Then Juul should be put next to the nicotine patches and gum in the pharmacy, and be marketed as a medication. The FDA heavily regulates substances that can be abused when not used as medication (things like meth ingredients).
Frankly, letting a company aggressively market a highly addictive compound to an impressionable segment of society because of a single-use excuse ("it can be used as medication!") is a bit disappointing. It also reads as astroturfing because it's such a limp talking point.
But this is somewhat an admission of using it as medication, which is far from what Juul is being marketed as. It should be next to the nicotine patches at the pharmacy. Can you even buy nicotine patches in bulk? Substances that can be abused for something other than their primary use as medication are heavily regulated by the FDA (think meth ingredients).
Huh. Well let's assume causality points in only one direction, genetics->tissue->ability, then I'm screwed and there's nothing I can do about it. Let's assume that it at least points partially in the other direction, ability->tissue, now I can keep my tissue healthy by exercising.
Since I don't know for sure which direction causality points, I'm going to take the path of maximal self-determinism and try to stay fit as long as possible.
This is probably heavily affected by at least two things:
1. increase in healthcare costs and how health insurance is bound to employment
2. increase in wealth concentration and a shift from cash compensation to asset compensation (Bezos is only absurdly rich if he liquidates his Amazon holding instantly)
So, I would say your portrayal of hourly compensation is disingenuous as well. All of these statistics probably need to be calculated as medians instead of means ("compensation per hour" sounds suspiciously like "total compensation / total hours", which is a mean) in order for it to come close to accurately describing the situation of the median American, because wealth concentration has skewed the mean American into something a lot more optimistic than one would think.
I agree averages can be misleading. As the joke goes when Bill Gates walks into a bar suddenly everybody's a billionaire, on average! At the same time medians can also be misleading. We have 50 people earning $10, 1 earning $100, and 50 earning $200. We swap to a system where we have 50 people earning $90, 1 earning $100, and 50 earning $300. There would have been a major shift upward with nearly everybody seeing major increases in earning, yet the median would not have shifted at all.
This [1] is the real median personal income. The data there only starts at 1974 but you once again see a 32% increase in income. Now factor in the change in hours worked. The average American works more than 100 less hours then back then. [2]. These numbers combined along with arguing that most people only saw a real increase in wages of 12% is simply not possible, nor is it possible to simply attribute all growth to the rich.
Now there is this [3]. The numbers from that paper are really what made me start digging into all of this stuff. To give the long and short of it - the poor are becoming middle class, and the middle class are becoming rich. With the net effect being a major decline in the number of poor, a major increase in the number of rich, and a small decline in the number of middle class. Probably not coincidentally, not entirely dissimilar to the hypothetical I proposed where the median can end up being misleading. These 'nobody except the rich are seeing more money' articles seem to be simply untrue, but they are click magnets.
This is a very challenging view-point, and I appreciate the effort you've put into backing it up. I think my biggest hesitation of accepting its results is the difference between annual income and wealth. By this study's standard, I'm nearly upper-middle-class, but I have a negative net-worth due to student loans. If my employment status came into question, I would be very quickly impoverished, and would have to rely on many social and governmental safety nets. Can this really be considered rich?
Maybe I'm an outlier as an individual in my mid-20s, but it's enough to make me question the definition of class on annual income.
Did you know that 72% of people with at least $1-$5 million of investable assets do not consider themselves rich> As that article mentions even multi millionaires are also constantly concerned about losing it all. Your situation does not change, at least not for many people. The numbers and reasons might, but not the general concern. Consider the ostensibly rich person with a fancy house, a beach house for holidays, a couple of luxury cars, and a couple of kids he's paying through Harvard. In reality that often translates into two mortgages, two car bills, and another $150k a year for college. It's the same scenario there. Until that wealth is 'consolidated', if his income slips up his life is going to be devastated. It's only the ultra wealthy one can start to become divorced from financial concern or even outright risk of ruin. And I think the fact that we can realistically set that as a goal ourselves now a days is probably a sign something good has been happening over the years.
