People sometimes ask me what my vision of DeFi is. This is a very tough question. DeFi is very messy with thousands of experiments happening. But high level, I think DeFi will go through 2 phases:
1) This will ultimately lead to hundreds of millions of users to install wallets and get uncomfortable with the UX.
2) This will force the tech (especially scaling) to mature.
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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.
"I really want to break into Product Management"
make products.
"If only someone would tell me how I can get a startup to notice me."
Make Products.
"I guess it's impossible and I'll never break into the industry."
MAKE PRODUCTS.
Courtesy of @edbrisson's wonderful thread on breaking into comics – https://t.co/TgNblNSCBj – here is why the same applies to Product Management, too.
There is no better way of learning the craft of product, or proving your potential to employers, than just doing it.
You do not need anybody's permission. We don't have diplomas, nor doctorates. We can barely agree on a single standard of what a Product Manager is supposed to do.
But – there is at least one blindingly obvious industry consensus – a Product Manager makes Products.
And they don't need to be kept at the exact right temperature, given endless resource, or carefully protected in order to do this.
They find their own way.
make products.
"If only someone would tell me how I can get a startup to notice me."
Make Products.
"I guess it's impossible and I'll never break into the industry."
MAKE PRODUCTS.
Courtesy of @edbrisson's wonderful thread on breaking into comics – https://t.co/TgNblNSCBj – here is why the same applies to Product Management, too.
"I really want to break into comics"
— Ed Brisson (@edbrisson) December 4, 2018
make comics.
"If only someone would tell me how I can get an editor to notice me."
Make Comics.
"I guess it's impossible and I'll never break into the industry."
MAKE COMICS.
There is no better way of learning the craft of product, or proving your potential to employers, than just doing it.
You do not need anybody's permission. We don't have diplomas, nor doctorates. We can barely agree on a single standard of what a Product Manager is supposed to do.
But – there is at least one blindingly obvious industry consensus – a Product Manager makes Products.
And they don't need to be kept at the exact right temperature, given endless resource, or carefully protected in order to do this.
They find their own way.
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.
