In the future, if you want a job, you must be as unlike a machine as possible: creative, critical and socially skilled. So why are children being taught to behave like machines?

Welcome to’s 7 week course, Practical Deep Learning For Coders, Part 1, taught by Jeremy Howard (Kaggle’s #1 competitor 2 years running, and founder of Enlitic). Learn how to build state of the art models without needing graduate-level math—but also without dumbing anything down. Oh and one other thing… it’s totally free!

It may come as an even greater surprise that bushido once received more recognition abroad than in Japan. In 1900 writer Inazo Nitobe's published Bushido: The Soul of Japan in English, for the Western audience. Nitobe subverted fact for an idealized imagining of Japan's culture and past, infusing Japan's samurai class with Christian values in hopes of shaping Western interpretations of his country.

Though initially rejected in Japan, Nitobe's ideology would be embraced by a government driven war machine. Thanks to its empowering vision of the past, the extreme nationalist movement embraced bushido, exploiting The Soul of Japan to pave Japan's way to fascism in the buildup to World War II.

This article outlines the scale of that codebase and details Google's custom-built monolithic source repository and the reasons the model was chosen. Google uses a homegrown version-control system to host one large codebase visible to, and used by, most of the software developers in the company. This centralized system is the foundation of many of Google's developer workflows. Here, we provide background on the systems and workflows that make feasible managing and working productively with such a large repository. We explain Google's "trunk-based development" strategy and the support systems that structure workflow and keep Google's codebase healthy, including software for static analysis, code cleanup, and streamlined code review.

Our extensive use of Perl to build many of our internal services often comes as a surprise to many and we can understand why. Perl is a dinosaur among mainstream programming languages. It lacks the glamour that other, relatively younger languages have. There is also a common misconception in the programming world that modern software engineering practices cannot be followed with a language like Perl. In this post, we hope to debunk that myth. We want to give you a glimpse of the developer experience (DX) here at Semantics3 where we write a lot of Perl code but still manage to employ the latest engineering best-practices. We would like to highlight that we are able to do so with the help of a tool-chain written entirely in Perl.

When you purchase your system with a mainboard and Intel x86 CPU, you are also buying this hardware add-on: an extra computer that controls the main CPU. This extra computer runs completely out-of-band with the main x86 CPU meaning that it can function totally independently even when your main CPU is in a low power state like S3 (suspend).

GitHub is the go-to place to host your open source projects, that much is well known. A lot of companies also use their paid plans to get the ecosystem around GitHub for their own code. Why would you want to use anything else? We took the decision to move away from GitHub and in the end we benefitted hugely!

“We’re trying to be really agile, so we don’t waste time on design or documentation.”

“I have to ship this to production immediately, so I don’t have time to write tests!”

“We didn’t have time to automate everything, so we just deploy our code by hand.”

I don’t know about you, but I’ve always been uncomfortable with Jenkins’ apparent statefulness. You set up your Jenkins server, configure it exactly as you want it, then DON’T TOUCH IT.

Fortunately I now have a solution. With a combination of Docker, Python’s Jenkins API modules, the Jenkins job builder Python module, and some orchestration using docker-compose, I can reproduce my Jenkins state at will from code and run it in isolated environments, improving in iterable, track-able steps.

Why has Bitcoin failed? It has failed because the community has failed. What was meant to be a new, decentralised form of money that lacked “systemically important institutions” and “too big to fail” has become something even worse: a system completely controlled by just a handful of people. Worse still, the network is on the brink of technical collapse. The mechanisms that should have prevented this outcome have broken down, and as a result there’s no longer much reason to think Bitcoin can actually be better than the existing financial system.

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