Made me think: if we cut corporate taxes, raised the minimum wage, and reduced means-tested welfare, where would we end up? Same position but with less bureaucracy?
Something tells me that the welfare safety net has more societal benefits than a wage floor, but right now we don't really have a respectable form of either compared to 20 years ago.
Hmm, I was hoping for something more contemporary that I could relate to, but was disappointed that it focused on pieces written centuries ago...like most formal musical theory.
Anyway, this passage stuck out to me:
"""There is something that still rings true of Mattheson’s general idea. We do tend to associate some musical features with being uplifted and others with melancholic reflection, both of which might afford a certain subsequent pleasure to listeners. Just think of how we use music in our everyday lives: some tunes help us to work out or to get something done, while others allow us to cry."""
Composers aren't the only ones who have ever tried to manipulate the crowd. I'm not sure how pop stars/rock bands etc. plan out their sets, but one thing that any DJ[0] worth his salt pays attention to is "harmonic mixing"[1]. Taking things "darker", or trying to bring up the energy, are common strategies taken into account when planning a harmonic transition. I've personally bore witness to plenty of incredible sets that take you from the very top to the very bottom, and it's funny to me that the same ideas are masked behind hoighty-toighty music theory terminology that is used almost exclusively in reference to...music that was composed hundreds of years ago.
[0] By DJ I mean someone who does more than weddings, and certainly doesn't take requests.
> it's funny to me that the same ideas are masked behind hoighty-toighty music theory terminology that is used almost exclusively in reference to...music that was composed hundreds of years ago.
I'm just coming up to speed on music theory, but my impression so far is that it's reactive, not proactive. We already have music that we like; music theory is about trying to tear it down, identify why we like it, establish base principles that can be used to guide composition, and then use those to create something new. Fairly recently, this had led to "generative music".
I'm finding music theory to be useful to build a more accurate mental model of the instruments I'm playing, which I believe will eventually improve my ability to improvise and play by ear. I think that people who are musical prodigies have an intuitive understanding of those things, but I'm having to build my own understanding explicitly.
I've been playing bass and guitar occasionaly (as an amateur musician) since I was 15 and I'm now in my early 30s, I studied a bit of theory when I was learning and already knew how to build chords and also have a reasonable ear, last months I decided to learn how to read sheet music and study musical theory and jazz a bit more deeper, what I found is that now I'm way more confortable with my improvisation not being repetitive and over the same scales again and again and that I have a way better knack at finding the next note on songs that I haven't heard before, so my experience is similar to yours.
As an aside, I'm pretty certain that I'm suffering from frequency ilusion, I frequently find musical theory discussions at every place that I am used to read, where in the past it seems that this things were not that prevalent.
Well you're lucky I read this comment right as my morning coffee kicked in; it really depends on your taste I guess, but I'll try to be as broad as I can. Most of the sets I've heard/been at were not recorded, so syndicated radio shows from the time are the best approximate of what would have been played.
Lots of more-recent converters to the Prydz fanbase point to this set as being the "A-ha" moment of getting his music. He somehow manages to fit in a lot of different-yet-cohesive moods into 60 minutes, and the final song is a (live?) mash-up of two of his classics that is really, really clever and satisfying.
Take your pick of 2011 or 2004 depending on whether you want to tackle more-poppy, modern 128BPM or a more classic, lo-fi acid-influenced 138BPM. I think the bootleg of Massive Attack's Teardrop from 2011 is a very special track, can't really speak highly enough of it...
I included a YouTube link because the audio doesn't do the gorgeous setting justice - sunset at The Gorge, Washington State, if you can get past the interesting rave attire that Americans seem to feel compelled to wear at festivals. Fine Day is an absolute classic, very airy and day-dreamy; bonus for the recording capturing the crowd singing along.
