instead I would recommend that you read Steve Blank's "4 Steps To The Epiphany." Also, I picked up "Do More Faster" recently on recommendation from a previous thread, which I found fascinating. There's some great advice within both books.

</comment></comment><comment><USER8> A similar question was posted on Quora. See this link: <http://www.quora.com/What-books-should-entrepreneurs-read>

</comment><comment><USER9> Definitely agree with "Do More Faster." Great book with excellent advice. I also recommend "Startup Lessons Learned"

</comment><comment><USER10> The Origin and Evolution of New Businesses - Amar Bhide

</comment><comment><USER11> Good to great.

Blue ocean strategy</comment>


On Layout and Web Performance - <AUTHOR> http://kellegous.com/j/2013/01/26/layout-performance/

<comment><USER2> Excellent article. Most projects treat the client-side like a necessary evil and so I've seen pages with thousands of divs that can cause a hundred reflows for a single click. Not good, although at least it made the backend feel very fast in comparison!

And here's Kelly Norton's example code: <http://kellegous.com/media/upload/2013/01/layout.js>

<comment><USER3> I really like that he included a reduced case of sample code. It really makes it easy to understand the differences in the solution.

Also, that last line, that comment, heh.

</comment></comment><comment><USER4> Imagine my surprise when I groggily google Kelly Norton.

<comment><USER5> I've been battling with her in PageRank for years. I claim she isn't playing fair!

<comment><USER6> FYI, it took me a little digging around to figure out where your atom feed is. :-)

Here in case anyone else wants it: <http://kellegous.com/atom.xml>

<comment><USER5> Thanks. I've meaning to put the links back for a while and never have done it.

</comment></comment></comment></comment><comment><USER7> The right solution to this problem in general is to not do layout manually in script and instead do declarative layout in CSS. That, of course, requires more powerful CSS features, but those are happening. Several browsers now shipping calc() unprefixed and flexbox is well on its way; those should help a lot between the two of them...

</comment><comment><USER8> The little pop-up bubble in the lower-right corner showing the reader how long it took the page to render is pretty sweet.

</comment><comment> bink-lynch Very enlightening! I am building a single-page application, was one of the "unaware" that will definitely be much more mindful of this now. Thank you!

</comment><comment><USER9> Why does Element.innerText cause the browser to "layout?" The author said he might explain this in another article.

<comment><USER5> You are going to make me give away my future punchline. ;-) The short story is that innerText will include the line breaks that are introduced by text layout. A lot of people call innerText when what they actually want is textContent (which doesn't layout because is just a concatenation of the descendent text nodes)</comment></comment>


Strapi – Fast. Reusable. Easy to use. The next generation framework for Node.js - <AUTHOR> http://strapi.io/ <comment><AUTHOR> This is a new framework on the basis of koa. As the ORM used known waterline. Comfortable studio for designing API in the browser. And much more.

I found this today and was impressed.

<comment><USER2> Hi Kulakowla,

I am Pierre, one of the co-founder of Strapi.

First of all, thanks a lot for your positive feedback.

What did you especially appreciated in the stack (the open-source Node.js framework, the admin panel, the visual development tools included in the Studio...) ?

We have a public and active Slack, feel free to join : [http://strapi.io/support](http://strapi.io/support)

Bests,

Pierre

<comment><AUTHOR> Thank you, Pierre. I've joined to your channel in Slack.</comment></comment></comment>


Accelerated interviews for fired employees - <AUTHOR> http://www.layoff-aid.com/ <comment><AUTHOR> A friend of mine was laid off ([https://techcrunch.com/2016/12/13/disqus-lays- off-11-as-it-p...](https://techcrunch.com/2016/12/13/disqus-lays-off-11-as-it- plans-a-deeper-focus-on-data/)). He spent time interviewing for a new job and found that it sucked. Companies move super slowly because recruiting/hr expects candidates to move slowly because of job and limited time. So he's finding candidates and companies willing to move fast.

</comment><comment><USER2> Founder here. We don't deal with fired. We connect people from SF startups affected by layoffs with local startups that can hire quickly. Getting laid off != getting fired. Recruiters want our candidates, but don't otherwise know how to snag them.

<comment><USER3> whats the difference? regarding laid off/fired.

<comment><USER4> Being fired is usually the result of poor performance from the employee or violating company policies.

Being laid off happens when the company is performing poorly and isn't necessarily any fault of the individual employees.

<comment><USER3> and whats the difference? how can you tell layoffs and firings apart?

<comment><USER2> Thank you for asking. We Googled "layoffs vs firing", and got the following from Susan P. Joyce on Job-Hunt.org:

"Being laid off is NOT the same as being fired because it is not considered to be the fault of the employee. It is, actually, the fault of the employer. A layoff is often called a "reduction in force" or "down-sizing." ... This is often the reason that more highly-paid employees seem to be on the layoff candidate list."

Here's an article from Jan 2016 listing many VC-backed startups that laid employees off: [https://techcrunch.com/2016/01/08/burn-slower-or- vaporize/](https://techcrunch.com/2016/01/08/burn-slower-or-vaporize/)

Here's a newer article from this year that also lists different VC-backed startups that laid people off: [https://venturebeat.com/2017/01/14/early- layoffs-and-closure...](https://venturebeat.com/2017/01/14/early-layoffs-and- closures-in-2017-suggest-a-rocky-year-ahead-for-tech-industry/)

All the while, the tech scene and general economy have been _growing_. Layoffs in tech are a byproduct of the accelerated lifecycle of VC-fueled startups, leaving unsuspecting employees to unexpectedly look for a new job without having one, wasting valuable time and earning potential.

