Data Science Insider: March 17th, 2023

In This Week’s SuperDataScience Newsletter: Microsoft Introduces AI Co-Pilot to 365 Suite. UK to Invest £900m in AI Supercomputer. Self-Service Analytics Could Boost Business Success. OpenAI's GPT-4: Revolutionising Language Processing. PyTorch 2.0 Released. 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. --------------------------------------------------------------- [Microsoft Introduces AI Co-Pilot to 365 Suite]( brief: Microsoft is adding AI-powered "co-pilot" features to its 365 suite of apps to offer suggestions and assist users in Word, Outlook, and Teams. The system will use natural language processing to identify key phrases and provide tailored recommendations based on user behavior. Users will be able to type naturally while the co-pilot offers possible next steps, with voice command support also included. Microsoft is testing the feature with a small group of users and aims to roll it out more widely in the coming months. The co-pilot tools are intended to increase productivity and streamline workflow by using AI to provide real-time assistance and help users to complete tasks more efficiently. Why this is important: As regular readers of the SuperDataScience newsletter will be aware, this development follows on quickly from Microsoft’s introduction of Chat-GPT like features to its Bing search engine, signaling a firm commitment to making AI more widespread and competing with OpenAI. [Click here to learn more!]( [UK to Invest £900m in AI Supercomputer]( brief: The UK government is planning to invest £900m in a new supercomputer that will be used to develop the country's own version of the AI language model, GPT. The project was announced by Chancellor Jeremy Hunt and aims to reduce the UK's reliance on American technology and to enable the country and its developers to be able to compete with the likes of China in the development of AI. The government believes that building a British GPT will provide significant benefits in areas such as healthcare, climate change and national security. The supercomputer will be built in collaboration with the private sector, and it is hoped that the project will create thousands of new jobs across the country. Why this is important: The UK's commitment to developing an AI language model that will rival GPT, may ultimately allow them to provide benefits in areas such as healthcare, climate change, and national security. [Click here to read on!]( [Self-Service Analytics Could Boost Business Success]( In brief: Although we will always bang the drum for professional data professionals here at SuperDataScience, a new report by Dresner Advisory Services has found that self-service data analytics can provide businesses with more effective insights. The study found that companies using self-service analytics were more likely to achieve high levels of success than those relying solely on traditional analytics methods. Self-service analytics allows employees to access and analyse data themselves, without the need for technical expertise or IT support. This enables them to make quicker decisions and identify trends and opportunities more efficiently. The report also highlighted the need for companies to invest in employee training and adopt a data-driven culture to fully benefit from self-service analytics. Why this is important: Self-service data analytics provides companies with more effective insights, enabling them to make quicker decisions and identify trends and opportunities more efficiently. This can ultimately lead to increased success and competitive advantage and should be considered being used alongside the services of data scientists. . [Click here to discover more!]( [OpenAI's GPT-4: Revolutionising Language Processing]( In brief: The development of GPT-4, the next iteration of OpenAI's Generative Pre-trained Transformer language model, could be set to revolutionise natural language processing. GPT-4 has just been announced and is expected to have 100 trillion parameters, compared to GPT-3's 175 billion, which would significantly improve its ability to generate text that resembles human writing. This would have applications in fields such as virtual assistants, content creation, and language translation. GPT-4 is also expected to improve its understanding of context and nuances of language, which could help reduce the biases found in previous AI language models. However, GPT-4's development raises ethical concerns, including the potential misuse of AI-generated content, highlighting the need for ethical AI development practices. Why this is important: The development of GPT-4 could significantly improve natural language processing capabilities but also highlights the need for responsible AI development practices to mitigate potential misuse of AI-generated content. [Click here to see the full picture!]( [PyTorch 2.0 Released]( In brief: PyTorch 2.0, the latest version of Facebook's open-source ML framework, was finally released this week after a beta version has been available in preview since December 2022. It features new tools and enhancements, including a just-in-time compiler and an improved distributed training library. PyTorch 2.0 also has support for tensor operators on graphics processing units (GPUs) and central processing units (CPUs), and the ability to scale models using hybrid parallelism. It has already been adopted by several companies and organisations, including Tesla, Toyota, and Google. PyTorch is a popular choice for ML development due to its simplicity and ease of use, and its latest version is expected to increase its appeal to developers in the field. Why this is important: PyTorch 2.0's new tools and enhancements could make it more appealing to developers working in ML, due to its simplicity and ease of use. Its support for tensor operators on GPUs and CPUs and its ability to scale models using hybrid parallelism is expected to improve its performance and make it more versatile for use in various industries. [Click here to find out more!]( [Super Data Science podcast]( this week's Super Data Science Podcast, Chip Huyen, co-founder of Claypot AI and author of O'Reilly's best-selling "Designing Machine Learning Systems", shares her expertise on designing production-ready machine learning applications, the importance of iteration in real-world deployment, and the critical role of real-time machine learning in various applications. Technical listeners like data scientists and machine learning engineers will definitely enjoy this one! [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! 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