rm999

There's something big about hiring that I never realized until I started doing it: most hiring managers never get trained in hiring and don't put much thought into it. Job descriptions often go through several layers, with a line manager, a director/VP/CTO, and HR all making modifications. By the end it's often a franken-document that doesn't reflect what any one person is looking for.

My advice is to understand what the company actually uses and values when deciding if it's a good fit. For example, let's say you're a Java programmer who sees an awesome job description that asks for both Java + Scala, but you know the team/company primarily uses Java. What you can do is spend a few hours studying up on Scala and playing around with it. Then, on your resume, put down "proficient in Java, some experience with Scala". That last part gets you past the HR screen. If you're asked about Scala you can say something like "oh yeah I've been playing around with it, I'm really looking forward to getting more into it!" You'll get grilled on Java and get a free pass on Scala. Also, very important: it's not a lie (please don't lie on your resume, it's the easiest way to get rejected when you're actually a good fit).

You may already know this part, but for anyone who doesn't know: vector space models very often use cosine distance to make comparisons, instead of Euclidean distance. In this model, you can visualize your vectors as points on a unit hypersphere, where the distance between two vectors is how far apart they are on the sphere. x+y finds the point between them, x-y finds the point between x and the antipode of y (or, perhaps more intuitively, pushes x away from y). 2*x doesn't have any additional meaning (it's the same as x). But x+2y is the equivalent of finding a point that is proportionally closer to y than x (I think this is 2 times as close to y than x, but I didn't do the math). edit: to be clear this paragraph is very hand-wavy on the math, and is just meant to create an accurate-enough visual.

My intuition of why things like king + man - woman work is because the points in the vector space model happen to create a well-behaving manifold with smooth meaning changes. It's not very principled, but it does work.

I wrote a series of blog posts with a coworker about doing this with music:

https://tech.iheart.com/mapping-the-world-of-music-using-mac...

https://tech.iheart.com/mapping-the-world-of-music-using-mac...

Instead of mixing nouns and adjectives, we do things like mixing songs and artists and radio stations etc. In the second post we show how Nirvana - Kurt Cobain + Female Vocalist works remarkably well. I've studied empirically why this worked, and the best I could come up with is that the high dimensional space we created had a very dense set of points in the region of popular western music that led to a smooth manifold.

What does introvert even mean? I've heard shy people who are energized by talking to others described as introverts, and I've heard outgoing people who have to be alone to energize described as introverts. These descriptions are the opposite, but they're given the same label. Then you have articles like this one, where some of the bullet points make sense for both types of people I describe, some make sense for only one, and some make sense for neither. Online discussions about introversion are usually just as confusing.

Then at some point the term "ambivert" became popularized, with claims the majority of people fall into a vague middle category (http://www.today.com/health/winning-personality-advantages-b...). But this doesn't really clarify anything to me, from what I can tell it just adds another label onto a spectrum that isn't well-defined.

I'd love clarification on this, especially if anyone has a good authoritative source on it.

I've purchased generic red plastic cups before, and the experience was terrible. They were hard to pull apart, weren't stable laterally (i.e. the force when you grip it with your hand), and sagged after an hour of being full of liquid. The experience made me appreciate how well designed solo cups are, especially for how simple they look.

I added it to my short list of items I never buy generic (paper towels, paint, and car tires).

Have you seen murfie.com? They have reasonable prices and will "sell" you a physical CD but just digitally deliver you the FLAC. Of course the fact that they even have to do it this way is so anachronistic. Audiophile quality digital audio is one of the places where piracy - specifically a few invite-only music torrent sites - have completely surpassed (and arguably innovated beyond) anything legal.

Speaking for NYC, but I imagine silicon valley is similar.

The supply-demand dynamics have changed a lot in the last couple years. I'd roughly break it out into two groups: people with work experience + strong software development skills, and those without. The first group is in higher demand than ever, and tend to add a lot of value to companies that really need it.

The second group has gotten extremely crowded, especially from STEM graduates - usually with a masters or phd - who have completed MOOCs or bootcamps. Supply keeps growing while demand is flat or shrinking (especially as executives get burned by "data scientists" who don't know how to help them build things of value). There's a huge crunch here; a lot of people I know in this group have been searching for jobs for months, eventually settling for a low quality job or giving up entirely :(

Right now 100% of the comments in here are about "predicting" the election, when the word "predict" isn't even used in the article. Probably an over-eager editor who changed the title.