Existing job-search processes usually take months from kickoff to signing, as it takes time to both find the right fit and move through a company's various interview steps. Our platform will address the first problem by broadly circulating candidates to hiring startups that want to know about newly- available talent, and we address the second problem by incentivizing employers to compete on speed of interview process. If they don't, they'll simply lose these local, experienced candidates to some other firm.

Layoff-Aid only accepts candidates affected by layoffs from SF tech startups.

Let me know how I can clarify further.

<comment><USER5> Unless a company is shutting down, the first to be laid off are (or are _perceived to be by upper management_ ) "poor performers".

<comment><USER2> Would love to learn from data if you have any to back that up. From what we've seen, top reasons that determine who gets laid off include those who: 1) get paid well (the layoff is a desperate cost-cutting measure) 2) are randomly selected (the company is acknowledging that layoffs are not performance- related) 3) either got hired most recently or have most tenure (an attempt to reward longtime employees or respect those who just joined)

<comment><USER2> There's also the "entire department" (often post-acquisition) rationale. In any case, your perception is pretty common, and that creates a hiring opportunity for savvy recruiters who know better and don't pre-judge.

<comment><USER2> Here's today's example of an "entire department" layoff at SoundCloud: [https://techcrunch.com/2017/07/06/soundcloud-the-youtube- for...](https://techcrunch.com/2017/07/06/soundcloud-the-youtube-for-audio- cuts-173-jobs-closes-san-francisco-london-offices/)</comment></comment></comment></comment></comment></comment></comment></comment></comment>


Buying a new domain name, buy variations of that domain also? - <AUTHOR>

Because I'm cynical, I always buy up any and all variations of the target domain name, ie. misspellings, phonetics, etc.  However, there's also a lingering doubt that it's not really worth it, after all, I could use that money for more Ramen noodles :).  What's your recommendation/experience? <comment><USER2> I'd not build a business on a non-.com name unless I intended for it to be a part-time/passive business whose primary traffic stream was SEO. Also while the URL hacks are cool to us, our parent's just don't understand them and will type the site name + .com.

I usually like to get the .net and sometimes the .org of my product, but seldom go beyond that. While it's in the domain registrar's interest to sell you .info, .biz, .us, .co, .whatever else, I don't see a lot of benefit. The one exception would be if you are marketing to a non-US country (eg. if marketing to the UK, perhaps get bot the .com and the .co.uk).

If a domain doesn't pass the "ear test", where someone hears your name and must be able to find your domain on the first attempt, I'd definitely get other popular variations.

If you do buy a lot of variations in the beginning, be sure and forward them to your main site while tagging them with Google Analytics. That way, you can check GA and see which ones send traffic before deciding if each is worth renewing. Shameless plug but I wrote a blog post on how to do this at [http://www.keepingitrural.com/leverage-unused-domain- names-b...](http://www.keepingitrural.com/leverage-unused-domain-names-boost- website-traffic)

</comment><comment><USER3> if whatever you're building on the primary domain is successful, you'll end up purchasing the variations down the road anyway and usually at a huge premium because someone else will have bought them up to hitch a ride on the gravy train. Might as well buy them early and save money.

<comment><USER4> I really disagreee with this. If you become massively sucessful on a myspace/google/facebook level then perhaps. But has pg bought yombinator.com? Where does dig.com take you? What about gamil.com? twiter.com? micorsoft.com?

Forget about the misspellings, you're not going to lose a lot of traffic to them, people will soon realise they're in the wrong place. Save your money for better things like advertising and servers.

<comment><USER3> you overestimate the brain power of the average internet user.

<comment><USER4> del.icio.us was bought by yahoo before it became delicious.com. how many people typed the wrong domain in? Quite a few probably. Not enough to stop it being a huge success, not enough to prevent it being acquired by yahoo. I think it's a non-issue.</comment></comment></comment></comment>


Five Creative Strategies Every Startup Should Consider When Producing a Video - <AUTHOR> http://www.techvibes.com/blog/five-creative-strategies-every-startup-should-consider-when-producing-an-online-marketing-video-2012-05-22

<comment><USER2> Most viral videos contain either one or a combination of these strategies. Very informative.

</comment><comment><USER3> Very informative article. Thanks!</comment>


Microsoft releases Web Sandbox under open source  - <AUTHOR> http://www.infoworld.com/article/09/01/29/Microsoft-releases-Web-Sandbox-under-open-source_1.html

<comment><USER2> Maybe: Dion Almaer of Ajaxian fame wrote

"The (MS) post makes it a little hard to know what exactly is open sourced (mentions the runtime, is that everything?). It also doesn't link to an actually repo. The only code that I can find is this piece ( [http://websandbox- code.org/js/1.1165.01272009_debug/sandbox2...](http://websandbox- code.org/js/1.1165.01272009_debug/sandbox2.js) ) which is copyright Microsoft. I have an email into the guys to get more info."</comment>


Privacy is over. Here comes sociality. - <AUTHOR> http://news.cnet.com/8301-13641_3-10437644-44.html

<comment><USER2> It's an interesting article, but I'm not sure how I feel about the word 'publicy'.</comment>


Are you tired of all the negative stimulation? - <AUTHOR> I have noticed I have started to retreat more and more to my safe spaces. It seem every where you go now weather it been in person on on-line to tune into your favorite television show, movie, news station
web site, or friends chat session is flooded with negative garbage. I am getting so tired of all the dark light being casted on things. I say its time for a positive approach to things. I mean if we start to flood each other and our selves with positive things maybe just maybe an over all shift in personal wellness as well as social wellness could start to take place. Just a hopeful thought. <comment><USER2> It's all over the place.

Fox News - screw the democrats. MSNBC - screw the republicans. CNN and BBC "try" to stay neutral but you know who's on who's side. (there shouldn't be sides; it should be the side of what's best for the country)

New car comes out? It's ugly; it's too slow; it looks like this other car.