Club instead of festival or Essential Mix. Again, ends on a very classy, satisfying track that rewards you for sticking through to the end. A bit more techy and minimal than my other choices.
Same club, one year earlier. Again, more techy and minimal. The track around 28 minutes, "Trigonometry" is a perfectly drawn out with a very intense climax, and absolutely deserves the "progressive" moniker - unfortunately it's the radio show and Sasha talks over the track hah. This is only a middle snippet of the full 4 hour set.
Something a bit poppier, but deep. Just like the Eric Prydz UMF set, a lot of Lane 8 fans point to this radio edition as being their "A-ha" moment. Very, very classy and restrained, but with some darker, more emotional moments.
If you can handle modern (post-2000) trance, then this is definitely one of _the_ sets to listen to. Really runs the full gambit of the genre as it was in 2008, starting slower and poppier, and ending with a very intense final two hours.
Hmm, electronic genres are definitely clustered around 128, 140, and 170 (+/-2), and those are all reasonable heart rates when you're partying...But a "human heart beat" can be literally anything so I'm not convinced.
Perhaps they mean the average non-stressed, slightly relaxed rate of around 100 or so? I'm not convinced either, but it is interesting to think about. Tempo and rhythm/beat has such a profound effect on the emotional response to music.
I'm on a hiring committee for a job with the title of "Machine Learning Engineer". The most qualified candidates we have come through the process are physics PhDs who did a significant amount of coding during their PhD and have been able to segue into machine learning because they were interested.
Our other tier of hireable candidates have been individuals with 4+ years of industry experience, usually with CS PhDs with a machine learning specialty.
The rest of our team came from internal transfers, people who were less qualifed but proved that they would have a positive impact on the output of the team.
I'm a physicist, and got my degree in the early 90s, but maybe I can shed some light on this.
First, physics has been computation driven since the 1940s. When I was in grad school, programming was vital to my project. I wrote mountains of code, and also designed my own electronics.
Second, I noticed a weird difference between physics and engineering. Engineering students were given problems that were expected to be solved within a particular domain of engineering. A physics student might be given a problem with no idea of how to solve it, much less even how to define the problem itself clearly. That was my project. So a physics student could find themselves having to learn practically any technical skill.
Third, a matter of motivation. We knew that we would need to make ourselves employable. My project would occasionally fail in some spectacular way that would require me to learn more programming, or more electronics. Imagine that. ;-)
Fourth, possibly also as a matter of employability, math and physics people have always figured out how to worm our way into ill-defined, nascent areas of technology. These are areas that have not yet created a mainstream training pipeline, so we can plausibly claim to be as well trained as anybody. "Embedded systems" was such a field when I was finishing school.
Adding onto this, every physics PhD I've talked to has really impressed me with how much problem-solving they tackled during their stint in academia. You really said it succinctly with "a physics student could find themselves having to learn practically any technical skill".
Running and extending numerical simulations with supercomputer clusters is just something you have to learn to do in order to solve your problem in some cases, apparently.
Their ability to code is usually sub-par, but they ask the right questions about the data, which is critical in the data setting that we work in.
We don't work in advertising / marketing / business analytics, which is very easy to have an intuition about; and we don't strictly work with images, which, again, isn't terribly difficult to have an intuition about. So a strong scientific background is actually a major plus for us.
I could see that if we were doing purely deep learning image classification or advertising prediction then the physics degrees would be less useful, but thankfully we don't.
Probably the wrong fit if the industry experience isn't right, in which case they would be on a fast-track to a senior dev role in the non machine-learning part of our company.
You're right about "research", although I'd hesitate to use the word hardcore hah. We get tons of candidates with ~2 years of slightly relevant work, but rarely do we get candidates with the exactly right relevant work. The "qualified" candidates I spoke of have ~4 years of slightly relevant work, but there are only a couple of them, and they're either out of our hiring budget or currently working for our team.
