HN user
http://twitter.com/balajis
Hey, drop me a line: balajis at a16z dot com. We try to help entrepreneurs who have an experience like you've had get back on their feet. No promises, but often we can find you a great job at one of our portfolio companies.
Hey all. Surprised to see our little site at the top of HN :) We'll be updating the website at some point with more news. Till then, sign up for notifications and check out trybtc.com and blockscore.com.
:) I assure you that we are going to be hiring engineers through this process.
Hmm. In all fairness, the full quote is:
A BS/MS/PhD in Computer Science or the equivalent is nice
to have, but the most important requirement is significant
independent programming experience as demonstrated by your
GitHub account, personal projects, academic publications,
or startup success. Your accomplishments are much more
important than your paper credentials.We could certainly rattle off more terms :) Kernel density estimation? Deep learning? Semi-supervised learning?
But it's amazing how far you can get with some simple scatterplots, histograms and linear/logistic regressions.
a) Most of the time, more data beats better algorithms: http://anand.typepad.com/datawocky/2008/03/more-data-usual.h...
b) Even those seemingly simple things get complicated when you have a lot of data: http://komarix.org/ac/lr
Sure, go ahead! We just ask that you not share the questions with others after completing it.
It's an ongoing opportunity, but we will be hiring the first set of people soon. So it will be to your advantage to apply sooner rather than later.
Did you include the country code prefix? Otherwise please try emailing vivek at hackerrank dot com with the bug to see if he can reproduce.
Well, empirically we're getting quite a lot of people attempting it! :) Three hours is pretty lenient (you could blaze through it in less time), though the last question is challenging. We think the questions are kind of fun as well.
Without something like this we'd just have 100s-1000s of unstructured resumes in different formats to rank against each other. This process is more fair and (IMO) allows someone without a college degree, or from outside the US, to compete on a level playing field.
Great question. The short answer is that there are many social goods which are only available when people of like mind are in the same physical location. Among other things:
1) Walkable communities where everyone has some things in common are extremely popular (e.g. college).
2) By contrast, today many of us live corridored lives in anonymous apartment complexes, knowing more people at work than at home. Just from an efficiency perspective, that is a huge waste of time and life. Every single person there has to do a commute (or get on the internet) to meet people they know.
3) The specific location that people end up concentrated at is unimportant. But being located near someone else will be extremely important for the foreseeable future; among other things: you can't read body language, you can't yet easily collaborate on physical objects, and people can't yet reproduce over the internet :)
4) In more detail, it's a bit like dinner. Whether you meet your friends at place X or place Y doesn't matter. What matters is that you meet your friends in person. You could be more technically precise and say only the variance in location matters, and not really the mean (the specific spot on the surface of the earth).
Anyway, I have a much longer version of the essay (really, a short book) that I had to edit down which went into this and related qs. I'll post that at balajis.com soon.
Sheesh. Balaji here. Clearly this touched a nerve, so will be writing on this at some length. But this is the bit I don't get:
But when I asked him what harms techies faced that might
prompt such a drastic response, he couldn't offer much
evidence.
He pointed to a few headlines in the national press warning
that robots might be taking over people's jobs. These, he
said, were evidence of the rising resentment that
technology will foster as it alters conditions across the
country and why Silicon Valley needs to keep an escape
hatch open.
But I found Mr. Srinivasan's thesis to be naive. According
to the industry's own hype, technologies like robotics,
artificial intelligence, data mining and ubiquitous
networking are poised to usher in profound changes in how
we all work and live. I believe, as Mr. Srinivasan argues,
that many of these changes will eventually improve human
welfare.
But in the short run, these technologies could cause
enormous economic and social hardships for lots of people.
And it is bizarre to expect, as Mr. Srinivasan and other
techies seem to, that those who are affected wouldn't
criticize or move to stop the industry pushing them.
I can only speak for myself, but the motivating emotion here isn't arrogance. It's one part apprehension, knowing what happened to the Chinese in Malaysia, the Indians in Uganda, and the Jews in Europe. And it's one part hope, thinking that we can build something better with a clean slate, without 230 years of legacy infrastructure and cruft.
One of the speakers here. I found the online reaction to my talk pretty interesting as a case study in internet telephone. Here's the talk itself:
http://www.youtube.com/watch?v=cOubCHLXT6A
First party viewers mostly seemed to like it:
http://seen.co/event/startup-school-2013-cupertino-ca-2013-6...
CNET gave a second party writeup:
http://news.cnet.com/8301-1023_3-57608320-93/a-radical-dream...
Then third party people started mischaracterizing it:
http://valleywag.gawker.com/silicon-valleys-ultimate-exit-is...
Finally, the Hill wrote a fourth party account, quoting these third party accounts, and that's what Washington DC saw:
http://thehill.com/blogs/pundits-blog/state-a-local-politics...
Not everyone got it wrong; I think this account is closer:
http://www.randomhouse.ca/hazlitt/blog/virtual-expatriates-a...
But I encourage you to open up those tabs and go through them one by one to see a kind of pinball reflection of the tone of the talk. In microcosm it's an example of the emerging gap between Silicon Valley and DC, and gives a sense of how policy makers can inadvertently form their opinions from echoes of echoes. Doubly ironic and somewhat sad as we can use the internet to make direct connections between people these days. The good thing is that interested parties can see the primary source directly.
Instructor here. We'll be doing a v2 of the course after a few months and will repost the materials at that time (we've learned a ton from the first MOOC run).
Hi Smirnoff: try out the first few lectures and see if it fits your background. The key is how quickly you can pick up the web programming stuff.
The full Stanford course materials for the Jan-Mar timeframe are at stanford.coursera.org/cme184-001. The startup.stanford.edu URL tracked the first few weeks, but this was redundant for Stanford students and another page to keep up to date. So the material there is more of a teaser for people interested in the Coursera MOOC class.
That said, it will be more useful for the Coursera students to have a site that is accessible when logged out, so look for startup.stanford.edu to track the MOOC course material beginning tomorrow evening or so.
The material has changed significantly since v1. Page will be updated soon to track Coursera materials.
We'll go pretty deep on emacs, especially for REPL integration and debugging. My reasoning is that most people never get a course on an editor. But people who already use vim, Textmate, or something else can just ignore those parts and use what they are comfortable with. With 100,000+ students everyone will have some part of the course that they already know cold.
Hey guys - this is the instructor here. You can sign up for the class at coursera.org/course/startup. The startup.stanford.edu webpage will be updated sometime tomorrow to start tracking the Coursera MOOC content.
Happy to take any feature requests, bug reports, etc. here or via email (balajis at stanford dot edu).
Hey Formite - this is the instructor here. I actually did start a reasonably successful biotech/genomics company named Counsyl[1] (~200 employees, testing 3% of US births, $65M in funding) and I do think the ambit of the course is broad enough to assist with that.
It's a good strategy these days to build one's business on top of a software core, with APIs for all major business functions and physical interface layers only when absolutely necessary. That's really the overall principle that I'm trying to communicate, along with examples in practice. Let's see if I end up being successful in this pedagogical goal!
Best way I've found to do joint versioning of code with large datasets (whether binary or tab-delimited text):
1. Check in symbolic links to git. You can include the SHA-1 or MD5 in the file name.
2. Have those symbolic links point to your large out-of-tree directory of binary files.
3. rsync the out-of-tree directory when you need to do work off the server
4. Have a git hook check to see whether those files are present on your machine when you pull, and to update the SHA-1s in the symbolic link filenames when you push
By using symbolic links, at least you have the dependencies encoded within git, even if the big files themselves aren't there.