Fintech firms will become digital layers around central banks, just like banks were physical layers
Central banks will create plug and play digital infrastructure (e.g. UPI, Aadhar) on which fintech products are built
Central banks will enable fintechs to replace banks
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Legacy site *downloads* ~630 KB CSS per theme and writing direction.
6,769 rules
9,252 selectors
16.7k declarations
3,370 unique declarations
44 media queries
36 unique colors
50 unique background colors
46 unique font sizes
39 unique z-indices
https://t.co/qyl4Bt1i5x
PWA *incrementally generates* ~30 KB CSS that handles all themes and writing directions.
735 rules
740 selectors
757 declarations
730 unique declarations
0 media queries
11 unique colors
32 unique background colors
15 unique font sizes
7 unique z-indices
https://t.co/w7oNG5KUkJ
The legacy site's CSS is what happens when hundreds of people directly write CSS over many years. Specificity wars, redundancy, a house of cards that can't be fixed. The result is extremely inefficient and error-prone styling that punishes users and developers.
The PWA's CSS is generated on-demand by a JS framework that manages styles and outputs "atomic CSS". The framework can enforce strict constraints and perform optimisations, which is why the CSS is so much smaller and safer. Style conflicts and unbounded CSS growth are avoided.
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!
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What a weekend celebrating makers looks like.
A thread
👇Read on
Let's start with a crazy view of what @ProductHunt looked like on Sunday
Download image and upload
A top 7 with:
https://t.co/6gBjO6jXtB @Booligoosh
https://t.co/fwfKbQha57 @stephsmithio
https://t.co/LsSRNV9Jrf @anthilemoon
https://t.co/Fts7T8Un5M @J_Tabansi
Spotify Ctrl @shahroozme
https://t.co/37EoJAXEeG @kossnocorp
https://t.co/fMawYGlnro
If you want some top picks, see @deadcoder0904's thread,
We were going to have a go at doing this, but he nailed it.
It also comes with voting links 🖐so go do your
#24hrsstartup was an amazing event
— Akshay Kadam(A2K) \U0001f47b (@deadcoder0904) November 19, 2018
I never went to a hackathon but this just felt like one even though I was just watching \U0001f440
Everyone did great but there were a few startups that I personally loved \U0001f496
Some of my favorites are in the thread below\U0001f447
Over the following days the 24hr startup crew had more than their fair share of launches
Lots of variety: web, bots, extensions and even native apps
eg. @jordibruin with
\U0001f3a8\U0001f3c3\u200d\u2640\ufe0f DrawRun just launched on Product Hunt! Idea to App Store to Product Hunt in 68 hours!\u2070\u2070https://t.co/mxnLZ8FRSu
— Jordi Bruin (@jordibruin) November 20, 2018
Thanks for the motivation @thepatwalls @arminulrich @_feloidea