As someone who has been producing value in a data science/machine learning role for multiple years, it's disheartening to see comments that I may be blacklisted from positions due to "only" having a bachelor's degree.
Somewhat non-humbly, I was valedictorian at my high school, I triple-majored at a respectable Big 10 school, I actively use all 3 majors on a daily basis, in a foreign country, and sometimes in a language that is not my mother tongue (as an American).
I can't justify spending time and money on a master's degree (millennial wealth problems) where many courses would just be putting a formal, academic spin on ideas that I'm familiar with from a practical business-value-producing point of view.
Any advice on how I can effectively jump off the black-lists?
If your target is a data scientist role at Google, you're probably going to want more schooling.
But if you've been producing value in a DS/ML role for years, you have experience, which is even more rare than some of the qualifications people are listing here.
If you can say "I created an anomaly detection system using isolation forests that 5,000 clients relied on for detecting market changes", there will always be places that want your skillset: it is kind of a new field, after all.
So the credential bloat at entry-level shouldn't really be an issue for you.
Maybe a bit (a lot?) out there: why not go for a business degree instead, e.g. EMBA?
You mention “foreign country” so I’m guessing you can have access to good curriculums without paying the US premium on education (or just go for an online course).
Pros: the time and money is not “wasted” as you actually pick up new skills; the MBA card should be enough to trump any education requirement; and you become that most desirable of hybrids: the tech/data guy who can talk business (or vice versa).
Cons: significant time (and money) investment; doesn’t help you get expert DS jobs (you’d be aiming for team/program manager, consultant, etc)
My own experience: completed an EMBA in 2017. Ranked in FT’s top 10, the program cost was around 50 k€ (it’s increased a bit since) and I was able to get 25 k€ of outside funding. The program I followed lasts 2.5 years, meaning I was able to do it while keeping my job (and having a kid) without losing my sanity or my wife. Landed my dream job just before completing the curriculum for a nice 40% pay increase (not saying the EMBA alone had that effect, far from it —but it definitely helped).
Huh. This is actually a route I hadn't considered. Thanks for pointing it out! I will definitely consider it as I continue researching my next opportunities...
EMBAs are usually part-time over 18 to 24 months, MBAs are full time over 12 to 24 months.
So an MBA naturally has a bigger (as in more in-depth) curriculum than an EMBA. It is also a significantly higher investment in terms of time and opportunity cost, since you're not getting paid during the program.
EMBAs compensate with 1) more experienced participants (so in theory you don't need the introductory classes) and 2) a lot of pre- or post-readings (e.g. my corporate law module was 12 hours in the classroom, but you were expected to have read the 400-page book, and the numerous case studies).
But the bottom line is that you don't go into as much detail as you would during a full-time program. OTOH, since EMBAs are attended by "senior" employees (managers / VPs / directors / etc), and because they're part-time, what you learn is usually directly relevant and applicable in everyday work - and you usually get to work on real-life problems (yours or your teammates) during classes.
I'm not the best placed to say whether an EMBA is considered a "lesser" MBA. They don't really fill the same niche. An EMBA is a career booster if you're say a technical manager and want to move into business or senior management. An MBA is when you haven't started working (or are still junior) and are looking for a fast track to C-level, or to work in a specific area (e.g. consulting, finance, etc.). So basically MBA vs EMBA is mainly a function of your current experience level.
I had a dream of wanting to start a company one day and was interested in a more holistic understanding of the business side of things. I thought that it would add some credibility when speaking with business types but also uncover ideas to base the company on.
Personally, for me, I found it useful but not for the reasons of knowledge. The knowledge was good but the program helped to sharpen my speaking and thinking skills. It also broadened my mind to different perspectives - that the tech world that I come from is quite different to people outside of industry.
The classes and sessions have also made me think further and deeper about business, culture and management beyond the usual.