New game? Really? Another sequal to ... ?

Even on some very specific topic forums; someone asks a question and half the board jumps down their throat. IT WAS A QUESTION. Relax.

Forget new products from Google or Apple or whomever. I don't get it; if you're an Android user, what are you doing hanging out on an Apple news website? Did you think they were gonna write about Amazon products?!? (bad example, but...)

How quickly we've forgotten about if you have nothing nice to say, don't say anything at all.

So - trying not to read user comments anymore; trying not to watch the news so much, but that's hard - you want to "try" to self educate on important topics and hear both sides. Otherwise, it's becoming exhausting and I question what we're doing as developers now a days. When is contributing our time (even if it is often for money) to build these "communities" no longer worth it.

</comment><comment><USER3> Yes. I've killed almost all of my social media, and am most of the way there with HN (which is unfortunately also surprisingly negative these days).

No TV or movies except for some older stuff. Trying pretty hard with "print" news, though my id is still a sucker for the unceasing flow of outrage stories.

Even trying to just pleasantly chat or be helpful to people seems ill-advised these days. Everyone is on edge and seemingly ready to snap at a moment's notice.

The solution seems to be to just check out, farther and farther. Spending time with nature and my immediate family. Reading the classics.

</comment><comment><USER4> Seriously tune out. Go for a hike. The wild turkeys on the hillside don't care, my cat seems to not care. Go outside and get some air.</comment>


Fun with convex polygons - <AUTHOR> http://www.wildbunny.co.uk/blog/2012/03/29/fun-with-convex-polygons/

<comment><USER2> If the polygon is self-intersecting, the area around which the algorithm traverses the edges clockwise will be subtracted from the rest of the area traversed counter-clockwise. While interesting, I have yet to find this fact actually useful.

Edit: for more fun with polygons, check out Pick's theorem [1].

Since I'm guessing that pretty much everyone on this site has a copy of CLRS, the Selected Topics chapter on Computational Geometry has a good overview of cross product tricks. The convex hull algorithms are also interesting, useful, and very simple to learn.

If you're finished with that and are actually still interested, look at the Rotating Calipers method. It's a way of addressing all antipodal pairs of a given polygon, which serves as the basis for a whole whack of algorithms. Example - finding the narrowest rotation of a polygon. Some of you may recognize this as the solution to the last (and easiest) problem at the 2011 ICPC world finals [2].

[1] <http://en.wikipedia.org/wiki/Pick%27s_theorem>

[2] (PDF) [https://cm.baylor.edu/ICPCWiki/attach/Problem%20Resources/20...](https://cm.baylor.edu/ICPCWiki/attach/Problem%20Resources/2011WorldFinalProblemSet.pdf)

</comment><comment><USER3> All of these sorts of things start making a lot more obvious intuitive sense when you learn some basic "geometric algebra". See e.g. <http://news.ycombinator.com/item?id=3284160>

</comment><comment><USER4> The area method works with non-convex polyons, too. Not sure why he thinks it won't. See <http://en.m.wikipedia.org/wiki/Shoelace_formula>.

<comment><USER5> always knew this as "surveyor's formula"

</comment></comment><comment><USER6> Computational geometry algorithms are often fairly easy to explain, but implementing them robustly in quite tricky. Not only are there many edge cases, you also need to do your calculations with arbitrary precision (at least sometimes) [1]. You're generally much better off to use some library like CGAL [2] instead of rolling your own.

[1] [http://www.mpi- inf.mpg.de/~mehlhorn/ftp/classroomExamplesNon...](http://www.mpi- inf.mpg.de/~mehlhorn/ftp/classroomExamplesNonrobustness.pdf)

[2] <http://www.cgal.org/>

<comment><USER7> Not to mention the somewhat less license-encumbered Boost libraries Geometry ([http://www.boost.org/doc/libs/1_49_0/libs/geometry/doc/html/...](http://www.boost.org/doc/libs/1_49_0/libs/geometry/doc/html/index.html)) and Polygon ([http://www.boost.org/doc/libs/1_49_0/libs/polygon/doc/index....](http://www.boost.org/doc/libs/1_49_0/libs/polygon/doc/index.htm))</comment></comment>


How Quid uses deep learning with small data - <AUTHOR> https://quid.com/feed/how-quid-uses-deep-learning-with-small-data <comment><USER2> The baseline I'd like to see this compared to is the not-very-deep-learning "bag of tricks" that's conveniently implemented in fastText [1].

[1] [https://github.com/facebookresearch/fastText](https://github.com/facebookresearch/fastText)

<comment><USER3> Great point! I considering using fasttext as a baseline, however in practice fasttext really didn't work well at all with the small data set, much worse than the tfidf baseline. I think Fasttext's classification approach might not work well with such a small dataset. I'm not sure but I suspect its because it tries to learn embeddings - but there just isn't anywhere near enough data for that. I'd love an outside perspective on this.

<comment><USER2> Fair enough. That's a useful comparison to know about.

But I'm wondering how you get around that with the neural net. In the post, you said there are only a few hundred labeled examples, right? How can a neural net with hundreds of parameters set those parameters to anything reasonable, and not overfit, when there are about as many parameters as examples?

<comment><USER3> Great question and I share your intuition but I think its all properly regularizing your model. I guess for neural networks, Dropout works really darn well as a regularization strategy. I could have tried to see whether performance dropped significantly without dropout.

</comment></comment></comment></comment><comment><USER4> If you're interested in Sequence to Sequence tasks (e.g. neural machine translation or abstractive summarization) with small data, check out our recent paper from Google Brain tackling this problem (disclaimer, I'm the first author): [https://arxiv.org/abs/1611.02683](https://arxiv.org/abs/1611.02683)

<comment><USER3> Thanks! I'll check it out. I have also been reading about abstractive summarization - hard problem it seems!

