We can't know whether fake news tilted the election towards Trump. There is no experiment or analysis that can conclusively dis/prove that hypothesis. NYT and others should be humble here. Sure, fake news is stupid, but so is claiming that it "helped elect Trump"
Cash, money-laundering, sketchy real estate transactions (Benami- transactions under fake names), informal banking (hawala), the same as in most places in the world. Think early mafiosi in the US. The most significant legislative actions for curbing these are: Benami and Hawala legislations, computerization of land records in the late 90s and early 2000s, PAN numbers in the 90s and Aadhar in the last few years (a bit like SSN in the US), and the OP.
Uh when will the H1B=lower-wage meme just die? A lot of the H1B hiring is purely skills based. In my nook, all of it is skills-based. I am yet to encounter a hiring manager who'd hire shit employees on H1B just so that he can save money by paying them lower wages. Especially startups. I'd love to find out who those founders and managers are who'd hire less-than-optimal people solely so they can pay them less. Looking to short those companies, lol.
I suffered very unpleasant nausea after eating bars from a particular shipment of Soylent food bars. Soylent is now forever (or at least in the near future) associated for me with those bouts of nausea. That's the unfortunate thing about nausea, one episode related to a particular food can ruin that food forever for you.
There's no correct answer to this. But, from personal experience, there are companies and roles in which too many sick days and even maternity leave can shaft your promotion. They usually give fuzzy reasons like "you weren't fully present," etc. and won't necessarily directly say "you took too many sick days to care for your kid!" There is an implicit assumption that at certain early-career roles you are childless and managers and peers at such levels are quite poor at accommodating working parents.
I think it is because of a few interrelated things:
1. Ill-posedness of the problems: what is sleep?, why do animals sleep?, etc. vs. the well-posed physics problems such as, what happened at the beginning of the universe?
2. Data sufficiency: there is too much variability across people and animals to have enough representative data marginalized on each variable for many biological systems in general, and sleep in particular
3. Complexity of the system: cosmological systems and even subatomic particles are less complex models than biological systems
On incentives for researchers, there is also the maxim that there are many unsolved and interesting problems to work on, but scientific judgement is in knowing which are solvable. Of course, the occasional maverick goes after the hardest, most ill-posed, most unsolvable problem. But the existence of such mavericks is not guaranteed for every problem, sleep biology included.
This is a sign of the utter commodification of hardware and the possibility that a majority of innovation in the future (with the exception of low-power wearables) lies in the realm of software and algorithms.
Not to mention that a lot of the material minimalism goes out of the window once you have kids. Like any ideology, foisting it upon children may or may not be a good thing. I've seen that kids thrive when they are surrounded by a dump of blocks, books, toys, etc. which they can explore by themselves.
Just mull the power and influence of deep learning: Yann LeCun is in FB, Geoffrey Hinton and part of his lab are affiliated with Google, Ruslan Salakhutdinov is now with Apple. In addition to this, there are other alumni of LeCun, Hinton, and Bengio dispersed across different notable companies like OpenAI, etc. Aside from the post-WW2 semiconductors-spurt, I can't think of a 'technology' that has become so suddenly so important as deep learning. You have a few scientists who spawned the fields of neural networks and deep learning in charge of what appear to be significant research efforts at the top tech companies (by market cap). Like silicon semiconductors and integrated circuits, deep learning approaches are likely to be the primary set of algorithms underlying many future 'intelligent' products and services. You will likely see a similar thing in biology/biotechnology with CRISPR in the near future.
Blue sky research should be open. Last mile product development and products themselves can be closed source. Else, how do you create profits and value for shareholders? So far, except Apple, the others have made the outputs of their research labs open: published papers, demos, packages like TensorFlow, etc. Besides, there is a division of labor: govt, with its altruistic mission does open blue-sky research. Companies, OTOH maximize profits and the good ones that can afford to, also do open basic research. I don't see his vision to be counter to this.
I have to disagree on this. Data scientist is a very fluid and fast changing term. I know companies who now call what would traditionally have been "machine learning researcher", "machine learning engineer", or "research scientist in <any data related stuff - data mining, computer vision, signal processing, machine learning, statistics>" as "data scientist" positions. Because it is sexy, in many places, management and job hunters get a kick out of the term "data science" even if it is actually a renaming of other traditional roles. This book perfectly captures the diverse nature of the term.
Earnest skepticism: how can you trust Open APS without the rigorous testing required from companies like Medtronic? Sure, FDA regulations are not perfect. But they sure work in a large number of cases. While the DIY spirit of Open APS is commendable, hypoglycemia can be extremely dangerous and the risk is too high without FDA-level rigorous testing.
There's nothing wrong with Omaha per se, but some of the most cutting edge technology work is truly happening in, Bay Area, Boston, Seattle, and secondarily, NYC, Dallas, Austin, DC (defense).
Given this, while Omaha, Nashville, Oklahoma City, St. Louis, may, to varying extents, be great cities with good schools cheap housing, etc. they don't necessarily have the best technology companies.
