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Give Up GitHub

The Time Has Come!

Photo by Caleb White on Unsplash

This is the twenty-sixth edition of CrunchX and here are the stories and resources we thought were worth spending the time.

1. Give Up GitHub: The Time Has Come!

Denver talks about the mistake OSS developers made with Sourceforge. And how it can play out all over again with Github. The most interesting fact is that Microsoft doesn’t give the answer on what codebases they train Github Copilot… Check out if you’re an open source developer, or don’t like your code getting stolen. Written by Denver Gingerich and Bradley M. Kuhn on Software Freedom Conservancy and editorial selection by Miloš Živković. Read the article here:

https://sfconservancy.org/blog/2022/jun/30/give-up-github-launch/

2. Everything DARPA’s Been Doing for the Last 20 Years

You may recall DARPA (The US Defense Advanced Research Projects Agency) and its pivotal role in the development of the internet as we know it today. Gizmodo, as part of its 20-year anniversary, has a fascinating article on DARPA’s projects over the last 20 years — via interviews with many of its officials — the successes, the failures, and the truly bizarre. Well worth a read. Written by Mack DeGeurin on Gizmodo and editorial selection by Dr. Stuart Woolley. Read the article here:

https://gizmodo.com/interview-with-darpa-director-on-20-years-of-invention-1849158793

3. Programming-Idioms

I personally love idioms, in both prose and programming languages, as it’s always fun to compare and contrast how you’ve been doing things to how other people do things if you haven’t been exposed to them before. To that end, Programming-Idioms has a selection of cheatsheets containing common programming idioms in a range of languages. Fun to look through, and you might also learn something — or improve on what’s already there. Editorial selection by Dr. Stuart Woolley. Visit the cheatsheet here:

https://programming-idioms.org/cheatsheets

4. Technological doping: The science of why Nike Alphaflys were banned from the Tokyo Olympics

Technological advancements in Nike’s Alphafly line of running shoes helped runners so much that it was deemed “technological doping.” Banned from the Tokyo Olympics, these shoes helped runners break records by granting improvements in speed and efficiency. Written by James Witts on Science Focus and editorial selection by Antony Terence. Read the article here:

https://www.sciencefocus.com/the-human-body/nike-alphafly-banned-technological-doping/

5. Scientists brought a dead pig’s cells and organs back to life — and yours could be next

Scientists at Yale develop a method to restore cellular activity in the organs of a dead pig, breaking new ground in the organ preservation space. Dubbed OrganEx, the method also has the potential to tackle disorders like ischemia. Written by Rupendra Brahambhatt on Interesting Engineering and editorial selection by Antony Terence. Read the article here:

https://interestingengineering.com/science/dead-pigs-cells-organs-life-yours-next

6. How we work: moving fast to ship customer value

Chris talks about the values of shipping code. Trunk-based development is the first one. Although other flows are present this one gets the most bang for the buck. And the second one I like is that deployment is a non-event. If you don’t have continuous deployment the code quality suffers. Written by Chris Bell on Knock and editorial selection by Miloš Živković. Read the article here:

https://knock.app/blog/how-we-work-moving-fast-to-ship-customer-value

7. 10 Best-Paying Jobs in Data Science

A career in the field of Data Science has become the goal of many young people these days. This article shows you 10 jobs that are best paying their employees. The professions of Data Modellers, Data Scientists, and Data Engineers are on the list. Written by Cynthia Harvey on InformationWeek and editorial selection by Christianlauer. Read the article here:

https://www.informationweek.com/big-data/10-best-paying-jobs-in-data-science

8. Why Python alone will make you Fail in Data Science Job?

Python can be considered essential when working in Data Science, however, it cannot be the only programming language skill one should have in order to be successful in their job since Python cannot perform in all areas when analyzing vast amounts of data. Written by Sirisha on Analytics Insight and editorial selection by Christianlauer. Read the article here:

https://www.analyticsinsight.net/why-python-alone-will-make-you-fail-in-data-science-job/

9. Machine Learning Makes Life Easier for Data Scientists

The terms Data Science and Machine Learning often occur simultaneously, when talking about developing new products or services. However, they are not the same and have different focus areas. This article is diving deeper into the definition and theoretical background of these two terms. Written by Eray Eliacik on Dataconomy and editorial selection by Christianlauer. Read the article here:

https://dataconomy.com/2022/08/machine-learning-vs-data-science/

10. How AI Can Prevent Rising Candidate Fraud

A study has shown that candidates have been lying more than ever when it comes to their skills and CVs in order to get hired, since before the pandemic. The numbers in this regard have nearly doubled according to the study. Therefore, AI has been the weapon of choice to combat this development within the job market. Written by the editorial team on insideBigData and editorial selection by Christianlauer. Read the article here:

https://insidebigdata.com/2022/08/04/how-ai-can-prevent-rising-candidate-fraud/

Closing Note

These are our picks for this week. Hope you found something new, inspiring, astonishing, and knowledgeable news going around the tech space. Thank you very much for taking the time to read this edition of CrunchX. Look out for the next edition the following week.

Regards,

CodeX Team

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Nikhil Adithyan

Nikhil Adithyan

Founder @CodeX (medium.com/codex), a medium publication connected with code and technology | Top Writer | Connect with me on LinkedIn: https://bit.ly/3yNuwCJ