</comment></comment><comment><USER5> Curious how you guys got training data for this. Did someone have to go through and rate whether or not a sentence was quality or not? And how many training examples did you use? You say it was "difficult to develop a large set" but I'm curious how large that set actually was.

Edit: Also, do you think more data or a "better" or "more sophisticated" model would make the results better? I would guess more data would trump better model, but not sure.

<comment><USER3> Thanks for the comment! There were a few hundred sentences of each, collected internally from from a wide number of descriptions.

Yes, I'd definitely agree- more data is what we need here for further model improvements.

<comment><USER5> I actually had this issue recently when trying to get training data for a project of mine as well [0], so I built an app [1] as a way to more easily classify documents.

Basically I have simpler interfaces and the ability for multiple people to quickly answer questions like this on a set of data. Easily exportable in the end as well. If you're interested in using that to get some more data on sentences, let me know. I'm really curious how much better the results get with more data, and this could help.

[0] [https://bigishdata.com/2016/11/01/classifying-country- music-...](https://bigishdata.com/2016/11/01/classifying-country-music-songs- is-an-art-getting-training-data/)

[1] [https://fierce-mountain-21498.herokuapp.com/](https://fierce- mountain-21498.herokuapp.com/)

<comment><USER3> This is really great idea. Actually if there is something you can share along these lines, that would be amazing. I know Crowd Flower has a great "internal only" tool, which is kind of similar to what you are designing, but you have to pay for it. Actually I think there is a huge need for a generic tool along the lines of what you have started to build.

<comment><USER5> Haven't heard of CrowdFlower but yeah this is along those lines. Pretty similar. But I could definitely make something quick to fit this specifically. I've been looking for other uses along with what I'm doing and this fits exactly. Shoot me an email at the address listed on my profile and I can get going.

</comment></comment></comment></comment></comment><comment><USER6> Comparison is wrong between tfidf on words and CNN char. You should use char ngrams along with LR and this will beat all your classifiers with high probability. This is because your CNN char does not have enough data to draw all the useful chat ngrams. Doing it as preprocessing and passing it to LR is in practice always better on small datasets. You can go one step forward and add layers and test an MLP on your char ngrams.

<comment><USER3> Thanks, would you mind expanding? I also played around with some char CNNs. They had similar performance.

</comment></comment><comment><USER7> It's worth keeping in mind that learning from few examples is not such a big deal. What is really hard to do (and a long-standing problem in machine learning) is learning a model that _generalises well to unseen data_.

So the question is: does the OP really show good generalisation?

It's hard to see how one would even begin to test this, in the case of the OP. The OP describes an experiment where a few hundred instances were drawn from a set of 50K, and used both for training and testing (by holding out a few, rather than cross-validating, if I got that right).

I guess one way to go about it is to use the trained model to label your unseen data (the rest of the 50k) and then go through that model-labelled data by hand, and try to figure out how well the model did.

We're talking here about natural language, however, where the domain is so vast that even the full 50k instances are very few to learn well. That doesn't have to do anything with the model being trained, deep or shallow. It has everything to do with the fact that you can say the same thing in 100k different ways, and still not exhaust all the ways to say that one thing. So 50k examples are either not enough examples of different ways to say the same thing, or not enough examples of the different things you can say, or, most probably, both.

It's also worth remembering that deep nets can overfit much worse than other methods, exactly because they are so good at memorising training data. It's very hard to figure out what a deep net is really learning, but it would not be at all surprising to find out that your "powerful" model is just a very expensive alternative to Ctrl + C.

It's just memorised your examples, see?

</comment><comment><USER8> There's something strange about the ROC curve here. It seems that the feature engineered and logistic regression methods can pick out some examples very easily (20% true positive rate at a very low false positive rate) but the CNN seems to not be able to make many predictions at a low false positive rate. It then catches up later. It's almost like it can't pick out the easy examples, but does just as good a job on the harder ones.

<comment><USER3> This is a great point, would be worth further investigation. And I agree with your general interpretation. It would be interesting to look further at where CNN is failing to detect bad ones and where the feature engineered one picks them up.

</comment></comment><comment><USER9> The link to LIME looks a bit out of place - LIME is an algorithm of explaining classifier decisions which is most useful for cases when you can't inspect weights and map them back to features. For TF*IDF + Logistic Regression there is no need to use LIME, one can just use weights and feature names directly. LIME is more helpful for all other models (there is a lot of caveats though), not for the basic tfidf + linear classifier model.

<comment><USER3> This is actually a great point. Thanks for sharing. I should maybe considering removing LIME in that context or changing the wording.

</comment></comment><comment><USER10> I can't seem to find where the sample size is mentioned. It mentions that Quid has 50,000 company descriptions, but is n=50,000 tiny in thr ML/DeepLearning world?

I do neuroscience research and where I am coming from I have maybe n=150to200 per class. And that is not generally regarded as a tiny sample.

<comment><USER11> The issue is those 50,000 descriptions aren't labeled good/bad. Someone had to pick a subset of them and label them, so my guess is they did this for maybe 100 or 200 descriptions.

<comment><USER3> This is correct. We had 300-400 examples of each

</comment></comment></comment><comment><USER12> > A downfall of CNNs for text is that unlike for images, the input sequences > are varying sizes (i.e., varying size sentences), which means most text > inputs must be "padded" with some number of 0's, so that all inputs are the > same size.

Actually Kim's model you're using doesn't require padding because it uses k-Max over time pooling.

Also kuddos for NOT updating your word embeddings during training! A lot of people are doing it, but IMHO it's a mistake most of the time.

<comment><USER3> Are you sure about the padding? On page 1746, bottom right it says "padded as necessary". And intuitively it makes sense that all your inputs need to be the same size for a CNN.