The article itself is about a very interesting network analysis of establishment vs non-establishment behavior. I'd like to see more discussion about the content of the article.

edit: downvoted within 1 minute for trying to spur interesting discussion past the crappy headline :(

This is about game AIs, which are definitely interesting. But for the most part they overlap very little with what most people think of as AI.

In undergrad (mid 2000s) I partially specialized in both computer graphics and machine learning, and took a video game class to try combining these skills. I have two big memories from this time that stuck with me. The first is the time a dev on Civilization 1 visited our class. He spoke about the "AI" of civilization, which he revealed to be a simple random number generator. He told us people often thought it was far more complex, but that's really all there was to it.

The second memory is when we actually built a 3d engine + game from scratch. Every week we had to add a new feature, so one week I obviously took on the AI. My partner and I were doing a soccer-style game, and I had grand visions of implementing a sophisticated AI using what I'd been learning in my other classes, like SVMs and neural networks. I started doing research, and was shocked to learn that no video games at the time did any of this. I learned that computers at the time weren't really capable of running several versions of an ML algorithm simultaneously (one per agent) while dealing with everything else - and more importantly that there was little need. I ended up spending a couple days building out a basic state machine, and it worked. Even the professor thought we added incredible intelligence to the players, who in reality were just following ~10 rules like "if player in defense mode: move towards the midpoint between the ball and the goal while keeping some distance between other players".

My main take-away from that class is that there was little need for actual AI in video games, and that I should pursue a different career path :/

> The equivalent in any other platform is awful.

I think that's absurd. When personalization is done right you probably just don't notice it. For example, Google search makes fairly heavy use of personalization (in a great way IMO), but most people don't even remember it being added ~5-10 years ago. But, if you took it away, I think it would be starkly obvious to a lot of people.

That usually comes down to product and business decisions, not the algorithms. Facebook (like Pandora and many others) falls into the same trap of optimizing too much on top of their algorithms. Instead, some gentle prodding in an interesting direction is usually enough to prevent a bubble while guiding exploration.

I'd argue that without some guided exploration it's much easier to fall into your self-made bubble. For example unfriending people on facebook, or listening to the same 5 artists on Pandora.

It could be as simple as "Hey, we noticed you spend a lot of time on r/gaming and r/frugal - might we suggest r/gameDeals?". Or perhaps even just filling some of the front page with threads from subreddits that may interest the user.

I think there'd be a lot of interesting discovery available to reasonably active users of reddit. (I've spent a significant % of my career on personalized recommendations, and in my opinion reddit's product is close to ideal in many regards).

It's pretty clear to me that Reddit has always lacked a solid experienced science-driven data person. Someone who can pinpoint an issue, formulate the issue into a product-driven concrete problem, come up with hypotheses on how to fix the problem, then use their vast wealth of data and users to test and/or implement them.

It's not just the ad hoc unintuitive "solution" they came up with to mask votes (which most people agreed was a user-antagonist step in the wrong direction). It's a lot of things: their inept response to spam/vote brigading/other abuse; their lack of personalized content discovery (state of the art from 10-15 years ago would probably suffice). I could go on, as a product-driven data scientist who has been on reddit since the early days, I'm constantly struck by how little they do with the amazing data they have.

>Wow Stack Overflow has 300 employees!! So at a typical benchmark of $500,000 of revenue per employee they should be making atleast $15,000,000 per year in revenue.

Isn't that 150 million a year in revenue? If so, 500M is about right assuming a 3x revenue valuation.

From http://blog.bonus.ly/a-look-at-googles-peer-to-peer-bonus-sy...:

> A typical example would be one employee giving $175 to a peer that “coded an SQL query for me and saved me a lot of time.” ... the sums involved might be considered “insulting”.

I was born in Baltimore, lived there for several years, went to college there, and visit it several times a year. I still consider it my home and have an intense amount of love for it. So "no meaningful experience with the city" does not apply here.

Baltimore has serious crippling problems and denying that does the city no favors. Outside of very small pockets of often-non-organic gentrification (usually driven by the city or Hopkins), the city is at a nadir. Baltimore is the smallest it's been since WWI (for a few years now, to a rounding error), and the per-capita homicide rate is the highest it's ever been. Two awesome, solid people I know were murdered the last year I lived in Baltimore - in "safe" neighborhoods in unrelated incidents totally beyond their control. The fact that the homicide rate is now 30% higher is terrifying.

