kahnjw
Joined 10 years ago
Joined 10 years ago
I'd say anyone drawing conclusions from a a few weeks data has a 50% chance of getting burned at this point.
Were Linkedin, Instagram, Beats by Dre, WhatsApp, Tableau, Skype, GitHub, MuleSoft all failures because they were acquired for billions, making lucrative paydays for their founders and investors?
1. There are plenty of companies on the path to IPO that didn't take 1B+ in VC money 2. The "sharing" platforms are expensive investments because there are so many players fighting for market share.
We're talking about a strategy of fast growth vs slow and steady. All the companies we've mentioned so far invested in fast growth early on, whether from VC or reinvestment.
Every year, VC in the US _as a whole_ invests roughly 100B [2]. If you cut out non-growth and non-tech sectors I'd guess that number total goes to around 40B, and roughly 100B (very rough number) globally.
So yeah, some money gets "wasted" but it creates huge market capitalizations that are around two full orders of magnitude larger than a single years investment, and growing strong year over year.
[1] https://www.investopedia.com/terms/f/faang-stocks.asp [2] https://www.prnewswire.com/news-releases/us-venture-capital-...
I agree that GrubHub, Doordash, and to some extent Uber seem bloated when considering the sum total of the markets they play in. That doesn't mean these business models aren't sustainable, though. Some companies allocate resources to a few areas that turn into profit centers, some don't. The ones that don't will be sold off or parted out. And the cycle will continue. I'd wager that one of these companies will survive and turn out to be a profitable, healthy business in the next few years. The rest will probably be sold off or slowly downsized.
More broadly, to your criticism of SV's investment strategy, resource allocation is a hard problem. If you want to direct large sums of capital at certain business verticals, do you want to grow slowly and steadily over a 20+ year period only to find that the economics don't work, or do you want to fail fast with some extra waste in the middle? Failing fast has some upside to it, though I understand why I consistently hear this criticism on this site. It feels like the last decade has seen the pendulum swing towards fast money and back a little. I don't think were as far off from a healthy middle ground as some might argue.
Deep learning has surpassed human level performance on many tasks [1][2]... (could add more you get the point).
[1] https://www.sciencedirect.com/science/article/pii/S2215017X1... [2] https://arxiv.org/pdf/1502.01852v1.pdf