</comment></comment><comment><USER13> about that detecting _generic text that conveys little information_

Can I have that for my email? (Seriously) And as browser plugin? Oh and on telephone, TV, radio and in real-life would be also nice.

It's probably also a nice predictor of startup success, developer quality and sales guy effectiveness.

I just wonder if I would ever read or hear a Politician again.

Very inspiring...

<comment><USER3> haha, absolutely. It takes a lot of intelligence to detect non- informativeness. you might enjoy: [http://journal.sjdm.org/15/15923a/jdm15923a.pdf](http://journal.sjdm.org/15/15923a/jdm15923a.pdf)

</comment></comment><comment><USER14> What's the difference between softmax with categorical loss ([0, 1]) and sigmoid binary loss? ([0/1])

</comment><comment><USER15> Since word embeddings were the starting point, I'm wondering what would the impact be if they'd stretched the vector sequences to the same length using linear or whatever interpolation as opposed to zero padding the sentences.

<comment><USER3> Could you elaborate? I'm not sure if I follow

</comment></comment><comment><USER16> Why do you not have a dev dataset? Gridsearch over your test dataset is bound to overfit

</comment><comment><USER17> Wait, isn't "deep learning with small data" just machine learning, after all the buzzwords cancel themselves out?

I thought the whole point of "deep learning" is its approach to using data.

<comment><USER18> The point of deep learning is using a deep graph, like a neural network with a lot of layers, not the amount of data.

However, picking millions of parameters with small amounts of data is unlikely to work well.

<comment><USER19> It seems, at first blush, like using a very complex model to fit a very small amount of data is a recipe for some serious overfitting.

</comment></comment></comment><comment><USER20> Is all machine learning called "deep learning" now? Where is the line between "normal" machine learning algorithms and deep learning?

<comment><USER3> I think deep learning can be seen as a class of machine learning techniques with more flexibility and which uses neural networks (usually with quite a few layers).

</comment></comment><comment><USER21> I used to know some Quid people back in the day, good to see them here (and that they're international now, congrats to them).

</comment><comment><USER22> really nice article -- easy to follow, sensible steps, clean code. I haven't done too much text ML and this was a nice piece to follow - thanks!

<comment><USER3> I appreciate this!

</comment></comment><comment><USER23> What about FastText?

</comment><comment><USER24> This post is a joke. Seriously, it amazes me that the entire industry seems fixated on a handful of techniques, just like they were with random forests 10 years ago, just like they were on SVMs ten years before that, just like they were base neural networks before that. There's a simpler way, nature almost requires it.

<comment><USER21> > There's a simpler way, nature almost requires it

This is a normative statement, do you have empirical evidence?</comment></comment>


Don DeLillo deserves the Nobel - <AUTHOR> https://www.bookforum.com/print/2701/why-don-delillo-deserves-the-nobel-23926 <comment><USER2> A favourite DeLillo quote from an old interview:

> I ask him what attracted him to writing, whether he studied literature or > was stirred by certain authors or books. "No, no," he says, "I didn't do > anything. I don't have an explanation, I don't know why I wanted to write. I > did some short stories at that time, but very infrequently. I quit my job > just to quit. I didn't quit my job to write fiction. I just didn't want to > work anymore. I think more than writers, the major influences on me have > been European movies, and jazz, and Abstract Expressionism."

Source: [https://www.nytimes.com/1991/05/19/magazine/dangerous-don- de...](https://www.nytimes.com/1991/05/19/magazine/dangerous-don-delillo.html)

And yeah, he should get the Nobel.

</comment><comment><USER3> There are many writers who deserved the Nobel prize but never received it. Joyce, Kafka, Borges, Proust, Tolstoy, to name a few. The prize has been so consistently politicized over the years that it's hard to see it as a measure of much of anything other than how much a bunch of Swedish academics happen to like that author.

If it were up to me I might pick Thomas Pynchon or Cormac McCarthy over DeLillo for a Nobel prize, but there are many other worthy non-American candidates

<comment><USER4> How many Nobel prizes have been so far? 120 or something like that. For more than a century of literature. By definition there will be great writers left out.

It is nobody's fault or bias.

<comment><USER5> I don't know, maybe _it is_ someone's fault if a system with arbitrarily defined rules expressly made for awarding those who deserve recognition doesn't award all those who deserve recognition?

<comment><USER6> Nobel Prize is just some dude who wanted to do something nice with money he made selling dynamite. There's no reason to imbue it with responsibility for picking which authors deserve to be immortalized.

<comment><USER5> Sure, it may be too much to say it's someone's "fault". My point is just that even the people who give Nobel prizes probably agree that the aforementioned authors deserve getting something at least very similar to it, they just didn't get it because of some fake scarcity that implies someone else deserved it "more". So although no one has any obligation to change the tradition, it might be a good idea to do so.

</comment></comment></comment></comment></comment><comment><USER7> There is no better time to read DeLillo's "White Noise" and learn about "The Airborne Toxic Event".

<comment><USER8> That book mentions a baby whose first word is "Toyota."

Probably somewhere in the world a baby's first word will be "Corona."

<comment><USER9> My sons first multisyllabic word was "OK Google." 15 seconds later the Google Home was unplugged and it's still sitting on the mantel unplugged two years later.

<comment><USER7> ha! but maybe not too surprising given the origin of the word googol

</comment></comment></comment></comment><comment><USER10> Without expecting anything or even knowing DeLillo, I bought a cheap faulty copy of "Libra" a few years at a train station bookshop. It is a brilliant novel for reasons I am not nearly eloquent enough to describe, and I very much doubt that the point DeLillo wanted to make could be phrased in less than the novel's 400 pages (which I think is true for most (if not all) great novels and the main reason why I was always extremely sceptical of anything resembling the classic "write down what the book is about" exercise in school).

