The concept of “programmable money” made possible by the blockchain has gained a substantial amount of traction this year, but this is just the beginning.
With about $13B assets in decentralized finance, the space is evolving at an extremely rapid pace. However, it is still in a nascent phase with the potential of bringing new paradigms to financial services. To create a mapping from mainstream financial services to defi, we will use the fintech space as a proxy.
Fintech has unbundled banks and almost every other traditional financial institution. Moreover, those institutions otherwise known as “traditional” are also going out of their ways to embrace high tech by building it into their products or making strategic acquisitions. …
Payments Systems in the US by Carol Coye Benson, Scott Loftesness and Russ Jones was among the most informative books I read on the financial services industry. Below are some key snippets I’d like to retain and share.
The payments industry is different from other processing industries in terms of the value of money being transferred through the system. Providers who realize revenue related to gross value of the payment transaction (the “amount”) are more likely to have profitable businesses than those who realize revenue simply on a fee-per-transaction basis.
Brex’s diverse customers use a variety of software tools to run and grow their businesses. About half of all our customers use some form of ERP (Enterprise Resource Planning) application and expect Brex data to seamlessly integrate with their existing productivity tools.
In late 2019, we identified two sizable opportunities:
We built the Accounting API to enable ERPs to pull data from Brex through a direct transaction feed, and to allow bookkeeper apps to integrate with Brex for analytics, budgeting, and more. …
Brazilian finance minister Guido Mantega flatly declared in late September 2010 that a new currency war had begun.
At the heart of every currency war is a paradox: currency wars are fought internationally but they are driven by domestic distress.
They begin due to insufficient internal growth. High unemployment, low or declining growth, weak banking sector and deteriorating public finances.
Difficult to generate growth in purely internal means. Promotion of exports through devalued currency becomes the engine of last resort.
GDP is characterized by Consumption, Investment, Government spending, Net exports (exports minus imports)
GDP = C + I + G + (X —…
After almost 2 years, I wrapped up my time as a software engineer in the Siri Search team within AI/ML at Apple. I’m lucky to have joined an action-packed group within a company I’ve admired since childhood — one that has shaped humanity and became the most beloved brand on the planet. Goodbyes were bittersweet, but I take solace in knowing that Apple will always be part of my identity, like a package/dependency in the software within me.
Fun fact: The Breakout List (known for featuring hot startups) included Apple Siri in its list of “High Potential and High Growth Companies.” …
By now, we should be pretty familiar with the process of loading in image data and creating a DataBlock ( like
# convert mode specified is for black/whiteLoad in the data
il = ImageList.from_folder(path, convert_mode='L')
Inside an items list
il is the image you gave it, so you can index into the list and view the image content.
Techniques for avoiding overfitting
Lecture announcement: platform.ai allows you to train models using images. You can use this as a tool to train models on unlabelled data.
Dataset: Rossman Store…
Reviewing some concepts from last lecture — remember that activation functions are element-wise. The function is applied to each element in the input.
So if the input to an activation function is a 20-element long vector, the output will be of the same size. ReLU is the main one we’ve looked at.
Universal Approximation Theorem: If you have big enough matrices, it can solve any arbitrarily complex mathematical function to any arbitrary level of accuracy. …
We continue to look at NLP.
25,000 movie reviews in the IMDB dataset. It’s not enough information. So the trick is to use transfer learning!
The idea is we use a pre-trained model that has been trained to do something different to what we’re trying to do. …