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Applied Machine Learning Is a Meritocracy (machinelearningmastery.com)
127 points by theBashShell 15 days ago | hide | past | web | favorite | 87 comments



Once upon a time, I had an employer who was looking for a machine learning expert. I mean, we had a brilliant mathematician who was breaking serious ground in the field, but we needed an expert, apparently. We were having trouble drawing experts out of Silicon Valley, and our resident genius said "Hey, I satisfy all of the requirements for this job you've posted, and I'm already doing the work. Can you promote me from this crap software-dev role you stuck me in?" and the company's response was "No, it clearly states in the posting that you'd need a PhD in machine learning." We promptly lost our genius. If only TPTB knew that it was a meritocracy!

In short: article's claims sound fishy; your lived experience may vary.


Meritocracy is a big word.

Chess is a meritocracy. So is tennis and sales. Anyone can play. The best player wins.

Chess coaching is not. Better coaches might win more or get better gigs, but stuff other than coaching "merit" can play a big role.

But rather than getting stuck in a semantic argument... What the article means is that it's a relatively accessible field, on the way that software engineering is. The formal pathways are not as locked in.

A motivated and talented individual can bootstrap a career without formal education, qualification or approval.

All this is relative to, for example, civil engineering, law, medicine... There you'll need qualifications earned via established formal channels, gatekeepers and such.


Could one say that meritocracy is not meritocracy? No matter what skill you measure, a population with adequate nutrition since conception is going to be far better than a population where malnutrition impacts both pregnancy and children.

So what is the take away, especially with applying this to all areas of our lives? We can do something to try to equalize the workplace, the chess tournament, or the tennis court. But what about equalizing the stage or the bar?


Define "merit". You seem to want to use it to mean something like "potential merit", but that's a pretty slippery concept. Nobody, or very nearly nobody, lives up to their "true potential". It's difficult to define and even more difficult to measure, if it's even possible to do either.

In terms of actual merit, as measured by actualities and not potentials, a healthy population is going to have more merit than an unhealthy population. If that feels weird to say, well, it's just a restatement of the why you want populations to be healthy and why you want to help unhealthy populations become healthy. It isn't because healthiness is somehow an abstract goodness disconnected from any real effect, it's precisely because it represents a real loss in capability.

Personally I don't like the idea of trying to equalize the results at the final measurement bar, like the chess tournament, because that just removes all incentive to improve actual health. We should strive to make people really better and healthier, not break our measurement tools for effectiveness and healthiness, thus guaranteeing a lack of ability to improve either.


>Nobody, or very nearly nobody, lives up to their "true potential".

I agree.

But how do we discuss reasons that are or aren't justified to be taken into account. For example you can break down potential blockers into temporary and permanent. Being sick or the death of a loved one can temporarily hurt your potential. Poor nutrition or a brain injury can permanently hurt your potential.

Do we judge people based on if they can overcome anything holding them back? Or do we wait for them to overcome it before we judge them? What if we are the gatekeepers of a method to overcome our limitations (such as the person deciding who gets to attend university)?


> Chess is a meritocracy. So is tennis and sales. Anyone can play. The best player wins.

I'm not sure you are having the correct definition of meritocracy in mind. A meritocracy is a system where the actors who provide the most benefit to the society, benefit the most. However, in chess, tennis, etc., there is no real benefit.


The term "meritocracy" can be defined in various ways.

Originally it was coined as a satirical characterisation of a hypothetical stratified future society so obsessed with test performances in early years that all power became concentrated in the hands of adults who had demonstrated youthful aptitude and were thus assumed to not need to prove themselves any further thereafter since competition could only demoralise lesser minds; the author took the view that the "merit" of passing test thresholds would often be dependent on access to sufficiently expensive early years education and would resemble and often simply be a justification for upholding traditional social class divisions

As for tennis, I think it's fair to say that tennis fans consider Federer et al to provide them with considerable enjoyment, and far more so than less talented players whose games they don't watch, or indeed most people working in non-entertainment jobs who can only help a few people at once and/or find it difficult to prove how much better they are than other people in the same role


> As for tennis, I think it's fair to say that tennis fans consider Federer et al to provide them with considerable enjoyment

The problem here is that "meritocracy" reduces to "free market", where everybody is simply paid for the benefit they bring to others, and where only the few best win.