<comment><USER11> I had the exact same experience with DeLillo. The opening scenes with the boy travelling in trains with his face glued to the window as the train "smashed through the darkness" got me since I used to travel by suburban trains a lot. From there, a portrait of a man emerges that's the opposite of the usual biography. Biographies tend to be portraits drawn with a strong hand, dark pencil, clearly outlined, full of details and colors and leave no ambiguity. If intimate moments are at one end of the spectrum and their consequences are the far other end, DeLillo moves between the two like only a true craftsman can.

Of course, there is a gimmick in the book. I didn't realize that at first. I don't remember at what point and like usual gimmicks it hits you and you react as you realize whose story this is.

As an engineer, I live in a world full of definitions and determinate actions and consequences. Literature is what I have access to that constantly reminds me that there is more that meets the eye and truths are relative. Don DeLillo's literature ranks right up there.

<comment><USER12> >As an engineer, I live in a world full of definitions and determinate actions and consequences. Literature is what I have access to that constantly reminds me that there is more that meets the eye and truths are relative

It's a truth I dreadfully came to realize over the last few years. Not about literature, although that is a great way to figure it out and enforce the sensation, but about the world. Ideas, things that I took for granted for so long with my scientific and data nurtured mind no longer have the same hold. Like a glacier that forever seemed eternal they are now melting but not have not yet melted completely, I cannot see what's behind the glacier. That's were the dread comes in.

<comment><USER13> You might want to read 'The Crying of Lot 49' by Thomas Pynchon, or not. It's a fairly short book.

<comment><USER12> Thanks. I've been meaning to start reading Pynchon for a while now. This gives him another boost in the proverbial ladder.

</comment></comment></comment></comment></comment><comment><USER14> I have never read DeLillo, but reading this makes me think not that he deserves a Nobel prize, but that the author of the article should stop holding the Nobel prize in such high regard. It's like being outraged that your favorite film didn't win an Oscar.

</comment><comment><USER15> The first DeLillo book I ever read was _Ratner's Star_ , inspired by the many quotations Clifford Pickover interspersed throughout his mid- to late-nineties works.

One such quote haunts me to this very day: " _No definition of 'science' can be complete without a reference to 'terror'._ "

</comment><comment><USER16> Is anyone here a DeLillo fan? Seems like a natural place for me to ask for recommendations.

If I loved White Noise but didn't get much from Underworld, which DeLillo book would be best to read next?

<comment><USER17> Every book before Underworld is more like White Noise than they are like Underworld. Libra is probably the best one. If you like (American) football, then "End Zone" is good.

</comment></comment><comment><USER18> I enjoy reading something that is written by someone passionate about the topic, and I enjoyed this perspective, but I disagree based on my admittedly limited experience with DD.

I've read white noise and zero-k, and found both underwhelming. To be fair, I read these after having read most of DFW work - which I find far superior - which probably spoilt it for me. I didn't find the prose good enough to make up for the lack of a story. Nor the themes that interesting or well explored.

<comment><USER19> Based on the same limited exposure to DeLillo, I'd agree with you.

"Zero-K" was so boring, I dropped it maybe 75% way through. In general I enjoy both genre and "literary" novels, but Zero-K felt deliberately anodyne: meandering minimalist pseudo-scifi optimized for the sensibilities of the "New Yorker" readership.

</comment></comment><comment><USER20> As someone who loves to read but has no formal background in Literature, I'm very intrigued by the ways in which people rank authors so as to find the one most deserving of some award. The article provides a handful of criteria, including things like "striking and realized style", "consistency of excellence".. how are these measured? Can reasonable people disagree? I don't mean to say that it's all arbitrary. I have this feeling that it's not, but at the same time it's impossible to directly quantify or measure in a manner persuasive to everyone. I have no idea if Delillo is deserving or not, but the discussions sounding who is and who is not, what criteria are used, and how authors are measured against those criteria are the most fascinating part to me.

</comment><comment><USER21> These sorts of debates are silly. "Gravity's Rainbow" deserved the Pulitzer. Even the Pulitzer committee thought so. Yet it didn't get it.

Awards are not really a meaningful way of recognizing the merit of any kind of artistic endeavour. Sometimes they get it right, but often they do not.

<comment><USER22> I'd heard GR was so great, tried to read it, abandoned it just a few pages in. Having watched too many award winning/artistically acclaimed films too, I now know to stay away from them. Seems they're more about the critics getting one up on someone than is it actually worth spending time on.

<comment><USER21> It's amazing but a pretty tough intro to Pynchon. If you're going to read him I would recommend "The Crying of Lot 49" (a fun short novel) or "Slow Learner" (A set of short stories). "Inherent Vice" would maybe be a fun one to start with too.

It's not for everyone in any case. One of my best friends jokes about the fact that every time I say I like a book, for a while she would buy it, read a chapter, hate it and not read any more.

<comment><USER23> there's a few points where people tend to give up on it. i myself stopped reading it twice at the giant cocaine adenoid, and again when the man chases the harmonica into the toilet. never finished it.

</comment></comment></comment></comment><comment><USER24> The opening scene of Underworld, enacting a baseball match, is some of the most electrifying writing I've experienced (& I dislike spectator sports, and know zip about baseball).

</comment><comment><USER25> > Do you find it as obvious as I do that Don DeLillo richly deserves to > receive the Nobel Prize

> The inner workings of the Swedish Academy are opaque,

Huh? How do we know its obvious if we don't know what the criteria is.

</comment><comment><USER26> I completely disagree. I think Don Delillo has an unbelievably cool writing style (especially how he only writes one paragraph per page and makes sure his words LOOK AESTHETIC in addition to conveying meaning). But DeLillo has essentially zero significance in American culture.

