Weekly Reading 5/21

Some of the articles I’ve been reading this week:



Yesterday, I listened to a talk from the CEO of Digital Asset, Blythe Masters, on the Blockchain. It can also be described as distributed ledger, decentralized database, or digital ledger.

I surprised to realize how little I understood about the Blockchain, the differences between Bitcoin and Ethereum, and how this technology transfer and reconciliation for assets between institutions.

Like most people around Thanksgiving, I was flooded with news about the skyrocketing price of Bitcoin. It’s not the first time I’ve heard about Bitcoin. Fred Wilson got me to open a Coinbase account years ago. One of my biggest regrets wasn’t investing more then the $10 dollars they gave me to open the account. That’s lesson or issue with investing: it’s always easy to look back in time to see what you should have done. It’s much more difficult to know what to do now or anytime in the future.

One of my problems with Bitcoin is understanding why you should invest in it. It has no assets. It’s really based on faith that it will become a decentralized current and become accepted by the mainstream as a store of value.

What’s the difference between the two currencies?

Bitcoin is basically a database of accounts that is available to the public. Blyth stated, “you could download a history of all the bitcoin transaction since it’s inception.”

Ethereum is a more sophisticated version of Bitcoin. It’s faster to complete transactions. The biggest difference is the implementation of smart contracts which is basically a standard business contract but written into the code. The smart contract will execute once the conditions are met.

Blythe mentioned the positive with these types of blockchains is there integrity, since you’re able to see all of the transactions. The downside, at least for many companies, is the lack of confidentiality since of the information on the Blockchain, including the details of the smart contract, are publicly available. This is a major issue for many companies, especially large financial institutions, where sharing consumer information can be questionable ethically and in some circumstances illegal.

My biggest takeaway was the idea of live reconciliation of assets. Reconciling assets is something that can typically take a significant amount of time in many different sectors of the economy.

For the past few years, I’ve been focusing on Data Science. I’m still all in on Data Science and Artificial Intelligence but I’ll also start working on getting more education about the Blockchain. Specifically, how the Blockchain can improve the flow of assets.

photo credit: WorldSpectrum

Learn something new

Learn something new

That’s one of my daily goals. For the past year, I’ve been struggling with getting back into daily blogging so I’ve decided to write about something I’m already doing each day, learn something new.

Each day I’m going to show up to write about something new I learned in the past few days. Similar to the Alearningaday blog.

Next steps

Next steps

What’s next? It’s a common question many people ask first.

  • What’s for dinner?
  • Where should I get my next job?
  • What should we do today?
  • Who should I speak with next?
  • What’s the next turn?

The above questions aren’t bad questions. The just shouldn’t be your first question. Many people rarely ask why but that’s exactly the type of question we should all be asking ourselves.

  • Why are we doing things this way?
  • Why do we turn here?
  • Why do I need this?
  • Why am I here?

In Simon Sinek’s book, Start With Why, he discusses the importance of starting your questions here first to eventually find your answer and inspire the people around you. It’s a great book you should read if you haven’t already.

Photo Credit: qimono CC0

Why Data Science & AI

For the past few years, I’ve decided that my career in analytics needed an upgrade and that I needed to improve my data skills which lead me to studying data science. Since that time, I’ve taken Coursera courses, learned Python and some R, moved over to technology and focused on data full-time, I’ve almost worked my way through DataCamp’s Python Data Scientist certificate, and for the past few months I’ve started moving to the next step in my plan, Artificial Intelligence.

To do this I’ve started with some foundational training in Deep Learning. I’m been learning about and coding gradient descent, neural networks, and I’ve recently began studying Convolution Neural Networks (CNNs), some of the things I’ll be writing about in the coming days.

This is why I haven’t been writing as much but I want to start using this blog to write about the things I’m learning each day. That could be data science, artificial intelligence, financial markets, economics, books or articles I’ve read or some type of life lesson.

Why AI? Similar to how, a few years ago, that I decided that the future of my career path was headed toward data science, or at least a better understanding of data science. Today, I think the next step of that path is to better understand the field of artificial intelligence and how data science is moving in that direction. It’s a natural progression from my interest in data science. It’s the future. It’s also changing right now and i want to be a part of it.

Every day I want to learn something new. I’ll be using this space to write something about it each day.

A voice

A voice

I’m writing to have a voice so others don’t try to speak for me.

I need to have a voice…

To give my opinion.

To speak up.

To ask questions.

To recommend.

To decide.

To lead.

To predict.

To teach.

To manage.

To protect.

To welcome.

To share.

To give.

To move forward.