It also made me more disciplined - focus on the business not the product and technology. Used to waste countless hours building, researching with not much to show for.
It’s also given some confidence to speak to business types and connect with them at a deeper level while introducing technology to them.
You can most definitely fallback as an engineer but why are you thinking of an MBA in the first place? What’s your goal for pursuing one?
The reason I’m considering it is because I’m trying to envision myself in 10-20 years and thinking who I would be happy to be.
Right now, I don’t believe what would make me happy is to be a principal/staff engineer somewhere necessarily.
Don’t get me wrong, I love programming, but I see it as me getting paid to solve problems, and not getting paid to write good code, and I think there are other ways to solve those problems. For example, I think the biggest problems in my organization are managerial and organizational rather than technical, and I feel like the type of training that would come with an MBA can help one solve those issues, including communication, planning, product validation, people management, etc.
That said, my entire reporting chain up to and including the CEO doesn’t have an MBA, so it’s not like it’s a prerequisite.
The other path I’m considering is an MS in CS/SE because while I’ve been an engineer for a few years, my undergrad is in Mathematics, and I’m worried it’ll be a limiter later on to not have a CS degree, but also only a BS.
First off, kudos to you for looking ahead. It’s one of the things that’s really “scared” me into action. It’s funny because I went through the same thought process as you are going through now.
I was a decent enough software engineer and while I love to build things, I felt there was more.
Almost all company problems tend to be managerial and organisational rather than technical, which is a fascinating discussion in my MBA classes. You will definitely get the space and time to think about these things and your theories on how to solve them.
However, I will say that to solve those problems, you have everything you need today. Your knowledge, wisdom and experience can help guide you but fundamentally, these problems touch the aspect of humans behaviour. A great book is “How to win friends and influence people” - I’m recommending it not to influence anyone but it’s a good eye opener to human behaviour. The MBA will help with theories but it’s not fact of course.
I’ve also thought about an MS in CS for fears of being limited in the future as well but will respond back when I have more time. Or if you’d like we can have a chat over Skype or email.
Besides knowledge, I gained a lot of insight about myself, and also learned quite a bit about entrepreneurship (more in terms of state of mind than actual knowledge). And made a lot of connections and friends in a lot of different fields (e.g. a vet, an airline pilot, a board member in a very large corporation, a few startup founders, a tax attorney...).
Ironically, the EMBA also convinced me that I'm much happier in technical roles, and gave me the confidence to go for it. I'm currently the CTO of a startup and most of what I learned during the EMBA is of marginal usefulness to me, except the stuff about entrepreneurship. But I wouldn't be in my current job without the EMBA.
Agreed - I wouldn't be where I am today without it either.
I think the biggest misconception about an MBA is the actual textbook education but I've heard many CEO/CTOs make the same statement - helped them decide their career path and boost their confidence plus made a lot of friends across many different industries.
The UG online masters of computer science is a good option. Many people in this site speak highly of the curriculum[1]. Last time I checked the total for the entire curricula if you pass every course on the first try is around $7000. As a bachelor holder myself looking to break into some of these higher-salary and in-depth roles I’m certainly considering it. It’s even better if you have a company that will pay for it, and because it’s so cheap even the most meager offerings from companies will cover a good portion of it.
Yeah I'm definitely familiar with the Georgia Tech offering. But my impression is that it will be a $7000 + $(my_hourly_rate) * (hours_spent) certificate that will only get me past the employers who have a "Select your highest degree level" drop-down on their application form. Is it that much more respected than a collection of MOOCs?
As someone who's also involved in hiring, if I see no industry experience + GA tech online degree it's still on an entirely separate tier than 2 years of industry experience. But that's my bias I suppose, and part of the reason that I'm not the only one on the hiring committee.
Definitely biased, but here are some anecdotes/thoughts:
- I've found the rigor to be significantly more than most MOOCs, inline with other traditional grad courses I've taken.
