Data Science Insider: September 15th, 2023

In This Week’s SuperDataScience Newsletter: Tech Titans Discuss AI Regulation. Kafka: The Evolving Data Lake. Mastering Sentiment Analysis with NLTK and Altair. Data Science Certifications Are Career Boosters. Watchdog Claims AI Fuels Child Abuse Content. 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. --------------------------------------------------------------- [Tech Titans Discuss AI Regulation]( brief: Tesla CEO Elon Musk, along with tech leaders such as 'Mark Zuckerberg (Meta), Sundar Pichai (Google), Bill Gates (former Microsoft CEO), and Satya Nadella (current Microsoft CEO), have convened in a closed-door meeting with US lawmakers to discuss the regulation of AI. Senate Majority Leader Chuck Schumer organized the forum, which also included civil rights advocates. The power of AI, with its potential benefits and risks, has been a global political concern. Sam Altman, CEO of OpenAI, emphasized the need for collaboration between tech companies and the government to prevent AI-related issues, like mass job displacement and misinformation. Musk advocated for establishing a regulatory body for AI. While participants acknowledged the government's regulatory role, crafting legislation remains a complex challenge. Why this is important: Understanding the call for AI regulation is vital for data scientists because it highlights the growing societal and political implications of AI technology. Collaboration with regulators and responsible AI development is crucial to ensure AI's positive impact and mitigate potential risks. [Click here to learn more!]( [Kafka: The Evolving Data Lake]( brief: In these SuperDataScience newsletters, we have previously discussed the transformative shift in data management towards data lakes. This article builds on that by examining how integrating computer engines like Apache Spark, Trino, or ClickHouse, can make data lakes become 'data lakehouses,' enabling efficient data storage and processing. Apache Kafka, a popular event streaming platform, is traditionally used to store recent data before transferring it to data lakes. However, there is evidence suggesting that it is evolving into a new form of data lake. The article explores why Kafka is well-suited for this and also discusses how Kafka can serve as a single source of truth, simplifying data architecture and benefiting from its rich ecosystem for data ingestion and processing. Why this is important: Understanding how Kafka can serve as a data lake and its potential advantages, such as cost-efficiency and real-time data processing, can inform data storage and processing decisions. Additionally, knowledge of Kafka's limitations and the possibility of hybrid approaches with existing data lake frameworks can help us data scientists design effective data architectures. [Click here to read on!]( [Mastering Sentiment Analysis with NLTK and Altair]( In brief: In this Towards Data Science article, the author demonstrates the process of building a Sentiment Analysis report using NLTK and Altair. They start by utilizing the UCI News dataset to calculate the positivity of news headlines and create an interactive report. The article emphasizes the importance of analysing unstructured data for valuable insights and then proceeds to explain the steps involved in sentiment analysis. They use the Vader Sentiment Intensity Analyzer from NLTK to classify headlines, showcasing its lexicon-based approach's speed and accuracy. The author also visualizes the sentiment analysis results using Altair, providing interactive visualizations to enhance data exploration. Finally, they stress the significance of effectively communicating data analysis results and introduce the use of Datapane to create shareable reports. Why this is important: Building interactive visualisations using libraries like Altair empowers viewers to explore data directly, enhancing trust in analysis results. Moreover, effectively communicating results through well-structured reports with context is crucial to ensuring that stakeholders understand and utilize the findings for informed decision-making. [Click here to discover more!]( [Data Science Certifications Are Career Boosters]( In brief: The field of data science is experiencing tremendous growth, attracting both aspiring professionals and career switchers. Short courses and data science certifications, such as those offered by us here at SuperDataScience, have become popular options for gaining expertise in this sphere. This Data Science Central article explores the benefits of earning data science certifications, including skill validation, networking opportunities, specialization, career advancement, and competitive pay. It also highlights factors to consider when choosing a certification, such as syllabus complexity, study materials, duration, prerequisite skills, and course cost. The article concludes by listing top data science certification choices for 2023, emphasizing the growing demand for data science professionals and the importance of staying updated in this rapidly evolving industry. Why this is important: Certifications validate data scientists’ skills and expertise, making them more competitive in the job market. Networking opportunities provided by certification programs can lead to valuable insights and collaborations and specialization through certifications allows data scientists to focus on their preferred areas within the field. [Click here to see the full picture!]( [Watchdog Claims AI Fuels Child Abuse Content]( In brief: The Internet Watch Foundation has warned that pedophiles are using freely available open-source AI software to create child sexual abuse material (CSAM). The watchdog claims that offenders are discussing how to manipulate images of celebrity children, publicly available images, or known victims to produce new illegal content. These discussions involve refining basic image generation models with CSAM images to create more realistic and disturbing images. Law enforcement and child safety experts fear that AI-generated CSAM, which can be photorealistic, will make it harder to identify and help real-life victims, potentially worsening child sexual abuse online. Andrew Rogoyski, said: “Open source AI is important to democratising AI […] The downside is that people will misuse the technology.” Why this is important: Data scientists should be aware of how AI, particularly open-source AI, can be misused for harmful purposes. Understanding these cases is crucial to developing ethical AI and ensuring that data-driven technologies are not misappropriated for illegal activities. The use of AI in the creation of CSAM underscores the need for responsible AI development, robust regulations, and proactive measures to combat misuse. [Click here to find out more!]( [Super Data Science podcast]( this week's [Super Data Science Podcast]( episode, Meta’s AI Research Scientist Thomas Scialom gives us behind-the-scenes insights into developing Llama 2 and what’s in the works for Llama 3. With host Jon Krohn, he discusses the future of Artificial General Intelligence, why the Galactica science-focused LLM was taken down, and what he learned from it. [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