Blocking Malicious Bots With Centralized Machine Learning [Snapt, February 2022]

Title:

Blocking Malicious Bots With Centralized Machine Learning

 

Author:

Dave Blakey

 

Published:

Snapt, 22 February 2022

https://www.snapt.net/blog/blocking-malicious-bots-with-centralized-machine-learning?utm_campaign=Nova%20Bot%20Protection&utm_source=twitter&utm_medium=paidsocial&utm_content=Blog%20Post

 

From the blog article:

About a quarter of all web traffic comes not from human users but from automated bots – some good, some bad.

Neural Network Twitter Bot creates whatever delights or nightmares its fans force upon it: Do Androids dream of electrical creeps? [The Byte, March 2022]

Title:

Neural Network Twitter Bot creates wahtever delights or nightmares its fans force upon it: Do Androids dream of electrical creeps?

 

Author:

Noor Al-Sibai

 

Published:

The Byte, 21 March 2022

https://futurism.com/the-byte/neural-network-user-bot

From the article:

As their handle suggests, Twitter user and generative artist @ai_curio_bot uses neural networks to create gorgeous, trippy works of art. Per the artist’s other account, @ai_curio, they’ve created two bespoke neural networks — Looking Glass AI and Zoetrope 5 — to generate the phantasmagoric and often-hilarious pieces showcased on their account.

 

Teaching in Higher Education, 4 October 2020 - A return to Teacherbot: rethinking the development of educational technology at the University of Edinburgh

Title:

A return to Teacherbot: rethinking the development of educational technology at the University of Edinburgh

 

Authors:

Markus Roos Breibes & Michael Gallagher

 

Published:

Teaching in Higher Education, 4 October 2020

https://www.tandfonline.com/doi/full/10.1080/13562517.2020.1825373

Abstract:

In the market discourses of technological disruption, higher education institutions have routinely been positioned in deficit models and of anachronistic approaches to teaching at odds with the types of educational futures being presented by commercial organisations. Predominantly, automation technologies in the form of artificial intelligence are being promoted as the future of teaching. In this paper, on the other hand, we explore the prospects for using non-artificial intelligence automated agents in teaching and its impact on the teacher function at the University of Edinburgh. Through engagement with teachers, staff and students at the university, this research has identified use cases for bots, in what spaces they would be situated, and how they would supplement the teacher function. This paper argues that a community-driven approach combined with a sociomaterial conceptualisation can generate a shift from market discourses and to collaborative development of educational technologies.