By

Dr. Thibault Schrepel

A list of open-access resources to learn computer science

With each passing day, our societies become a little more digital. In this context, I decided to list free access resources to learn the fundamentals of computer science (basic programming, artificial intelligence, blockchain, cryptography…). These resources do not require any prior technical knowledge; they are all accessible, fun, and academic. I classified them per field of expertise and level....
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Reading suggestions – April 2021

This post features my latest reading suggestions based on the academic papers and press articles that I enjoyed reading in April 2021. As I tend to favor the active sharing of open-source publications, you can follow me on Twitter (@LeConcurrential) or LinkedIn (here) to access similar articles on a more regular basis. SUBSCRIBE TO THE CONCURRENTIALISTE NEWSLETTER (100% free) SUBSCRIBE TO THE STANFORD COMPUTATIONAL ANTITRUST NEWSLETTER...
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Documenting computer science resources for social scientists

EDIT: here are the results! Thank you! *** Dear all, I have created this short Google form to document open-access resources that could help social scientists (lawyers, economists,  political scientists, psychologists…) learn (about) computer science (broadly speaking, being basic programming, AI, blockchain, cryptography…). I will make the final list open access on www.leconcurrentialiste.com. Thank you very much for...
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Reading suggestions – March 2021

This post features my latest reading suggestions based on the academic papers and press articles that I enjoyed reading in March 2021. As I tend to favor the active sharing of open-source publications, you can follow me on Twitter (@LeConcurrential) or LinkedIn (here) to access similar articles on a more regular basis. SUBSCRIBE TO THE CONCURRENTIALISTE NEWSLETTER (100% free) SUBSCRIBE TO THE STANFORD COMPUTATIONAL...
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Why “future proof” regulation is a bad idea

One day, we will be in a position to develop evolutive regulation. The law will modify on “its own” using different machine learning systems adapting to their environment. “Future-proof” regulation will then become not only possible but also very handy. In the meantime, it is… not a great idea. At all. Let me explain. Our world evolves constantly. Complexity science...
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“Control = liability”: exploring Section 230, the DSA, Big Tech, Wikipedia and Blockchains

Control equals liability. Anyone who controls an area, product, or service—whether physical or digital—is responsible for what happens there (or with it). There are some exceptions to this rule, but the principle remains. For instance, the manager of a bar is liable if a customer trips over a case of wine. Similarly, the manager of...
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New podcast: Stanford Computational Antitrust

I am thrilled to be introducing our new podcast. 🎙 Link: https://taplink.cc/stanfordcomputationalantitrust The Stanford Computational Antitrust podcast explores how computational tools impact antitrust analyses and procedures. Our first episode is already available on Apple Podcasts, Spotify, Stitcher, and YouTube! Another one is coming later this week…
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Reading suggestions – February 2021

This post features my latest reading suggestions based on the academic papers and press articles that I enjoyed reading in February 2021. As I tend to favor the active sharing of open-source publications, you can follow me on Twitter (@LeConcurrential) or LinkedIn (here) to access similar articles on a more regular basis. SUBSCRIBE TO THE CONCURRENTIALISTE NEWSLETTER (100% free) SUBSCRIBE TO THE STANFORD COMPUTATIONAL...
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Reading suggestions – January 2021

This post features my latest reading suggestions based on the academic papers and press articles that I enjoyed reading in January 2021. As I tend to favor the active sharing of open-source publications, you can follow me on Twitter (@LeConcurrential) or LinkedIn (here) to access similar articles on a more regular basis. SUBSCRIBE TO THE CONCURRENTIALISTE NEWSLETTER (100% free) SUBSCRIBE TO THE STANFORD COMPUTATIONAL...
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Competing with new combinations: the case of DALL·E

Introducing DALL·E In early January 2021, OpenAI introduced DALL·E, a trained neural network “that creates images from text captions for a wide range of concepts expressible in natural language.” DALL·E is a real technological breakthrough, “a 12-billion parameter version of GPT-3 trained to generate images from text descriptions, using a dataset of text-image pairs. […] It has...
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“Computational Antitrust”

I am pleased to be introducing the Computational Antitrust project at Stanford University’s CodeX Center (visit the website). The project gathers over 40 antitrust agencies and 30 scholars. Ambition Computational law is a branch of legal informatics concerned with the mechanization of legal analysis (whether done by humans or machines). Deriving from it, the “Computational Antitrust” project at...
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Reading suggestions – December 2020

This post features my latest reading suggestions based on the academic papers and press articles that I enjoyed reading in December 2020. As I tend to favor open-source publications and active sharing, you may follow me on Twitter (@LeConcurrential) or LinkedIn (here) to access similar articles on a more regular basis. SUBSCRIBE TO THE CONCURRENTIALISTE NEWSLETTER (100% free) SUBSCRIBE TO THE STANFORD COMPUTATIONAL ANTITRUST NEWSLETTER...
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