Notes from 17/2–24/2

Amazon Accidentally Sent Out Their Email Template

Hum Qing Ze
3 min readFeb 25, 2020

Succint image, short header, call to action

Applied Critical Thinking Handbook (Formerly the Red Team Handbook) [open pdf — 2MB]

This will be quite a read.

To that end, our curriculum is rich in divergent processes, red teaming tools, and liberating structures, all aimed at decision support. We educate people to develop a disposition of curiosity, and help them become aware of biases and behavior that prevent them from real positive change in the ways they seek solutions and engage others. We borrow techniques, methods, frameworks, concepts, and best practices from several sources and disciplines to create an education, and practical applications, that we find to be the best safeguard against individual and organizational tendencies toward biases, errors in cognition, and groupthink. Red teaming is diagnostic, preventative, and corrective; yet it is neither predictive or a solution. Our goal is to be better prepared and less surprised in dealing with complexity.

AI

Knowledge Graph: The Perfect Complement to Machine Learning

Quite buzzwordy, but it reminds you that it’s just a name for a knowledge representation

Blockchain

Why’s Szabo Afraid of “Smart Contract” Critiques?

Usage of the term “smart contract” is only sowing (1) chaos, (2) incoherence, (3) unnecessary complexity, (4) regulatory blowback, (5) added costs, (6) confusion, and (7) reduced innovation.

These CleanApp people are… trying quite hard.

Why are they attacking him so hard though? What I’m reading is that they are expecting more from someone who has proper legal training. Thus, deliberately using the word ‘smart’ has some implications. It is implied that Szabo had some idea that legal implications of a contract would be included in the definition of a ‘smart contract’.

Okay I’m rambling and this isn’t a serious analysis, but yes we’ve noticed a lot of issues with this misnomer.

Career

We conducted 213,000 recruitment coding tests around the world. Here’s what we learned.

Data

How to build your Ultimate Data Science Portfolios

1. Aim for simple solutions with impacts for your audiences

2. Build solutions from your domain knowledge

3. Deploy and Communicate your Solutions

I thought I saw this author before!

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