Free marketeers often argue that markets are a better reflection of merit than alternative systems. I am considerably more ambivalent towards markets than this, but still think the fact that Federer is (i) disproportionately better compensated than other tennis players and (ii) better compensated than the average person is congruent with his performances having significant merit relative to people who cannot do what Federer does. At the very least, it is impossible to not to agree that Federer has significant merit with respect to the average tennis player (unlike, say, a programmer who is good at salary negotiations, well networked and lives in SV with respect to a lower-earning programmer who is merely better at every relevant aspect of software development) which I think was the OP's point.

And my original point was that meritocracy wasn't even originally conceived as a "good thing", never mind a utopian distribution of wealth and power allocation according to some ideal standard of social utility. Other people have subsequently chosen to [re]define meritocracy as some sort of aspirational standard for allowing more talented people to succeed; people defining 'meritocracy' with respect to the propensity of that skill to generate revenue are making as valid a use of the term as anyone else.


I know HN frowns on this sort of comment, but am perplexed by the downvotes here. Do people genuinely find an explanation of what Michael Young's book which coined the term was about objectionable or irrelevant?


X is a meritocracy, and everyone with skill and imagination may aspire to reach the highest level.

Where X is [machine learning, tennis, chess].


I wonder how normal stories like this are. Was this just one bad manager in one company, which you remember because of how surprising it was? If so, maybe the core claim that software is a meritocracy holds.

Or are stories like this common and everywhere?


Or are stories like this common and everywhere?

Very much so. Bad management is afraid of competence, because good performance cannot be argued away. I've seen this.


They simply play safe. If you hire someone with PhD it's very unlikely that anyone will ever blame you for not taking that other random smart dude instead. The other way around you might get into a trouble for your choice. It's just how bureaucracy works, protecting your butt first, and everything else comes 2nd.


I find the key factor the be company size.

When I worked for a Fortune 500, credentials mattered. Possibly more than competence.

I'm working for a much smaller company now and it's significantly closer to a meritocracy (or a "who will generate the most obvious value - even if it means working 90 hours per week" ocracy).


In a previous workplace we had a very capable part-time instructor. This fellow was never converted to a full-time position (eventually they got fed up and left); instead management kept recruiting externally for the full-time instructor position. They went through 3 or 4 people in as many years because the new recruits were glaringly incompetent. They were, however, innocuous and unthreatening. So far, no consequences for the departmental chair.


This is the HR version of “Nobody ever got fired for bringing in IBM”.

It’s true till it’s not.


Not a genius but had something similar happen. Was literally doing the work already and successfully. My coworkers and boss all vouched for me but the company had a policy. There are probably other companies where a similar policy that effects single person that works there.


So many times policy goes out the door if a Director or VP wants a specific person for whatever reason.


HR: no sorry, it’s policy

Worker: but you set the policy, it can be whatever you want it to

HR: ...

Saying “policy” must be a cover for a real reason that the company wants kept secret


Super common. More common than the opposite.

In fact a version of the above story has happened in the last two companies I worked for.


Right but, are most hiring decisions like this? If most hiring / firing decisions are based on ability (which is the case everywhere I've ever worked) then its a meritocracy with flaws. That is to say, if these stories surprise and disappoint you then the overall philosophy is that its a meritocracy and you're disappointed that its flawed for not being meritocratic enough.

As far as I can tell, even obsessing over credentials happens because its a proxy for merit[1], and we care about merit. Its often a lousy proxy, but our industry as a whole didn't care about merit, why would anyone care to look at a candidate's credentials?

[1] "Nobody gets fired for choosing IBM" -> "No recruiter gets fired for hiring a PhD"


Seriously, yes. This happens all the time. I recently finished a Masters in CS with a focus on data science and machine learning from DePaul University, and I built predictive models that saved my previous employer hundreds of thousands of dollars every month. They had multiple machine learning positions open, but they told me they wanted Ph.D.s from University of Chicago level schools.

Now I lead a team of analysts and junior data scientists at the University of Chicago.

That company is still making money hand over fist.

By the way, the point of the concept of meritocracy is that it depends on performance, not on some proxy variable.


Worth noting that the person who coined the term "meritocracy" did it to criticize the use of just those proxy values, particularly education, rather than actual performance:

https://www.theguardian.com/politics/2001/jun/29/comment


So I have something of a different experience, not exactly with DePaul or U of C students per se, but let's say, A and B respectively, where A=practical and B=theoretical.

