Observing the public conversation around FB, and the private ones happening among techies and ex-FBers, I think the mutual misunderstanding is worse than when I set out two years (and 500 pages) ago to (in a small way) bridge that gulf.
We're basically fucked.
Techies take weird, improbable visions, and make them realities: some BS pitch deck to a VC, mixed with money and people, really does turn into some novel thing.
Facebook & Co. can take on the most egregious disinformation examples, or efforts undertaken by identifiable state actors (maybe), but it will never be able to shut it down entirely.
Why do I feel confident in this assertion (that I'm sure will get trolled)?
Where'd that end up? Nowhere. We got GDPR, which is pointless, and if anything solidified FB/GOOG's position in Europe. Ditto CCPA.
If you sat down to a meal in the 80s, and took out a camera and took a photo of your food, while telling everyone you were sending copies to your friends, you'd have been locked up in an insane asylum.
The Beacon scandal that blew up FB in the late aughts now seems like a joke. People got worked up over that?
We'll read the current disinformation coverage the same way.
It's the bridge generation (looks in mirror) that's mostly freaking out about it.
We as a species are dumb. We don't learn anything, and only technical and scientific knowledge is cumulative.
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For technical founders it is irrationally, obscenely hard to reverse years of programming (ba dum bum) that sales is a value-destroying activity. Sales is CLEARLY a value-creating activity, contingent on you have a value-creating product.
The world will not drop what they are doing to adopt your work. This is particularly true in B2B, where simply building a better mousetrap won't overcome the activation energy required to get people with additional non-mice problems to prioritize changing mousetraps today.
This is very non-obvious for founders because founders are not often people who *want* to be sold to. We often come from a background where trying out tools is a bit of a fun hobby. We like looking at all the options, making charts, and ripping out partially complete tests.
"This week I unsuccessfully trialed four software options for automating that thing that has been killing us. Our actual production process remains the same as last week. Don't worry; this was a great use of time." is not a thing you want to write in a progress report to manager.
You are interviewed for multiple skills simultaneously. Cognitive skills, communication, leadership are a few to name. If the point is not finding a solution, then what is it? Let me explain.
Your interviewers try to understand what it feels like to work with you on a daily basis. An interview question is just a tool in achieving that, it is not there to specifically measure your skills on a topic but a tool to understand the depth of your thinking.
Before the interview starts, ask them what they want to get out of this interview. Good interviewers should already have a plan and a set of expectations. Ask them what you should do. Don't start coding yet. Ask them you should produce. Discussion, diagrams, pseudo code, code?
Then, start cracking the question. List whatever questions you think it is important to solve this question, ask your edge cases. Get to a point where you are discussing about pros/cons of the solutions. These steps are critical. Don't just start coding. Have a consensus first.
The new 12.9" iPad Pro is physically smaller than the old one with the same screen size. It's roughly the same size as an 8.5 x 11 piece of paper. 5.9mm thick.
10 billion transistors in the A12X. 8-core CPU. 7-Core GPU. 35% faster single-core performance. 1000x faster GPU. iPad Pro is Xbox One S class GPU performance in "94% smaller" package, Ternus jokes.
Apple's silicon team is just dropping bombs every event.
live shot of Apple's silicon team
iPad Pro gets USB-C for up to 5K external displays and enables charging out to iPhones. Wild.
At the heart of this lies the most important technique in modern deep learning - transfer learning.
Let's analyze how it
THREAD: Can you start learning cutting-edge deep learning without specialized hardware? \U0001f916— Radek Osmulski (@radekosmulski) February 11, 2021
In this thread, we will train an advanced Computer Vision model on a challenging dataset. \U0001f415\U0001f408 Training completes in 25 minutes on my 3yrs old Ryzen 5 CPU.
Let me show you how...
2/ For starters, let's look at what a neural network (NN for short) does.
An NN is like a stack of pancakes, with computation flowing up when we make predictions.
How does it all work?
3/ We show an image to our model.
An image is a collection of pixels. Each pixel is just a bunch of numbers describing its color.
Here is what it might look like for a black and white image
4/ The picture goes into the layer at the bottom.
Each layer performs computation on the image, transforming it and passing it upwards.
5/ By the time the image reaches the uppermost layer, it has been transformed to the point that it now consists of two numbers only.
The outputs of a layer are called activations, and the outputs of the last layer have a special meaning... they are the predictions!
Differential privacy was invented in 2006. Seems like a long time but it's not a long time since a fundamental scientific invention. It took longer than that between the invention of public key cryptography and even the first version of SSL.
But even in 2020, we still can't meet user expectations.
