Data Science Insider: March 3rd, 2023

In This Week’s SuperDataScience Newsletter: Elon Musk Developing "Building-Based AI" to Compete with ChatGPT. Retailers Lag Behind in Advanced Analytics. 10 Ways ChatGPT Can Help You Streamline Your Workflow. Researchers Develop New Neural Network for Faster Processing. Italian Voice Actors Strike Against AI Use in Dubbing. 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. --------------------------------------------------------------- [Elon Musk Developing "Building-Based AI" to Compete with ChatGPT]( brief: Tech billionaire Elon Musk has revealed that he is working on a new type of AI called “Building-Based AI” that will be able to compete with the runaway success of OpenAI’s ChatGPT. Musk claims that his AI will be able to create entire websites, videos, and games automatically. However, some experts have criticised the idea, saying that it could lead to the mass production of low-quality content and that human creativity cannot be fully replaced by machines. Musk, who has previously warned about the potential dangers of AI, has said that his new project is aimed at creating a “more benign AI” that can be used for good purposes. Why this is important: As we’ve seen over the past few years here at SuperDataScience, Elon Musk’s claims don’t always come to fruition. However, this has the potential to lead to advances in natural language processing, despite raising concerns about AI safety and ethics. [Click here to learn more!]( [Retailers Lag Behind in Advanced Analytics]( brief: Despite being told for years that advanced analytics can provide better answers to almost every business question, many retail companies have not taken advantage of the opportunity to do so. Walmart, Amazon and other leading retailers are operating at the forefront of the analytics frontier, making many important decisions based on real-time and historical data. However, most other retail companies are still using basic tools which track where they have been rather than where they should be going. During the pandemic, McKinsey estimates the 25 top-performing retailers, most of whom are digital leaders, were 83% more profitable than laggards and took home more than 90% of the sector’s gains in market capitalisation. Why this is important: Retail companies that fail to implement advanced analytics are missing out on potential profits. Issues with culture, organization, people, processes, systems, and data are preventing some organisations from making the leap forward. [Click here to read on!]( [10 Ways ChatGPT Can Help You Streamline Your Workflow]( In brief: News about ChatGPT may be beginning to become a bit tiresome but there’s no doubt that it has revolutionised the way data scientists approach problem-solving. This article by Analytics Insight lists ten ways in which it can aid data scientists, including generating synthetic data, optimising models, analysing sentiment, and identifying anomalies. ChatGPT can also aid in natural language processing tasks such as text classification and summarisation. The tool can even generate code and help with data visualisation. By leveraging its power, data scientists can streamline their workflow and focus on more complex tasks whilst leaving mundane tasks to the model, showcasing the potential of AI in the field of data science. Why this is important: It is becoming increasingly clear that ChatGPT is a powerful tool which can help data scientists save time and improve the accuracy of their models. [Click here to discover more!]( [Researchers Develop New Neural Network for Faster Processing]( In brief: Researchers from MIT and the University of California, Berkeley, have developed a new type of neural network that combines two types of AI models to achieve faster and more accurate processing. By merging a transformer model and an optical neural network, the researchers created a system that can perform complex image recognition tasks while reducing computation time and power consumption. The transformer model was used to process text data while the optical neural network was used for image processing, and the two models were connected to achieve seamless processing of both text and image data. The new system could have significant implications for the development of more efficient and effective AI systems in the future. Why this is important: The combination of transformer models and optical neural networks is set to disrupt for the future in a wide range of industries and applications. Check out our SuperDataScience platform for top courses that can help you stay on top of the game! [Click here to see the full picture!]( [Italian Voice Actors Strike Against AI Use in Dubbing]( In brief: Italian voice actors have launched a strike against the use of AI in the dubbing process, citing concerns that the technology is affecting their working conditions. The voice actors' union argues that the use of AI-generated voices is being employed to cut costs and that the technology cannot replace human actors. The voice actors fear that AI dubbing will negatively impact the quality of their work and job opportunities, saying: “current production rhythms are not conducive to [good] quality of work and of life.” The strike, which began on March 1st, has disrupted the dubbing of movies and TV shows, leading to some channels airing content in its original language. The union has not yet announced the strike’s duration. Why this is important: In these newsletters, we’ve seen many times how automation threatens human workers. These voice actors are not taking this lying down! It will be interesting to observe how the increasing numbers of workers who now have to compete against AI will choose to act. [Click here to find out more!]( [Super Data Science podcast]( this week's Super Data Science Podcast, data engineering educator Andreas Kretz joins Jon Krohn for a 1-hour primer that covers everything you need to know about the most in-demand role in data. From skills to tools, problem-solving processes and more, growing your knowledge of data engineering only improves your marketability, so tune in today if you're ready to future-proof your data career. [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