A or B students could generally get the job done, but B students tend to be able to go deeper because of their greater theoretical horsepower. I could assign them tasks of greater difficulty and they will figure it out on their own and deliver.

If the organization only requires A-level talent, then let's be honest, there's no difference between A or B students. The majority of enterprises out there really only require A-level talent.

But if your organization has the kind of challenges that require B-level talent (a minority of organizations, to be sure), I think you might struggle with A-level talent. I faced this first hand when I learned that I couldn't scale because I was limited with the A-level talent that I had and was spending an inordinate amount of my time training and guiding them that I barely had time to do my work.

In general you are correct, but in some very specific situations, my experience has been there's value in identifying the right kind of talent that fits the problems you are trying to solve.


It's not uncommon.

But there is sometimes more going on than meets the eye. If it's an A.I/M.L startup, the number of PhDs is a significant factor in fund raising. Being able to say "we have 6 PhDs on staff" will open doors.


Just ignore the fact they're not in the field of CS or mathematics. ;)


Recruiters/managers are very picky about the Masters/PhD requirements, even if the corresponding day-to-day work does not necessarily warrant it.


It's normal in my experience. It's not necessarily that these managers are stupid: they're just working in what they perceive to be their own best interests.


In the general case it's impossible to objectively evaluate the merit of knowledge workers because so much of what they do can't be quantified. But a good manager can make reasonably accurate subjective rankings.


It is often the case, and very unfortunate.

Also besides a 'written job description' -- there are always unspoken 'tokens' for candidate's gender or, even, race, perhaps other attributes.

Studies on this type of subject are a taboo these days.

Promotions to different organizational levels in larger corps (with 20k employees or more, I would say) -- is like breaking through glass ceiling. You can see the other side, you can do the job on the other side -- but you cannot get through there...

Scott Adams, Dilbert author, had a personal experience about a promotion he was sharing. [1]

To me, it resonated, because it was closely matching my own at some point in my career.

[1] https://youtu.be/ddBRiUsL_5I?t=2041


Occam's razor suggests incompetent management.


Or, it could be, the above suggests confirmation bias (which, in turn, results in selective justice).


As a machine learning freelancer, I can definitely understand the main argument of this article. When I started applying for contracts I always felt overwhelmed by the competition with math PhDs and other developers with brighter pedigrees. After closing my eyes to the competition, I started offering high quality communication, clear project specifications and complete honesty in terms of project feasibility, just as I would for any regular software project. After over 30 successful projects, I can't say I developed an Ai that can beat Starcraft, but I definitely brought a lot of value to all my clients. If you are passionate about machine learning and really like the grind, just go for it. Work finds a way


I'm one of those PhD types, and I would prefer to work with someone that has your skillset over someone who promises the moon and is solely excited about methodology. Based on your focus, I expect the projects you propose will have a measurable impact to the bottom line. And that is what builds reputation.


Hi!

Would you mind characterizing briefly, or giving examples of, the successful projects you've taken on as a freelancer?

I've thought before about trying to go that road, but the fact is, for almost every ml project opportunity I've come across, I would have had to say, "well, I can try out some stuff, and it might prove extremely valuable, but just as likely as not my POC will not perform well enough to use in production".


Not only is this the right attitude of what I'd want if I sought your services as a client, but this is heartening to hear as someone who's been thinking about getting more into this. Good on you!


This is a repetition of “tech is a meritocracy” that ignores all of the previous reasons that demonstrate why it isn’t.

There’s the nepotism portion (you need to get an interview first, before demonstrating merit, and nepotism bypasses a lot of that, and has the “they’re really good, just haven’t done much publicly/real world yet” backing).

Ignores that merit itself is not objective - just doing X doesn’t give an objective measure for how much merit X should get, and there’s a long history of evidence for non-merit/skill based bias in how much merit is “earned”.

Etc, etc


"Like the field of software development, the application of machine learning is a meritocracy. A meritocracy is a structure under which participants are valued based on their contributions or demonstrated achievement (merit)."

So far we've figured out that software development clearly isn't a meritocracy.


I think people aren't super clear on what they expect from meritocracy, this leads to statements like yours.