No millennials read or connect with his work, and only very few boomers do. I find Delillo's work largely hostile to readers that don't share his exact super-wide frame of references and age.

I like DeLillo but the idea of giving him a Nobel is an absolute joke, save the Nobel for artists who actually influence other artists and cultures. DeLillo just doesn't have much influence and his highly verbose style is transparently hostile.

<comment><USER27> I suppose you think Olga Tokarczuk or Svetlana Alexievich are more popular with millennials?

David Foster Wallace and Harold Bloom both have called Delillo one of the greatest living authors. I and quite a few other people I know in my age range (mid-20s) have enjoyed him without sensing his work is irrelevant to our demographic. Even his denser works like Underworld read like a 'pageturner' relative to his contemporaries like Pynchon or even Wallace. Let alone other writers in the canon like Dostoyevsky.

My criticism would honestly be that his writing is overly stylized and lacking in nuance. He inherits the hyperbolic, poetic quality of McCarthy but often applies it to the mundane and the result sometimes feels overwrought and overdramatized vs realistic. Zero K specifically felt like a fan fiction version of William Gibson's non sci-fi stuff like Zero History. And most of what he is trying to convey he just says outright in a 3rd person omniscient voice.

I actually think he is very culturally relevant and influential but I sense that if you were to evaluate his writing through the lens of academic comparative literature like the Nobel Prize committee (not the standard literature should be held to imo) it would fall short of most other laureats, Bob Dylan notwithstanding

<comment><USER26> > My criticism would honestly be that his writing is overly stylized and > lacking in nuance. He inherits the hyperbolic, poetic quality of McCarthy > but often applies it to the mundane and the result sometimes feels > overwrought and overdramatized vs realistic.

Could not agree more.

Bob Dylan and DFW deserve Nobels, IMO. Both of those guys have fans of all generations.

I feel like DeLillo is a "writer's writer." People like DFW applaud him, as you point out.

I just don't agree that DeLillo has anywhere near the amount of influence as, say, DFW.

I'm frequently amazed how large and diverse DFW's fan group is.

DeLillo seems to only appeal to writers. His work is very obscure, even within educated niches.

</comment></comment></comment><comment><USER4> Another American white man receiving the Nobel for literature? <\- This will be the headlines in the Guardian. Why not pick African or Asian writers who don't write in English and aren't famous?

My point is that no matter who the Committee in Sweden choses, there will be people writing how stupid that decision was.

<comment><USER28> " _Eschew flamebait. Don 't introduce flamewar topics unless you have something genuinely new to say. Avoid unrelated controversies and generic tangents._"

[https://news.ycombinator.com/newsguidelines.html](https://news.ycombinator.com/newsguidelines.html)</comment></comment>


AI Swarms on the Blockchain - <AUTHOR> http://www.barisser.com/ai-swarms-on-the-blockchain-f8f56f4f8b14

<comment><USER2> This is sort of the premise of Ethereum. Ethereum is supposed to be a better Bitcoin, with lots of bells and whistles. More scalability, with a not-fully- replicated blockchain, programs which represent contracts stored in the block chain, and other gimmicks.

I think someone should try Etherium in a MMORPG before using it on real money.

</comment><comment><USER3> Just because its a decentralized system, does not mean the problem is best solved with a blockchain. It is but one tool in the toolbox.

<comment><USER4> This needs to be repeated more often.

"Lets use the block chain to solve X"

Is often the most short site solution, and over looks a lot of problems with the underlying block chain. Permance of publicity is messy when applied to electronic information.

</comment></comment><comment><USER5> I don't understand the insistence that robots in the future not be specialized. Quite the contrary, I think they'll be highly specialized, and the ant metaphor agrees.

<comment><USER6> I agree that the phrase "non-specialized" is a bit tricky. Ants are mostly non-specialized in structure (there are only a handful of forms within the colony), but individuals take on specialized behavior based on the conditions that their put in. I think stem cells could be a better metaphor.

</comment></comment><comment><USER7> I had posted a discussion to Reddit[0] about a year ago that touched on a similar idea. Its a model for AI using a community of simple IA that as a whole becomes the AI. It injects social behaviours into the IA to govern how they interact with the community and to allow bias to develop among groups, and domain proficiencies to develop within individual IA. Because I envision the model being distributed, the proposed implementation includes a blockchain-like ledger of points of confirmed knowledge. I'm really not all that knowledgeable on the subject of AI but given the relevance and knowledge of HN I figured I'd toss it here to see if anyone wants to read a wall of text and give feedback. I have a backlog of books on AI I want to read, so if there's anything you'd like to add to my reading list after skimming through the idea I'd appreciate any suggestions :)

[0] [http://www.reddit.com/r/artificial/comments/1t5525/community...](http://www.reddit.com/r/artificial/comments/1t5525/community_based_approach_to_ai/)

</comment><comment><USER8> This is almost already considered (as others have mentioned) in Etherium and related bitcoin-related thinking - lookup "Decentralized Autonomous Corporations". The part you're adding is the incarnation (or maybe "inferriation"?) of the DCA into a robotic body, which is a pretty nifty connection.

</comment><comment><USER9> See Byzantine Fault Tolerance if you don't want to deal with a centralized ledger: [http://en.wikipedia.org/wiki/Byzantine_fault_tolerance](http://en.wikipedia.org/wiki/Byzantine_fault_tolerance)

</comment><comment><USER10> systems of record, got it.

<comment><USER11> Who watches the systems of record? Who watches the builders of the systems of records?

repeat ad infinitum or ad nauseam, whichever.

<comment><USER12> There are a finite number of repetitions until the onset of nausea, so the latter.

