Learning journal — Week 4 takeaways
This week’s readings and videos were about topics I did not have explored before, like testing and continuous integration. I got to know more about the tools like the simian army and the concepts of chaos engineering.
In addition, I got to explore a little more about quantum computing, like last week, I did not quite understand all the formulas but little by little I understand a little more about the topic and get to know about the people who have made this part of science advance.
by Mayra Lucero García Ramírez
⏳🖥 Computing & Science
- Seth Lloyd on Programming the Universe — Seth Lloyd
- Seth Lloyd: Quantum Machine Learning — Seth Lloyd
- Why We Should Have Your Own Black Box? — Matthew Syed
- Richard Feynman, The Great Explainer: Great Minds — Richard Feynman
- Stephen Wolfram: Computing a theory of everything — Stephen Wolfram
- TEDxCaltech — Tony Hey — Feynman and Computation — Tony Hey
- TEDxCaltech — Danny Hillis — Reminiscing about Richard Feynman — Denny Hillis
- Feynman on Scientific Method. — Richard Feynman
- The Pretotyping Manifesto — Alberto Savoia
- Tools for Continuous Integration at Google Scale — John Micco 🔗
- Testing Engineering@Google & The Release Process for Google’s Chrome for iOS — Ivan Ho & Lindsay Pasricha 🔗
- GTAC 2014: I Don’t Test Often … But When I Do, I Test in Production — Gareth Bowles 🔗
- GTAC 2014: Test coverage at Google — Andrei Chirila 🔗
- GTAC 2014: The Testing User Experience — Alex Eagle 🔗
- Chaos Engineering: the history, principles, and practice — Tammy Butow 🔗
- Breaking Things at Netflix — Kolton Andrus 🔗
🔨⚙️ Testing & Automation
Through the series of videos on testing and automation, I understood how testing is really important and how at great scale, talking about enterprises like Facebook, Google, Netflix among others testing is a crucial part to ensure their services. The necessity to test their services has opened a path to Chaos Engineering.
Chaos engineering consists of a series of tools and practices that consist of breaking things (awesome, right?). The purpose of “break things” of their own is to discover vulnerabilities, errors and failures firsthand and not wait for the event happens while they are unprepared. The bottom line is being prepared, prevent, and be immune to failures, incidents and losses using a sort of vaccine that is a consequence of breaking things. The simian army are great tools that fulfill this purpose.
In the same way and strongly related to testing is continuous integration, make changes without breaking something is very important, code review, code coverage, great practices that have lead enterprises to have reliable services.
These videos, explain how the inventions are done and how they fail or succeed. One part that caught my attention is that ideas can be really good, but in implementation there can be failures, can be no interest in it, and without interest in a product, it just won’t work. So how do we avoid building something that won’t work? here is where pretotyping enters, simulate a result of what the product will be lead us to show it and start seeing if it would work. If it would be we can pass to prototyping, to build, if not, the best way to go is to fail fast and find another idea (we can spot innovators) and continue searching.
Success is about mindset, ask questions and learn, the black box concept refers to know what happened, how it happened and then learn from the situation and move on.
Also, for this week’s assignments we develop 3 ideas using the pretotype technique and it can be found in here.
Computer Science & Quantum Computing 🧬⚗️
🔗Seth Lloyd on Programming the Universe 🔗Seth Lloyd: Quantum Machine Learning 🔗Richard Feynman, The Great Explainer: Great Minds 🔗Stephen Wolfram: Computing a theory of everything 🔗TEDxCaltech — Tony Hey — Feynman and Computation 🔗TEDxCaltech — Danny Hillis — Reminiscing about Richard Feynman 🔗Feynman on Scientific Method.
These ones were also very interesting, they mostly talk about Richard Feynman, a physicist who had a great impact on science, computer science and quantum computing, talking about the Feynman diagrams and quantum mechanics and as a collaborator of the Manhattan project. Feynman is not only remembered for its collaboration to science, but also because of his thinking outside the box and his way to explain and do things in a very particular, funny way.
Computer Science has the limitation of the world information processing, quantum computing is more focused on that, in the behavior of the world, the universe.