1/ Thread: "A Silicon Valley Ponzi Scheme"
Thanks to @chamath for laying this out in Social Capital's 2018 annual letter.
I've always appreciated his outspokenness.
This is creating a big bill that will soon come due...
But it's not who you think (that does), and the dynamics we’ve entered is in many ways creating a dangerous, high stakes Ponzi scheme.
Someone has to pay for the outrageous costs of this style of growth. Will it be VCs?
Likely not.
Eg: VCs habitually invest in one another’s companies during later rounds, bidding up rounds to valuations that allow for generous markups on their funds' performance.
if you’re a VC with a $200 million dollar fund, you’re able to draw $4million each year in fees.
Most funds never return enough profit for managers to see a dime of carried interest.
If u can show marked up paper returns & then parlay those returns into a newer, larger fund—say $500 million—you now have a fresh $10 million a year to use as you see fit.
There’s some deep misalignment here...
Partly why American healthcare is so expensive is bcos insurers, who play a key middleman role in setting prices for medical care, have a 2-sided biz model:
High costs allow them to charge higher premiums, allowing them to pull steadily more and more money out of patients’ and payers’ pockets.
In the end, both, patients and payers are the ones who end up as bag holders footing the bill.
The same thing is happening in today’s venture world.
Just as insurers’ biz model translates to higher costs of patient care,
So if its not VCs, who ends up holding the bag?
It’s still not who you’d expect.
In some cases, high prices may even work to their advantage.
Unlike the other pass-the-buck schemes
The real bill ends up getting shuffled outta sight to 2 other groups.
The 1st as u may guess are early stage funds’ limited partners, particularly future limited partners investing into the next fund.
Marking up Fund IV to raise money for more mgmt fees out of Fund V is so effective bcos fundraising can happen much faster than the long & difficult job of building businesses & creating real enterprise value
The second group of people left holding the bag is far more tragic: the employees at startups.
Although originally helpful as a way to incentivize and reward employees for working hard for an uncertain outcome,
Overall, you can understand how this arrangement endures:
Those companies then go spend the money on more user growth, often in zero-sum competition w/ one another.
What is the antidote here? Its 2-fold.
The 2nd is to break away from the MLM scheme that the VC-LP-user growth game has become.
It’s time to wait patiently, as the air is slowly let out of this bizarre Ponzi balloon created by the venture capital industry.
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I think about this a lot, both in IT and civil infrastructure. It looks so trivial to “fix” from the outside. In fact, it is incredibly draining to do the entirely crushing work of real policy changes internally. It’s harder than drafting a blank page of how the world should be.
I’m at a sort of career crisis point. In my job before, three people could contain the entire complexity of a nation-wide company’s IT infrastructure in their head.
Once you move above that mark, it becomes exponentially, far and away beyond anything I dreamed, more difficult.
And I look at candidates and know-everything’s who think it’s all so easy. Or, people who think we could burn it down with no losses and start over.
God I wish I lived in that world of triviality. In moments, I find myself regretting leaving that place of self-directed autonomy.
For ten years I knew I could build something and see results that same day. Now I’m adjusting to building something in my mind in one day, and it taking a year to do the due-diligence and edge cases and documentation and familiarization and roll-out.
That’s the hard work. It’s not technical. It’s not becoming a rockstar to peers.
These people look at me and just see another self-important idiot in Security who thinks they understand the system others live. Who thinks “bad” designs were made for no reason.
Who wasn’t there.
The tragedy of revolutionaries is they design a utopia by a river but discover the impure city they razed was on stilts for a reason.
— SwiftOnSecurity (@SwiftOnSecurity) June 19, 2016
I’m at a sort of career crisis point. In my job before, three people could contain the entire complexity of a nation-wide company’s IT infrastructure in their head.
Once you move above that mark, it becomes exponentially, far and away beyond anything I dreamed, more difficult.
And I look at candidates and know-everything’s who think it’s all so easy. Or, people who think we could burn it down with no losses and start over.
God I wish I lived in that world of triviality. In moments, I find myself regretting leaving that place of self-directed autonomy.
For ten years I knew I could build something and see results that same day. Now I’m adjusting to building something in my mind in one day, and it taking a year to do the due-diligence and edge cases and documentation and familiarization and roll-out.
That’s the hard work. It’s not technical. It’s not becoming a rockstar to peers.
These people look at me and just see another self-important idiot in Security who thinks they understand the system others live. Who thinks “bad” designs were made for no reason.
Who wasn’t there.
Machine translation can be a wonderful translation tool, but its uses are widely misunderstood.
Let's talk about Google Translate, its current state in the professional translation industry, and why robots are terrible at interpreting culture and context.
Straight to the point: machine translation (MT) is an incredibly helpful tool for translation! But just like any tool, there are specific times and places for it.
You wouldn't use a jackhammer to nail a painting to the wall.
Two factors are at play when determining how useful MT is: language pair and context.
Certain language pairs are better suited for MT. Typically, the more similar the grammar structure, the better the MT will be. Think Spanish <> Portuguese vs. Spanish <> Japanese.
No two MT engines are the same, though! Check out how human professionals ranked their choice of MT engine in a Phrase survey:
https://t.co/yiVPmHnjKv
When it comes to context, the first thing to look at is the type of text you want to translate. Typically, the more technical and straightforward the text, the better a machine will be at working on it.
Let's talk about Google Translate, its current state in the professional translation industry, and why robots are terrible at interpreting culture and context.
Straight to the point: machine translation (MT) is an incredibly helpful tool for translation! But just like any tool, there are specific times and places for it.
You wouldn't use a jackhammer to nail a painting to the wall.
Two factors are at play when determining how useful MT is: language pair and context.
Certain language pairs are better suited for MT. Typically, the more similar the grammar structure, the better the MT will be. Think Spanish <> Portuguese vs. Spanish <> Japanese.
No two MT engines are the same, though! Check out how human professionals ranked their choice of MT engine in a Phrase survey:
https://t.co/yiVPmHnjKv
When it comes to context, the first thing to look at is the type of text you want to translate. Typically, the more technical and straightforward the text, the better a machine will be at working on it.