* Data users expect consistent data releases
* Some people call synthetic data "fake data" like
* It's not clear what "quality assurance" and "data exploration" means in a DP framework
We just did the 2020 US census
* required to collect it by the constitution
* but required to maintain privacy by law
But that's hard! What if there were 10 people on the block and all the same sex and age? If you posted something like that, then you would know what everyone's sex and age was on the block.
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Here’s the story of how Malcom McLean made a billion dollars and which startup could be following in his footsteps. (Inspired by our episode with @laurabehrenswu)
In the early 1950s, the shipping industry was a dying business.
New York’s docks were handling half as much domestic cargo in the early 1950s as they had been in the depressed 1930s.
In thirty years, no one had invested significant money in coastal shipping.
As McLean found out, loading ships was difficult and slow.
A truck or train would deliver items to the port. Each item was unloaded separately, recorded, and carried to storage.
When a ship was ready, each item was taken from storage, counted again, and hauled on-board.
The cost of this labor was significant. As one expert at the time explained:
“A four-thousand-mile voyage for a shipment might consume 50 percent of its costs in covering just the two ten-mile movements through two ports.”
Yet, despite the industry’s issues, it felt little pressure to change.
Foreigners were barred from operating domestically. Cartels ran international routes. And gov. subsidies eased the pain of labor costs.
Reshaping the industry needed an outsider.
Enter Malcolm McLean.
On this lovely Black Friday…
I wanted to breakdown a quick, profitable mindset shift for any and all trying to make money online.
→ How to turn your problems/hardships into cold, hard cash
Here’s the mindset:
→ Every problem you have in life can be converted into cold hard cash on the Internet
Because you are NOT unique.
If you have a problem, there’s thousands of others out there who are having similar issues.
Solve your problem.
Solve their problem.
That’s the equation.
But enough of the got damn fluff, let’s take a look at specific examples:
I wanted to learn how to speak better Spanish.
I’d been traveling for years, but never took the time to study.
In the 1990s, a maverick breast surgeon at @TataMemorial (fresh from his return from the UK) stepped up to do research. Now, to understand the situation, you should go back 30 years, when research was not as big as it is now, and certainly not from surgeons.
Surgeons, and especially cancer surgeons, were renowned for their technical prowess, and their sheer bravado – "wherever the cancer, however advanced, I will take it out". So, our surgeon-researcher was ridiculed for even attempting clinical research
For a surgeon, he couldn’t have chosen a worse topic to research on: early detection; nothing to do with surgery, or even treatment. Remember, this was the 1990s. Cowboy surgery was celebrated, and research ridiculed
Being a breast surgeon, he was troubled with women consistently coming with advanced cancers, and he set out to see if he could work on picking them up at an earlier stage. But community-based early detection needs money, and he just didn’t have it.
2) We were down in the lobby and I was kind of crushed. I don’t know what I expected, The Thing and the Yancy Street Gang to be sitting around smoking cigars? Anyway, my Dad was taking a beat to figure where we were going next and a guy came up to us.
3) He was wearing a white shirt and tie and said to Dad “Is he disappointed because. The Marvel offices were just offices?” My Dad said yes and then the guy who had gray around his temples and a mustache said “hold on a second” and opened one of those office mailboxes with a key.
4) He then handed me a thick stack of EVERY SINGLE MARVEL COMIC COMING OUT THE NEXT MONTH. “Here you go. Keep reading Marvel comics” he said and then walked off. I left in a daze and about 15 minutes later it hit me “Gray around the temples, mustache... That was Stan Lee!”
5) Later when I wrote on the Ant Man movie I told Kevin Feige the story, the year, look of the guy etc and Kevin said “That’s exactly the kind of thing Stan would do and he would have been there then. That was him.” Rest In Peace Stan Lee and thank you for the comics.
What you call chaos I call spontaneity.
A regimented life is like a heartbeat that's non-chaotic; it's a system that’s too ordered. It doesn't have any life to it. And real life has lots of ups and downs, some of them very extreme.
I over-plan, but planning is pretty useless. What tends to dominant life are a small number of Black Swan events in both directions, positive and negative.
Expose yourself to asymmetric upside and lots of good options: things that can become massively important for you.
And you want to avoid the asymmetric downside: anything that can end the game, whether it's through financial ruin, or reputational ruin, or physical ruin.
That requires a certain amount of chaos and spontaneity.
If nothing else, 2020 taught the power of optionality.
We think about planning as linear and controlled, but that's not how the world around us works anymore.
The world is dominated by nonlinearities, so understanding options value is far more important.