Speaking personally, I grew up in an incredibly deprived part of my nation, I have little in the way of formal education and I definitely do not have connections. However I have achieved incredible social mobility due to technology. Why? because there is _some_ level of meritocracy going on even if it's not entirely widespread through every single hiring manager or company and I have a deep unyielding passion for this field that drives me to continually educate myself which despite my poor connections and education is looked at favourably.

I still think of meritocracy as a noble goal, and I feel that merit is certainly definable if that's the main issue (IE; points based on time spent contributing to open source and things like invitations to speaking engagements and the like).

I genuinely do not buy the argument that having "merit" in other areas infers that you have license to be a toxic asshole; because at (least in my mind) part of merit is being able to work with others. You don't have "merit" if you can't communicate effectively.

In fact, there is an old saying about that: "Lots of MIPS but no I/O" which would make for a shitty CPU. Why would it make for a non-shitty developer?


I think meritocracy is the wrong phrasing for all of that though. Basically it boils down to there being slightly different standards around formal education than might be expected in some other career paths. I also think a lot of that is a perceived difference in standards and I've not seen any actual evidence that software engineering as a career field is genuinely more accessible to people without formal qualifications. Even though I believe that to be the case as well.

There of course are still standards and lots of disagreement on whether they are merit based (e.g. whiteboarding interviews) and evidence that women and other minorities are systematically excluded in the whole, which is clearly not merit based.

Further whilst I think many of us could define what merit means for any particular job or find consensus in a group making that decision. I still expect there would be large differences between definitions and methods of selection.


As someone who was never considered prestigious enough for my first field (finance) who switched and has been successful in big tech, I can vouch it is way better than fields like finance and law


"More meritocratic than finance and law" is not exactly a high bar to clear.


Maybe not, nontheless it does, and I'm thankful for that.


Compared to a lot of other fields, software development is such a screaming meritocracy, we're practically living in a real life utopia. Where else can you literally write your own ticket to a 200k+ salary without so much as a high school diploma?--IF you have the skills, that is. Compare medicine: you could walk on water and raise the dead, but good luck getting a position without certification!


I think the author is trying to lend support to people who feel excluded from the field due to a lack of credentials - great! You can, in fact, materially contribute and succeed without a PhD. Machine learning is a pretty big tent.

Claiming that a profession is meritocratic, though, strikes me as a harmful framing. From my vantage I don't see a) what an objective notion of merit would be and b) that all people who have the capability to contribute is strictly equal to the number of good jobs that are currently available.

I can definitely see when someone is already doing something useful well, but not if they might do that later or if the notion of useful will change.


Merit is relative. For example, it shows a lot of merit that you successfully completed a PhD program in machine learning. However, for some reason, there seems to be this constant need to discount people with academic qualifications when most of what machine learning is comes directly from there. For example, just because you write cool, useful applications in machine learning, doesn't mean you are breaking ground in the field. It means you are using other peoples knowledge effectively and there's absolutely nothing wrong with that and his highly necessary. But don't confuse it with making contributions to the theory itself.


Great point. If someone without credentials were truly doing ground-breaking stuff in the field, then getting a PhD should practically be a formality--schools should be banging the door down trying to recruit that person just for the status of having him or her (with full tuition waiver plus generous stipend being the bare starting ground).


I think what he meant by meritocracy is that the merits from doing projects hands on and having solid results, as opposed to the “scholastic” meritocracy which I had initially assumed he meant (and which may be confusing other readers too).


normal people call this an "empirical discipline"


Exactly


meritocracy is a structure under which participants are valued based on their contributions or demonstrated achievement (merit).

Of course what is considered meritorious or an achievement is almost entirely dependent on the stakeholders in power above you and rarely has any purely objective measure, and any objective measures are almost always project dependent, making it all a highly political game to figure out what's important to whatever system is judging you.


I would add that even some of the academic papers focus on the applied perspective of machine learning. Such examples can be found in papers issued by security research institutes/companies. And now that we have cloud computing to replicate/validate or even extend those research papers is really just the matter of determination even if the subject of the paper needs a whole cluster of distributed resources.


Says someone with a PhD. The advice in the text of just going into the field of ML blazing, is just weird. Every field is difficult, and you always have to see the light at the end of the tunnel. Personally I like to get the basics first, so yeah, I would read that required math first.

However, this just boils down to people's preference, are you a bottom up learner, or not. Both ways have yielded success for many different people. So what is the text actually saying?


