Data Science Insider: December 3rd, 2021

In This Week’s SuperDataScience Newsletter: DeepMind and AI Lead to Mathematical Breakthrough. Python to Rival JavaScript for Web Applications. Blockchain and Data Science. Timnit Gebru Starts Her Own AI Research Centre. Twitch To Use ML to Detect People Evading Bans. Cheers, - The SuperDataScience Team P.S. Have friends and colleagues who could benefit from these weekly updates? Send them to [this link]( to subscribe to the Data Science Insider. --------------------------------------------------------------- [DeepMind and AI Lead to Mathematical Breakthrough]( brief: Scientists have used AI to suggest and prove new mathematical theorems for the first time. The potential breakthrough came in a collaboration between mathematicians who specialise in pure mathematics at the universities of Oxford and Sydney, alongside Google-owned DeepMind. Their work examined knot theory and representation theory, areas of "pure mathematics" which typically depend on human intuition for breakthroughs. In a paper first published in the journal Nature, researchers have explained how DeepMind was also able to uncover patterns and connections in the advanced mathematical fields of knot theory and representation theory. Mathematicians at the University of Oxford used AI to discover a surprising connection between algebraic and geometric invariant knots, establishing a completely new theorem in the field. What sets DeepMind’s work apart, is its detection of the existence of patterns in mathematics with supervised learning — and giving insight into these patterns with attribution techniques from AI. Why this is important: This is the latest in a series of breakthroughs for DeepMind, which has repeatedly been able to crack problems that require analysing an enormous amount of data and computation, such as learning how to play computer games better than humans can, or figuring out how proteins can be folded. [Click here to sign up!]( [Python to Rival JavaScript for Web Applications]( brief: A new project has been announced which will enable the Python programming language to run within web browsers with the help of WebAssembly. The CPython on WASM project, which will build the default and most popular implementation of the Python language written in C, is being developed by Berkeley-based software developer Ethan Smith. According to this article in The Register, the project was created with the help of core Python developer Christian Heimes, and could make Python a viable alternative to JavaScript, at least for some web applications. WebAssembly has become hugely popular thanks to its promise of bringing the performance of native applications to the web, to a level that isn’t possible with JavaScript. Currently, the goal of the project – to bring Python to the browser through WebAssembly’s Emscripten compiler – focuses on enabling the use case, rather than performance. Why this is important: The project marks a step closer to Heimes’ goal of making the web a supported platform for CPython, just like Windows or macOS. The announcement follows another project which debuted in April, called Pyodide, which also enables Python code to run in a browser. [Click here to read on!]( [Blockchain and Data Science]( In brief: Blockchain technology is a hot topic nowadays, especially with the recent boom in decentralised finance, the exponential growth of Bitcoin and other cryptocurrencies, and the ongoing NFT craze (it was announced this week that NFT is Collins Dictionary’s word of the year). From a Data Scientist’s perspective, blockchains are also an exciting source of high-quality data that can be used to tackle a wide range of interesting problems using statistics and ML. In contrast to traditional data sources (e.g., centrally controlled corporate databases), blockchains by design provide several benefits that are important for Data Science applications, This Analytics Insight article argues that blockchain will be the next big thing for data science and insists that blockchain will improve data science by allowing data traceability, allowing for real-time analysis, ensuring the accuracy of data, making data sharing less difficult, ensuring trust, enhancing data integrity, encoded transactions and data lakes. Why this is important: Blockchain is something that we will all be aware of but have perhaps not considered how it’s likely to interact with data science. This article gives us another insight into the direction our industry may take in the near future. [Click here to discover more!]( [Timnit Gebru Starts Her Own AI Research Centre]( In brief: Exactly one year after Timnit Gebru was dismissed from her post at Google, the prominent expert in artificial intelligence ethics announced plans for a new AI research institute, designed to be an independent group committed to diverse points of view and preventing harm. Gebru has lined up funding from the Ford, MacArthur, Kapor Center, Rockefeller, and Open Society foundations for the center — called DAIR, or Distributed AI Research — and plans to hire five researchers over the next year. The group’s first research fellow, Raesetje Sefala, is based in South Africa and studies how computer vision algorithms and satellite images can be used to track the legacy of spatial apartheid — the segregation of minority groups in certain areas. Gebru also wants her group to serve as a resource to advise other organisations on AI programs and she’d like to set up a fellowship for people who are affected by AI. Why this is important: Gebru’s effort is an attempt to forge a research group outside of corporate or military influence that tries to prevent harm from AI systems by focusing on global perspectives and underrepresented groups. As the development of AI systems has boomed, the field has become dominated by large companies with access to the vast amounts of data and computing power used to build algorithms. Gebru, and other researchers and activists, argue that the trend is making the area less accessible, especially to groups at risk of being hurt by AI. [Click here to see the full picture!]( [Twitch To Use ML to Detect People Evading Bans]( In brief: Twitch is introducing a new ML feature to help streamers protect their channels from people attempting to avoid bans. Dubbed "Suspicious User Detection," the tool will automatically flag individuals it suspects may be "likely" or "possible" ban dodgers. In cases involving the former, Twitch will prevent any messages they send from showing up in chat. It will also identify those individuals for streamers and any mods helping them with their channel. At that point, they can decide if they want to ban that person. By default, possible repeat trolls can send messages in chat, but they too will be flagged by the system. "The tool is powered by a machine learning model that takes a number of signals into account […] and compares that data against accounts previously banned from a Creator's channel to assess the likelihood the account is evading a previous channel-level ban," a Twitch spokesperson said. Why this is important: While Twitch plans to turn on Suspicious User Detection for everyone, the tool won't automatically ban users for streamers. That's by design because it's impossible to create a ML tool that is 100% accurate. The introduction of the tool follows a summer in which Twitch struggled to contain "hate raids." The attacks saw individuals use thousands of bots to spam channels with hateful language. Hate raids became such a frequent feature that some creators walked away from Twitch for a day in protest of the company's lack of action. [Click here to find out more!]( [Super Data Science podcast]( In this week's [Super Data Science Podcast](, Peter Bailis joins us to talk about his work in automating analytics for large amounts of data and making commercial problem solving more efficient. --------------------------------------------------------------- What is the Data Science Insider? This email is a briefing of the week's most disruptive, interesting, and useful resources curated by the SuperDataScience team for Data Scientists who want to take their careers to the next level. 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