Normally, proximity to a bigger city like DC should be a good thing - you can get a nicer place for cheap and use public transportation (MARC train) to commute. But something has prevented Baltimore from growing and gentrifying.

I think the biggest problem, the obvious one, is crime. There are some small pockets of intense gentrification, and even these areas aren't particularly safe. The rest of the city is a no-man's land. Literally within a few blocks of crowded, active areas (e.g. Fells Point) there are extremely unsafe blocks where the chances of a mugging (or worse) are unreasonably high. Then, there are huge contiguous swaths of the city where no one but residents are really advised to enter. I remember going out to a bar in West Baltimore and not a single cab was willing to drive into the neighborhood to pick us up. The patrons of the bar refused to let us walk home ("you're gonna get stabbed!"), and a kind stranger drove us home.

Most people I know who live in Baltimore want out, and many either move to DC or to the suburbs.

>I think the guideline exists because even as an honest question it does not add anything to the comment

I hope you see the irony here considering how much you're derailing this conversation (I'm only responding because I realize your intentions are good). And I'm pretty confident my comment added plenty of value to the discussion - I realize sometimes tone is lost in text, but after my clarification I don't see why you need to harp on this. Anyway, original comment edited.

It was an honest question, not snark (passive aggressiveness is not my style).

The introduction is kind of hidden on the page, and clarifies the meaning of "model" in this context. Otherwise, GP is correct that "model" is often used to mean a supervised model, and that people generally call it "supervised learning", not "model-based learning".

The introduction clarifies what the authors mean. In this context "model" isn't about implementing a supervised model, it's about "modeling" your problem to build a bespoke algorithm that closely matches the problem. Unsupervised methods like clustering would probably fit in here too.

I haven't read much of this early access book yet, but I'd give the authors a lot of benefit of the doubt. Christopher Bishop wrote one of my favorite machine learning books (I read it after my graduate study in machine learning and it filled in a lott of the gaps): https://www.amazon.com/Pattern-Recognition-Learning-Informat...

It's not a bug I'm concerned about, it's this part of the privacy policy "if you permit the Uber app to access location services through the permission system used by your mobile operating system (“platform”), we may also collect the precise location of your device when the app is running in the foreground or background"

What I'm getting at is that it's pretty straightforward and easy for Uber to maintain a database of every user's locations at all times, even if they aren't active users. This kind of data is valuable. Assuming Uber isn't already doing it, all it takes is one mid-level product manager to initiate a small project to kickstart it.

> Uber's infrastructure is completely incapable of handling that volume of data,

The data volume isn't very big. Let's assume Uber records locations for 20 million users and pings each user every 5 minutes. We're talking about 20 million users * 12 events per hour * 24 hours * 16 bytes (my generous assumption of how much it would cost to store a user id, timestamp, and precise long/lat data) = ~100 GB a day or 3 TB a month. And 20 million / (5 * 60) = 67k events per second.

I could probably build out the infrastructure to process and store a year's worth of user location data for 20k a year on AWS.

I'm thinking 20-50 years from now as the developing world develops and embraces globalization on its own. In the next couple decades we're likely going to see some bad (or at least chaotic) times :(

I see this as part of the waning influence of the USA as a world hegemon. The USA and its allies, as a matter of foreign strategy, have propped up secular "democracies" since WWII. This has led to world-wide stability and peace (especially post-cold war, when its sphere of influence expanded into Soviet territory). But, this often involved supporting unpopular and/or autocratic leaders who would maintain a democracy as long as they could overthrow unsuitable leaders (often with covert American help).

I think there have been multiple backlashes to this in recent times. The socialist revolutions of central and south america, the arab spring, the rise of Putin's influence in the ex-soviet sphere of influence, and now the rise of nationalist anti-globalization leaders like Trump. A lot of people world-wide are deciding that America's place in world affairs is no longer tenable or desirable.

I'm totally mixed on this and consider myself fairly neutral. I appreciate the relative peace and stability that we've had, but I also think it's been untenable. A better world will likely come, eventually, from more distributed decision making that doesn't involve just a small % of the world's population.

I'm not a fan of Trump or the way this election played out (or even facebook, really), but this article is absurd.

>Because Facebook has multiple figures in leadership positions that supported Trump. Thiel vocally, Luckey surreptitiously.