- Some classes are hybrid, sharing the term with on-campus students.
- Not having finished the degree, my work as a data scientist has significantly benefited from the coursework. This is not to say that it wouldn't have benefited from other, non-GT coursework.
That's rather sad considering the degree isn't going to say Online and Georgia Tech is top 10 in the world in Computer Science and online or not that credential carries real weight for people in the know.
Well I'm not the one who does resume sorting, so usually if it makes it to my desk I know there's a good chance they're qualified. If you give me (personally) two resumes, one with a master's degree from almost anywhere, and one with two years of experience doing /exactly/ what we do, I'll choose the latter first. At this point, master's degrees don't carry the weight they used to in my mind based on (1) people I've interviewed (2) my coworkers and (3) my friends and acquiantances.
>Any advice on how I can effectively jump off the black-lists?
Find a decent hiring manager who has actually done some hands on Data Science/Analytics work and knows what skills/thinking are actually required. Lots of Data Science hiring managers have no or limited practical experience with doing actual Analytic work so they get overly focused on paper qualifications and buzzwords. This is reinforced by HR people who love buzzword bingo.
I created a vehicle plate recognition system before ML got cool, but I can't get any ML job with my less than bachelor degree (associate? dunno how to translate) here in Brazil. I think there are only 2 positions open for machine learning less than 100km from where I live.
>As someone who has been producing value in a data science/machine learning role for multiple years, it's disheartening to see comments that I may be blacklisted from positions due to "only" having a bachelor's degree.
Don't worry.
The big salaries will go to people who create value and solve problems. You can do that without a PhD. In fact, if most Data Science communities are representative, PhDs feel they're above 90% of the work required to put data to work to solve problems. You know, the ones who walk into a job and say, "Oh, I don't get to apply the latest algorithm onto a perfectly cleaned toy data set? I'm leaving!". They're going to have their lunch eaten.
I come from the background you describe, have lots of friends from the same background, and my experience has been the opposite. Most people know that data is messy business and that as data scientists we will often serve more as engineers in our day to day work.
Hah. I want to feel this is right. I like to think of my work as the "full-stack" equivalent of the "data science" career path. There's no part of the data pipeline I'm not currently doing/qualifed to do/interested in doing: acquisition, transformation, storage, exploration, analysis, machine learning, presentation & dashboarding, integration, server maintenance & operations...
The "toy examples" require only a very small subset of the skills required to extract business value from an amorphous blob of data.
It's quite reasonable to suppose that there are many reasons why one person would or would not mobilize to vote, and, correct me if I'm wrong, it's common knowledge that the "swing voter" effect is not due to undecided people becoming decided, rather that people are marginally motivated or unmotivated to vote.
So, in the spirit of democracy, where the desires of all those who /can/ vote (not just those who /do/ vote) are respected, it is probably interesting to examine why voters do and do not find the motivation to vote. Hypothetically, if we had mind-reading devices, and motivation was not a prerequisite for voting, which side of the vote would have benefited?
Asymmetrical motivation is the hypothesis that in referenda where Action/No-Action are the choices, there will be more voter motivation for Action rather than No-Action. This very reasonably applies to Brexit.
A swing vote just refers to a voter whose decision cannot be accurately predicted. Not voting is as much a part of democracy as voting. Even in extremely formal and small settings ranging from national congresses to the EU, abstaining from casting a vote one way or the other is very much a viable decision in and of itself.
I would argue that abstaining from voting in a formal setting is significantly different than not "voting" in modern elections. There's significant historical evidence of voter suppression, including suffragist movements. Voter motivation is not something that I think we should brush away lightly, because it has an impact on democracy just like voter manipulation and voter suppression.
Frankly, letting a company aggressively market a highly addictive compound to an impressionable segment of society because of a single-use excuse ("it can be used as medication!") is a bit disappointing. It also reads as astroturfing because it's such a limp talking point.