</comment></comment></comment><comment><USER13> Is "Follow me on twittter" really part of the article ?

It feels like the whole purpose of this thing is getting followers.</comment>


Dictionary of Algorithms and Data Structures (1998) - <AUTHOR> https://xlinux.nist.gov/dads/ <comment><USER2> Just to mention one that's usually quite ignored, I love the simplicity and usefulness of the Levenshtein distance: [https://xlinux.nist.gov/dads/HTML/Levenshtein.html](https://xlinux.nist.gov/dads/HTML/Levenshtein.html)

I once implemented it in typical scenario where sales people had to look for a client, but it could be written as: 1/ That Client With A Strange Name, Ltd. 2/ The Client With Strange Name, Ltd. 3/ That Client With A Strange Name 4/ [etc]

It worked really well and avoided lots of duplicated entries.

<comment><USER3> Yes, but the downside is that (afaik) you can't use an index to quickly retrieve the matches in order. You really have to scan your complete dataset on every search.

Besides, related to this, does anybody know of a good Javascript implementation of a 3-way merge of strings, and perhaps also of JSON-like structures?

<comment><USER4> You can store the values in a trie (e.g., with one node per character in the string). Exact lookup in the trie is O(string_length), like a hash table. Inexact lookup can similarly walk the tree, but explore side branches within a certain budget.

So if your string is "abc", you'd follow the node for "a", then the one for "b", but _also_ the one for "c", at a cost of 1 (because dropping the "b" incurs an edit distance of 1).

<comment><USER5> > Exact lookup in the trie is O(string_length), like a hash table

It's worth noting that some standard libraries (Java's JDK for one [1]) will cache the value of String.GetHashCode(), meaning string lookup in a HashTable is constant time average (but O(n) worst-case due to collisions).

[1]: [http://mindprod.com/jgloss/hashcode.html](http://mindprod.com/jgloss/hashcode.html)

</comment></comment></comment></comment><comment><USER6> I often look up algorithms there, it's a great resource. Unfortunately, you cannot search for parallel algorithms specifically and need to know what you're looking for anyway.

I was wondering whether someone could recommend similar resources (or books) for _parallel algorithms_. These are still very underrepresented on websites and in books, often just an addition or mentioned in passing by.

Any recommendations?

<comment><USER7> "Algorithm Design: Parallel and Sequential" [0] -- developed at Carnegie Mellon University.

[0] [http://www.parallel-algorithms-book.com/](http://www.parallel-algorithms- book.com/)</comment></comment>


The AI Index 2019 Report - <AUTHOR> https://hai.stanford.edu/news/introducing-ai-index-2019-report <comment><USER2> I'm pretty sure there is a ~2002 "Nanotech index report" out there which looks a lot like this. Oh looksie; I am right:

[http://www.nanotech-now.com/CMP-reports/NOR_White_Paper- July...](http://www.nanotech-now.com/CMP-reports/NOR_White_Paper-July2002.pdf)

<comment><USER3> True but I am not sure "nanotech" was used by top S&P 500 companies and their engineers on a daily basis.

<comment><USER4> Actually it's quite analogous.

When nanotech became a hot concept, the goal posts were moved so that companies could claim they were nanotech companies even though they were using pretty basic chemistry. No nanobots required.

And now we're seeing a lot of statistics being rebranded as AI because the latter attracts investors and journalists.

<comment><USER3> AI is the term used by marketing division and clueless public. Researchers don't use that term without a special need. FAANG engineers actually use ML approaches.

</comment></comment></comment></comment><comment><USER3> >> Diversifying AI faculty along gender lines has not shown great progress, with women comprising less than 20% of the new faculty hires in 2018.

I am wondering what is % of women doing PhD in the same field and whether it is growing. Without the latter number growing it would be hard to have a greater % of women among new faculty hires.

<comment><USER5> We'd also need to see numbers on new positions and freshly available positions. Even if the number of candidates is relatively stagnant, they can't get jobs if their number is larger than the number of positions available. Many of the doctoral candidates I knew in school couldn't find positions in academia because of market saturation.

<comment><USER3> >> Many of the doctoral candidates I knew in school couldn't find positions in academia because of market saturation.

The situation is now drastically different compared to say 40 years ago. That is why so many PhDs leave for industry to be better paid. The latter is possible for CS guys but in other domains the situation is pretty bad since they don't have easily accessible highly paid industry jobs.

</comment></comment></comment><comment><USER6> > In a year-and-a-half, the time required to train a large image > classification system on cloud infrastructure has fallen from about three > hours in October 2017 to about 88 seconds in July 2019. During the same > period, the cost to train such a system has fallen similarly.

3 hours to 88 seconds? Wow... I wonder if that's been further reduced today (December 2019)

</comment><comment><USER7> I get that these bullets points are answering What instead of Why but for those that are more readily discernible, like "In a year-and-a-half, the time required to train a large image classification system on cloud infrastructure has fallen from about three hours in October 2017 to about 88 seconds", what's causing this? Are models getting smaller without a loss in accuracy? Is training distributed over a greater amount of cheaper machines? Personally, I'd be more excited about the former rather than the latter. We can't all afford MegatronLM-type experiments - [https://nv- adlr.github.io/MegatronLM](https://nv-adlr.github.io/MegatronLM).

<comment><USER8> Both. Companies are certainly building bigger and bigger clusters for training.

At the same time though, consumer GPUs have gotten significantly faster (compare e.g. an Nvidia 2080TI to a 980TI), and learning algorithms keep improving / better learning algorithms become more widely used (e.g. Adam instead of stochastic gradient descent).

<comment><USER9> And also, architectural search allowed for neural networks to use more efficient builtin blocks, using many less parameters, and achieving the same accuracy with smaller models (and lowering training cost)</comment></comment></comment>