Thiel isn't in a leadership position at facebook (de facto or de jure - he's a board member who doesn't take a day-to-day role) and Luckey is about as marginalized as you can be within a company while maintaining contractual agreements. The real leadership of facebook seems genuinely progressive. Also, I'm not sure some employees supporting a mainstream politician is grounds for the company to be shaken up or disbanded (49% of voters supported Trump!).

>Because Zuckerberg believes the fake news his platform elevates played no part in the election ... Because Facebook’s core product promotes the distribution of false information

Nate Silver largely agrees: https://twitter.com/NateSilver538/status/802272157954781185. And sure maybe it had some impact, but so did 50 other things going on. I'm not going to defend fake news and I think it's harmful to the election process and facebook, but this isn't a strong argument against facebook as a company.

>Because Facebook shipped a racist feature in its core advertising product.

A huge amount of advertising is targeted racially in a non-controversial way. This is a reality of advertising and I don't consider it racist. Facebook has made it clear it does not tolerate the illegal or discriminatory use of this feature.

There's a huge difference in economics. A house will be used, so looser tolerances in carpentry are not obviously good and are seen by many as a bad trend. Sure, you may not die from those lower tolerances, but you'll likely regret it. See for example http://www.mcmansionhell.com/post/150597521816/mcmansions-10...

The median house will be used for decades, the median software is used for months (maybe days, or even minutes). This is really what my point is.

The author makes some great points that I initially wanted to dismiss, but I think are actually really interesting. Unlike many other types of engineering/craft, most experienced software developers have settled on an aversion to perfectionism. A good carpenter wants to build a solid house even if no one will ever see its frame. Ditto to an auto engineer at BMW, or a hardware engineer at Apple, or a mechanical engineer at Boeing.

Why do software engineers break this mold? I think it's because building software is inherently cheap, which means it's easy for a large number of people to build things without an obvious economic incentive, which means there's often a product misalignment. When someone builds a house or a car, they are certain their product will get used. Most software, on the other hand, never sees heavy use. Probably 90% of what I've built over my career has never been used, and I've had a productive career.

The most rational thing in software is to ship something functional, then perfect it after it's been proven to be useful and popular. I can see why someone with a craftsman's mind would hate this. I feel a sort of disgust with myself when I ship shitty code, but ultimately I know it's what makes me so productive and valuable to my employers. This disconnect is real, and it's worth talking about.

You're right that the fact that US factories weren't being bombed was critical, but it's important not to underestimate the scale here. The USA was a world powerhouse before wwii, with a higher gdp than all axis countries combined. Switching to a high-throughput wartime manufacturing powerhouse was straightforward.

>I would. 60+ million people voting for a man as odious and unprepared as Donald Trump says a whole lot to me.

Let me rephrase: you are extrapolating the wrong thing when you say the "liberals drastically overplayed their hand" and then use this election as evidence.

Obama almost certainly would have annihilated Trump (his support in rural swing states is much stronger than Hillary's), and he's more liberal than Hillary. For all we know, Bernie could have done decently. Hillary's downfall is that she's seen as an out-of-touch corrupt establishment politician, which Trump (and Obama) were not.

> Micro-aggression, safe spaces, trigger words

I think you're missing some perspective on this; a small % of activists on the left (mostly on college campuses) do not represent the trends of liberals in the USA. I can't think of a mainstream Democrat who considers these serious causes (including liberal ones like Bernie Sanders or Elizabeth Warren).

The reality is the left has been making huge inroads on social causes in the last eight years - in fact, this may be the primary enduring legacy of the Obama years. The public perception of gay marriage, police violence against blacks, and marijuana use have all drastically shifted and led to very real changes that won't be undone. I wouldn't call this overplaying their hands.

Also, I wouldn't extrapolate much from this election. Obama is a fair bit more liberal than Hillary and is extremely popular compared to her.

I feel the opposite. I bought a Roomba 650 almost exactly four years ago (one of the best purchases I've ever made) for about 350 dollars after a bed bath and beyond coupon. With a little bit of maintenance it still runs every day exactly as well as it did the day I bought it.

The 650 is the robovacuum Sweethome recommends and has recommended for years (http://thesweethome.com/reviews/best-robot-vacuum). The newest Roombas since then have been mildly incremental, and the competitors have struggled to offer something that works better. One of my close friends bought the exact same model last week for 370 dollars.

That's not to say there isn't room for a lot of improvement, but I think it's been a super slow moving space.