Almost nobody will talk to you about ML positions unless you have at least MS in ML or have a large portfolio of recent SOTA implementations under your hood. More often a PhD in ML is a requirement for entry-level ML jobs with ridiculously low salaries (seeking enthusiastic doctorate holders etc.). Meritocracy is an illusion unless you do your own company and start competing in hottest areas - there your exit might be ridiculously big.


The author clearly abides by the old adage, “Tell them what you are going to tell them, tell them, then tell them what you told them.”


It's like a hamburger you see.


No it isn't. Applied machine learning is an arms race of who has the data.


There's a more interesting research race to figure out how to learn well with less data.


Is there, though? Sure it would be great, but this feels more like the modern day alchemy.


Yes there is an active literature on this. The extreme is called ‘one-shot learning’, which means what you’d guess.

I know it is a thing. My question is if there is actual money/progress being made there. Hence my comparing it to alchemy. A widespread practice that generally did not produce any results in what they were attempting.

My question is if people are so good at math why are they doing machine learning, especially in practice?

Some very good people investigating it theoretically. But the best young math professors that I’m personally friends with actually do have something of the “elitist math attitude” and will tell me things like they think the ML field belongs in the 1600s while they successfully work in their obscure area of algebra applied to mathematical physics or something


I thought meritocracy was a discredited concept.


I’m always confused by this. Isn’t merit exactly what we want to be hiring for? I don’t understand why you wouldn’t want people who are the best at getting the job done. Or in opensource, I don’t understand why you would want to care about any attribute of a contributor other than the quality of their contributions. Anything else seems like discrimination.

And I acknowledge that we often don’t do a good job of this; but surely that doesn’t mean we want to move away from merit based decisions.


My reading of the parent comment is that it is acknowledging that few decisions are purely merit based. People making hiring decisions have incomplete information and often rely on nebulous impressions and feelings of the candidate. People also tend to like and feel more comfortable with other people who "get" them, and have similar backgrounds/characteristics. I do not think the comment is advocating against hiring the best nor advocating for making less merit based decisions.


Yeah; I guess there are two questions:

1. How meritocratic are the decisions we make today?

2. Do we want more meritocracy, or less?

I think there's specific ways we fail to make meritocratic decisions (credentialism, "culture fit", big company politics). But in my experience these things are the exception, not the rule. We don't start by trying to figure out if someone is a good culture fit, then assess their technical skills afterwards. We assess technical skills, then if we like what we see we check culture fit.

I don't know about the GGP post, but I've certainly talked to people who claim to reject (2) - saying that the whole idea of meritocracy is flawed. But I'm always confused by that argument. Would you accept a rubbish pull request in a personal project? Would you hire someone with no technical skills into a technical role in your company? If the answer is no, then you're on team meritocracy-is-good.


> 1. How meritocratic are the decisions we make today?

"Not very" based on my experiences.

> 2. Do we want more meritocracy, or less?

Ideally you want more meritocracy -but- that relies on a level playing field which is much, much, much harder to implement and would involve people paying taxes, etc.

> Would you accept a rubbish pull request in a personal project?

Honestly, I might, if it was something I was never going to get around to and it scratched >50% of an itch. Or if I could see it had potential for later work. Or if it was from someone I wanted to have contact with.

> Would you hire someone with no technical skills into a technical role in your company?

If you add "relevant" after "no", you'd be surprised how often this happens.


You might find this interesting from the author that coined the term meritocracy. In particular addressing point 2.

https://www.theguardian.com/politics/2001/jun/29/comment

"It is good sense to appoint individual people to jobs on their merit. It is the opposite when those who are judged to have merit of a particular kind harden into a new social class without room in it for others."

I think you can see inklings of this in support for Trump, Brexit and distrust of elites the term for the new 'meritorious' social class.

Further merit in a job should extend well beyond technical skills.


Wow, ok, so it looks like there's a 3rd thing we're discussing: Does meritocracy mean "status based on qualifications" or does meritocracy mean "status based on relevant ability".

Reading that article it looks like the term 'meritocracy' was coined to refer to the former, but we didn't have a word for the latter and so the word has been co-opted and muddied. "Meritocracy is a discredited concept" could thus mean any combination of these statements:

1. We don't / can't currently hire based on collage degrees

2. We don't / can't currently hire based on relevant ability

3. We shouldn't try to hire based on collage degrees

4. We shouldn't try to hire based on relevant ability

People in this extended comment thread seem to be arguing assuming that these stances are interchangeable, or arguing assuming that there is consensus about which of these points we're arguing and they know what it is.

