Data Science Insider: December 29th , 2023

In This Week’s SuperDataScience Newsletter: NY Times Sues OpenAI. Expert Tips for Optimal Data Pipelines. GPU Revolution: Transforming Data Analytics Speed. Newsquest Elevates Journalism with AI Assistant. Unlock 2024 Success. 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. --------------------------------------------------------------- [NY Times Sues OpenAI]( brief: The New York Times is taking legal action against OpenAI and Microsoft, alleging copyright infringement that led to the improper training of ChatGPT. The lawsuit asserts that millions of New York Times articles were used without permission, enhancing ChatGPT's capabilities to compete with the newspaper as an information source. The complaint highlights instances where ChatGPT generates verbatim excerpts from New York Times articles, impacting the newspaper's subscription revenue and advertising clicks. With Microsoft investing over $10 billion in OpenAI, the lawsuit underscores the legal challenges surrounding AI development and the complexities of copyright issues in the digital era as well as the ethical and legal considerations surrounding the use of data, particularly when training large language models like ChatGPT. Why this is important: Understanding the potential copyright implications of data sources is crucial in developing responsible and legally compliant AI systems. It highlights the need for data scientists to be vigilant in ensuring that training datasets adhere to copyright regulations, fostering a responsible and ethical approach to AI development. [Click here to learn more!]( [Expert Tips for Optimal Data Pipelines]( brief: In this insightful Towards Data Science article, Michael Berk shares eight crucial tips for optimizing Apache Spark based on his extensive experience assisting large retail organizations with data and ML pipelines at Databricks. The tips cover various aspects, including conceptualizing Spark as a grocery store analogy, understanding lazy evaluation, optimizing pipelines efficiently, addressing disk spill issues, leveraging SQL syntax, using glob filters for efficient data file reading, employing reduce with DataFrame.union to minimize planning phases, and recognizing the value of large language models like ChatGPT for distilling complex information. For data scientists, these insights offer a comprehensive guide to enhance Spark performance, emphasizing efficient coding practices and strategic optimization approaches. Why this is important: From optimizing code execution with lazy evaluation awareness to efficiently managing disk spill problems, these insights empower data scientists to design and execute robust, scalable, and cost-effective data and machine learning pipelines. [Click here to read on!]( [GPU Revolution: Transforming Data Analytics Speed]( In brief: In this article, experts delve into the challenges hindering the transformative potential of AI in data analytics, emphasizing the time-consuming nature of queries and data access. William Benton, NVIDIA's Principal Product Architect, alongside Deborah Leff from SQream and data scientist Tianhui “Michael” Li, discuss overcoming obstacles in enterprise-level data analytics. They highlight the revolutionary impact of powerful GPUs in accelerating analytics processes, bringing about a paradigm shift. By harnessing GPU capabilities, organizations can significantly reduce the time it takes for the entire analytics workflow, unlocking new levels of insight and democratizing access to accelerated data processing. This acceleration not only enhances data science workflows but also transforms decision-making across the organization. Why this is important: The article emphasizes how the integration of GPUs with CPUs can revolutionize data analytics, enabling faster queries and real-time insights. This acceleration not only optimizes individual steps but also enhances communication and feedback loops, allowing data scientists to work more creatively and efficiently. [Click here to discover more!]( [Newsquest Elevates Journalism with AI Assistant]( In brief: Berrow’s Worcester Journal, the world's oldest surviving newspaper, is embracing AI to enhance journalism. As part of Newsquest, the UK's second-largest regional news publisher, eight "AI-assisted" reporters have been employed in the past year. These reporters use an in-house copywriting tool based on ChatGPT to convert mundane data, like local council minutes, into concise news reports, enabling traditional reporters to focus on in-depth coverage. Newsquest's CEO cites the AI system's value during breaking news events, allowing human reporters to delve into investigative work. Despite concerns, Newsquest emphasizes that AI serves as a tool, with human oversight maintaining accuracy. This trend reflects a broader shift toward AI integration in newsrooms, offering efficiency without compromising journalistic integrity. Why this is important: This story when combined with the New York Times lawsuit stoory underscores the need for collaboration between data scientists and journalists to ensure accurate, reliable, and unbiased reporting with ethical data. As the industry evolves, data scientists will continue to contribute to the refinement of AI applications, shaping the future of journalism. [Click here to see the full picture!]( [Unlock 2024 Success]( In brief: In the pursuit of advancing data science expertise in the upcoming year, KDnuggets has curated a selection of top-tier resources, bootcamps, and courses. Partnering with Springboard, the offerings aim to elevate the data science journey. Notable resources include Kaggle for AI-centric competitions, "Learn Python The Hard Way" for Python proficiency, and "R for Data Science" to navigate R's significance. Bootcamps, particularly Springboard, emerge as a dedicated path with proven outcomes, mentorship, and a significant job guarantee. Courses from platforms like Datacamp and Udemy provide structured learning for those seeking a middle ground between bootcamps and free resources. The recommended platforms and courses cater to different learning preferences and skill levels, ensuring a comprehensive approach to mastering data science. Why this is important: For those looking to boost their expertise in 2024 these resources alongside those offered by SuperDataScience will help jumpstart your new year. [Click here to see the full picture!]( [Super Data Science podcast]( In this week's [Super Data Science Podcast]( episode, the founder of Quickchat AI, Piotr Grudzień, believes the key to any successful AI platform is to ensure it can be tailored to a company’s specific needs. He speaks to host Jon Krohn about helping clients generate realistic and satisfying conversations that help their customer base find what they need quickly. [Click here to find out more!]( --------------------------------------------------------------- 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. Want to take your data science skills to the next level? Check out the [SuperDataScience platform]( and sign up for membership today! Know someone who would benefit from getting The Data Science Insider? Send them [this link to sign up.]( # # If you wish to stop receiving our emails or change your subscription options, please [Manage Your Subscription]( SuperDataScience Pty Ltd (ABN 91 617 928 131), 15 Macleay Crescent, Pacific Paradise, QLD 4564, Australia