Data Science Insider: February 3rd, 2023

In This Week’s SuperDataScience Newsletter: OpenAI Releases Tool to Spot AI-Generated Text. Whisper is the Future of ML. Data Science Slack Communities. AI Claims Earth Will Cross the Global Warming Threshold. ML Deployed to Help Identify Extraterrestrial Life. 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. --------------------------------------------------------------- [OpenAI Releases Tool to Spot AI-Generated Text]( brief: OpenAI - the research laboratory behind the AI program ChatGPT has announced this week, in a blog post, the release of a tool designed to detect whether a text has been written by AI. They warned that the tool is ‘not fully reliable’ (yet!) and explained that the new classifier tool has been trained not just with ChatGPT in mind, but instead is designed to distinguish between text written by a human and that written by a variety of AI. Currently, the classifier’s success rate is only around 26%, but OpenAI claims that it will significantly improve and argues that when used alongside other methods it could be invaluable for identifying those who are abusing the text generator. Why this is important: ChatGPT has been a runaway success but has attracted significant amounts of controversy about how open it is to abuse (particularly by students). This release appears to be OpenAI’s attempt to mitigate the criticisms. [Click here to learn more!]( [Whisper is the Future of ML]( brief: This fascinating long-form article by the New Yorker argues that despite ChatGPT grabbing all of the recent headlines, it is OpenAI’s Whisper (an open-source speech-transcription program) that reveals where the future of ML lies. OpenAI states on its website that “We’ve trained and are open-sourcing a neural net called Whisper that approaches human level robustness and accuracy on English speech recognition.” This bold claim appears to have gone somewhat under the radar but this article argues that it is simultaneously incredibly simple and exceedingly sophisticated and is at times “capable of superhuman performance.” It also contends that the open-source nature of the program represents a wider transformation of the industry. Why this is important: The article argues that it is availability, rather than intelligence, which is the standout feature of modern ML. [Click here to read on!]( [Data Science Slack Communities]( In brief: Slack data science communities can be an informal yet educational way to network and develop your talents. They aim to promote personal development and entrepreneurial skills among students and career data scientists and have thousands of members. Virtual communities have been a thing for a number of years but their popularity really soared during the pandemic when people were unable to meet and interact in person. These groups have continued to flourish and Slack offers a real gold mine of inspiring peers with whom you can share similar data science joys and challenges. This article by Analytics Insight offers ten communities, from Datatalks.Club to Riga DS Club, which you should consider joining. Why this is important: No matter what stage you’re at in your data science career support and interaction are always key to ensuring you develop as much as possible. [Click here to discover more!]( [AI Claims Earth Will Cross the Global Warming Threshold]( In brief: A study by Standford University has found that our planet is set to exceed 1.5 Celsius warming within the next ten to fifteen years. The study used an AI to predict warming timelines and includes new evidence that global warming is primed to reach 1.5 degrees Celsius (2.7 Fahrenheit) above pre-industrial averages in the early 2030s. Worryingly these figures remain the same regardless of how much greenhouse gas emissions rise or fall in the coming decade. Researchers trained a neural network to analyse a wide variety of temperature observations from across the planet alongside past measurements of the globe’s temperature. It then asked the AI to determine timelines for given temperature thresholds. Why this is important: These temperature benchmarks have been identified as crisis points in the United Nations Paris agreement. By discovering when we are likely to cross them there is some hope that we may be able to mitigate or slow down the damage that we’ve already done. [Click here to see the full picture!]( [ML Deployed to Help Identify Extraterrestrial Life]( In brief: A study led by an undergraduate student at the University of Toronto alongside researchers from the SETI (search for extraterrestrial intelligence) Institute, has revealed an ML method that they believe could aid in the filtering out of interference. This would allow scientists to more efficiently identify unusual radio signals from space, contributing to the ongoing search for extraterrestrial intelligence. SETI programs have traditionally used radio telescopes in order to detect clear-cut artificial signals coming from the skies. However, this search is hindered by interference from human tech, which has the ability to generate false positive identifications that are time-consuming to filter out from large data sets. The team developed deep learning models using ML library TensorFlow and Python library Keras. Why this is important: The tool initially identified around 3 million signals of interest, which was then filtered down to eight previously undetected signals of interest. The researchers propose that their method could be applied to other big datasets to accelerate SETI. [Click here to find out more!]( [Super Data Science podcast]( this week's Super Data Science Podcast, Kirill Eremenko and Hadelin de Ponteves join Jon Korhn for an awesome ML primer that will enlighten even experienced practitioners. The popular data science instructors also introduce their latest course: Machine Learning in Python: Level 1. [Click here to find out more!]( --------------------------------------------------------------- What is the Data Science Insider? 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