Personally, I believe that we should try our best to hire based on relevant ability. Because I want the most qualified people as coworkers and creators of the products and services I consume. I welcome debate of the idea, but arguing about meanings badly is pointless.

Slatestarcodex wrote a great piece about this whole thing a few years ago. I highly recommend having a read: https://slatestarcodex.com/2017/07/24/targeting-meritocracy/

> The intuition behind meritocracy is this: if your life depends on a difficult surgery, would you prefer the hospital hire a surgeon who aced medical school, or a surgeon who had to complete remedial training to barely scrape by with a C-? If you prefer the former, you’re a meritocrat with respect to surgeons. Generalize a little, and you have the argument for being a meritocrat everywhere else.


It's muddied because we have to define merit.

Take for example your quote from Slatestarcodex. That's purely about qualifications. Surgeon A might be an alcoholic and Surgeon B might have an incredible success rate. Are their qualifications relevant then?

Anyway the point of the article and book isn't about merit as just qualifications but about the detrimental impact of rewarding only merit on the stratification of society. Changing the criteria for merit just alters the stratification.


I looked in to the criticism a few months ago. From what I could gather there are a few people who feel that previously mistreated people should now be given an advantage to make up for the past. There is also another group of people who don't disagree with trying to rate people on merit but disagree with the people who say we currently do that because the reality is everyone is biased and if you don't do well its probably not entirely that you lacked the merit.


You can get your job done well but still be toxic and cause harm in other ways.


Meritocracy has been coined by the mediocres so as to have something to drape intp when they need to justify their (lack of) work.

Often, things are named by those that do them the greatest injustices.


From what I've seen a mediocre who feels the need to drape oneself would never speak such a word. They'd find other justifications for not getting that job or promotion.


I understand why you would say that, but it's not an entirely discredited concept; except among a few people who seem to prefer identity politics.

I don't mean that to be inflammatory at all by the way; but there are people in the world who believe the circumstances of their place in society plays a significant role in how you should weigh them and their contributions.

So, I wouldn't jump to "discredited" just because there's one blog post from a surprisingly influential person. I would instead say "contested".


If you don't "mean to be inflammatory", then why do you open with an inflammatory statement, and then continue with intentionally inflammatory misrepresentations? It's clear that you do mean to be inflammatory.


I don't mean this question to be inflammatory, but what was inflammatory about his statement? Was it the term "identity politics?"


> misrepresentations

"Affirmative action" is the PC term for what he described, and is pretty broadly accepted...


Yikes - just mentioning that there are people with differing opinions is considered "inflammatory"?


You can't discredit it universally, that'd be like disproving God.

More exactly, it is the psychological trait "Belief in a Just World" (BJW.)

One doesn't have to look far in our actual civilization to see innocent victims, injustice, but that still doesn't penetrate the existential strata of the universe eventually righting all wrongs.

Here's a good analysis of the psychological studies: https://www.youtube.com/watch?v=aQ0lR23T7FA

If you don't have time to watch the video, the most significant points are:

1) Believing in a Just World / Meritocracy, is an evolved emotional buffer to the chaos and reality of ever-present injustice.

2) BJW trait correlates with higher measures of happyness after traumatic events like natural disasters - and seems to be a trait that remains relatively static among persons regardless of the tradgedies they suffer or windfall they receive.


Well, if it's Open Source / free software, as the ML research field is, then it is a meritocracy.


Have seen jobs where PhD is "required". (Many data scientists tend to push this view as they feel it protects them and gives them elevated status).

Am also in the middle of training a group of future data scientists. The company is having issues hiring, and believe it is easier to train SME's in data science than the reverse.


Mmkay. It's an applause light. What are we even suppose to think/say?

https://www.greaterwrong.com/posts/dLbkrPu5STNCBLRjr/applaus...


Access to datasets makes machine learning not a meritocracy. Saw a recent talk at an insuretech conference where the speaker lamented that China will leap ahead in AI research since they gather more data about users than anyone else. From that perspective, things like GDPR hinder EU researchers.


Meritocracy all the things!


In this post I learned...




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