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Hmm, this article took a quick turn into a story about how it takes just one year of coding experience + something from fast.ai to become "world-class deep learning practitioners"; make of that what you will.
Earlier quoted context omitted.
I don't see anything that mentions just a year of coding experience, but as a participant in their free MOOC I can say that it's highly worthwhile. It's unique and complimentary to the more academic material usually found on deep learning.
From the article... "And even for highly technical aspects like deep learning, fast.ai has shown that people with 1-year of coding experience can become world-class deep learning practitioners; you don’t need to hire Stanford PhDs. "
I agree a lot with #3 but disagree heavily with #4. There are canonical examples of PhD theses that became successful companies, not to mention the dozens of companies who exited (e.g. CV companies to Qualcomm).
Yeah, Akamai, Google, to some extent Bose come to mind. Most PhD theses would NOT become companies, so this is good advice for a PhD student but not for a founder. If a founder finds a PhD thesis that is worth productionizing, then the fact that it was a PhD thesis is irrelevant.
Hmm, this article took a quick turn into a story about how it takes just one year of coding experience + something from fast.ai to become "world-class deep learning practitioners"; make of that what you will.
I don't think that's too outrageous as long as we don't read "practitioners" and hear "experts". Agree that the article is a thinly disguised recruiting advertisment though.
The way I'd frame it is:
1) If you want to build a company that is venture scale, taking VC funding is a great option to consider. If you don't want to build such a company, VC funding is a very poor option.
2) There are good and bad VCs. The bad ones suck. The good ones will help you and support you even if the outcome is 2x or 0x. Fred Wilson at Union Square Ventures articulates this attitude well in several posts:
a) "If you look at the distribution of outcomes in a venture fund, you will see that it is a classic power law curve, with the best investment in each fund towering over the rest, followed by a few other strong investments, followed by a few other decent ones, and then a long tail of investments that don’t move the needle for the VC fund.
But that long tail is comprised of entrepreneurs and their teams. People who have given years of their lives to a dream that was ultimately not realized.
And as I have written many times over the years on this blog, I spent the majority of my time on that long tail. This is irrational behavior if you think about fund economics, but I believe it is rational behavior if you think about firm reputation." (http://avc.com/2015/11/power-law-and-the-long-tail/)
b) "There are two interesting things here that I always think about. The first is that even the very best investors in the VC business only get a hit about 1/3 of the time. That means that they have their share of "slog it outs" and "hit the walls" too. I am certainly in that camp. The second is that we end up spending an incredible amount of time and energy (hopefully not money) on the 2/3 of our investments that don't work out. When everything goes well, you really don't need that much from a VC. Of course, I have added value in all of my winners. But its the ones that don't work that I have left my blood, sweat, and tears on. And that's the paradox of being a VC that cares. Which is the only kind of VC you want to work with." (http://avc.com/2013/03/when-things-dont-work-out/)
I agree a lot with #3 but disagree heavily with #4. There are canonical examples of PhD theses that became successful companies, not to mention the dozens of companies who exited (e.g. CV companies to Qualcomm).
For what it's worth, trends #4 and #5 are both qualified with "AI Specific" further down. There will be some PhD theses that do solve real problems, but many are not going to make a startup successful by themselves.
Negative trend 6: adopting a trendy, complex web stack before you absolutely have to when a simple one would get you to market faster
VC is a "trend to avoid"? Avoid "Hypergrowth"? I guess companies like Google, Facebook, Twitter, Amazon, Stripe, Airbnb, Dropbox, Pinterest and a hundred others all really messed up.
I mean I could go point by point and give examples that are the opposite of these trends, but that isn't any more meaningful than these suggestions. You can choose to run a company however you want, and you should. If you believe these things are bad, don't do them. Attract employees that agree with you. The market will decide if you are right or not.
But enough with the blog posts about it, especially if they are dismissing critical tools that many companies use very successfully. Every company is different, every product is different, every team is different. Use some common sense on what tools make sense for you, and keep an open mind.