The key to this problem is really held by cities like Twin Cities, Dallas, Research Triangle NC, and Atlanta, which have great infrastructure, industrial cultures, cheap housing. It would be nice if tech companies open substantial outposts there or if new companies are founded there that become Amazon-level successful. Whether this will actually happen is another thing altogether. These cities haven't spawned super-successful tech companies in the last 30 years, but have older "tech"/industrial companies that continue to thrive.
Why should we delude ourselves that he is genuinely remorseful or that he will redeem himself for such a horrific crime? Some criminals reform, others don't. It is a mistake to assume that everyone can or will mend their ways. One consequence of the article's theme, the fact that we don't fully control our destiny (absence of free will) is that the likelihood of recidivism is high.
Uh, it's not that clear cut. Also, the line is drawn along the lines of developed vs. developing economies.
Having lived in India and had some experience with US multinational companies, the 'massive international markets' in developing countries are limited to electronics, automobiles, and computer science: a few companies like Ford, GM, Microsoft, Intel, and most significantly, Apple. In other industries, companies like Unilever, P&G, etc. setup subsidiary structures because the markets in India and China are often much smaller in $s. At the same time, in structures similar to how P&G or Ford manage their Indian or Chinese businesses, Indian and Chinese companies control US/European corporations: Jaguar Land Rover, Volvo, Starwood Hotels, AMC Theaters, etc.
Yes, but if you flood it with white noise, it'd screw up any transmit waveforms. The only alternative is to have a software radio that is flexible enough to switch bands when it encounters noise.
I think it's more of a continuum than you suppose in your comment. It's not a binary of "great" vs "average" PhD. There's plenty in between and many types of averages. Karpathy had it good, as did Might, Guo, and other purveyors of wisdom on PhD. But that doesn't invalidate their arguments and observations.
This is strange: you buy a jet-black phone so that it looks slick. Then you buy a case and change its appearance because scratches might show? Weird logic.
I totally agree! Also, there is plenty of variance and random luck in the fate of companies. Kodak went down, yes. But many other similar companies survived and thrived. GE once sold personal computers and 3M, magnetic tapes. But they successfully extricated themselves from these businesses when they became difficult to profit off of. While there are certainly deterministic reasons for this, one shouldn't discount the effect of luck. People forget how diversified these companies are. The positions they themselves hold, in terms of markets, are hedged- with short and long bets. Just because they are hedging their bets more by buying Dollar-Shave-Clubs and Jet.coms doesn't mean there's a bubble.
Additionally, on the tech/start-up side too, there were many shorter-lived companies that never lived up to the hype or declined from a position of unrivaled greatness (Cray?).
If there is a fatal error in the OP, it is in the certainty and needless cocksureness of McClure's predictions.
Given the huge sizes of these markets and the value of products and commodities, it is laughable to predict an imminent decline in companies that do pharmas, chemicals, industrials, medical devices, etc. based on metrics cherrypicked to create such a narrative (e.g. shift in highest-revenue companies).
Well, yes and no. Kingdoms and provinces weren't ever linguistically organized till 1957, 7 years after India was unified as a Republic (1950). Most kingdoms and provinces were multilingual, though they all had one or more court languages for which the respective governing elites patronized scholarship. An example is the Vijayanagara empire in southern India (1330s to 1565) which was ruled by different multilingual elites who patronized Kannada, Telugu, Sanskrit, and to a lesser extent, Tamil and Persian. There are also other types of counter-examples- dialects that were patronized by kings or leal chiefs with their own armies (e.g. Dakhani Persian/Urdu of the various Sultans and Nizams (1300s - 1900s) of the Deccan region of South/South-Central India)
"1. A language is a dialect with an army and a navy"
Tell that to the speakers of 10s of languages of India, most of which are so different from one another that no definition would classify them as dialects. I wonder if that quip, even as a humorous one, makes sense when it fails for about 20% of all humans.
Severe sampling bias. News in the West is focused on all the bad things that happen there. That doesn't mean that there can't be a small percentage of the population that has the time and motivation to educate themselves. I've met my share of Syrians, Libyans, and Iraqi graduate students who were educated in and lived through pretty difficult times pre- and post- dictator-overthrow.
Two of those are not like the other. Frankly, Portland has a pretty anemic economy and the colleges here are mediocre too. Boulder is a little better. Can't say Northeast Ohio is that bad, Cleveland is on par with Boulder and Portland.
Austin, OTOH has one of the best universities in the world and a host of large and important tech and software companies.
She may also be learning! You're discounting experiential learning aka learning on the job. Also, she may be reading books relevant to work, including domain-specific books, management books, pop-sci management books, etc. I think the spirit of the article is great, but the definition of learning is rather narrow.
I think this is relevant to HN given the widespread use of various supplements in the community. It is also interesting given popularity of Tim Ferris, Nootrobox, and other supplement enthusiasts.