This whitepaper offers an overview of the ethical considerations surrounding research into or with large language models (LLMs). As LLMs become more integrated into widely used applications, their societal impact increases, bringing important ethical questions to the forefront. With a growing body of work examining the ethical development, deployment, and use of LLMs, this whitepaper provides a comprehensive and practical guide to best practices, designed to help those in research and in industry to uphold the highest ethical standards in their work.

Blockchain technology and Artificial Intelligence (AI) have emerged as transformative forces in their respective domains. This paper explores synergies and challenges between these two technologies. Our research analyses the biggest projects combining blockchain and AI, based on market capitalization, and derives a novel framework to categorize contemporary and future use cases. Despite the theoretical compatibility, current real-world applications combining blockchain and AI remain in their infancy.

Intel Movidius VPU enable demanding computer vision and AI workloads with efficiency. By coupling highly parallel programmable compute with workload-specific AI hardware acceleration in a unique architecture that minimizes data movement, Movidius VPUs achieve a balance of power efficiency, and compute performance. But the AI models from customers are usually generally built and not designed for a specific hardware as fig.1 left shows. Due to the different designs of various AI accelerators, general models can't fully utilize hardware's capability. That gives the chance to design better models for hardware: higher fps at same accuracy level or higher accuracy at same fps. However, even for hardware specialists, the design space of possible networks is still extremely large and impossible for handcrafting.

Since its release in late November, ChatGPT has taken the world by storm. The chatbot's advanced AI abilities allow it to do tasks completely on its own, such as composing essays, emails and poems, writing and debugging code, and even passing exams. Now that a chatbot can do what humans do so well in a matter of seconds, what does that mean for our future? If you have had the chance to chat with the AI chatbot, you were probably impressed with how much it can understand and its ability to respond in a conversational manner. However, the chatbot is capable of doing much more, and its technical capabilities are tested every day.

Everyone has been talking about MLOps for over a year now. I looked around for how the lifecycle and processes have evolved. The discipline of seeking insight from data has been around for 25 years. Back then, it was known as data mining. In this article, I present a survey of the ML lifecycle process and conclude with my take on it.

The growing number of organizations creating and deploying machine learning solutions raises concerns as to their intrinsic security, argues the NCC Group in a recent whitepaper. The NCC Group's whitepaper provides a classification of attacks that may be carried through against machine learning systems, including examples based on popular libraries such as SciKit-Learn, Keras, PyTorch and TensorFlow platforms. Although the various mechanisms that allow this are to some extent documented, we contend that the security implications of this behaviour are not well-understood in the broader ML community. According to the NCC Groups, ML systems are subject to specific forms of attacks in addition to more traditional attacks that may attempt to exploit infrastructure or applications bugs, or other kind of issues. A first vector of risk is associated to the fact that many ML models contain code that is executed when the model is loaded or when a particular condition is met, such as a given output class is predicted.

Magic and hype: Two words that are frequently applied to artificial intelligence. Today, solutions leveraging the power of artificial intelligence are already paying off in robotics, automation, and manufacturing. AI is powering predictive systems, increasing the capabilities of robots, improving the precision of machine vision, and helping businesses optimize their processes to improve quality and reduce waste. This Association for Advancing Automation (A3) whitepaper will examine six application spaces where AI is already taking hold in automation and manufacturing. We will discuss how the technology is making a difference and what you should consider in your enterprise's AI journey.

Sea Machines has released a whitepaper highlighting how AI-based navigation and autonomy technology developed for commercial maritime platforms such as USVs (uncrewed surface vessels) can also be used to solve the challenges faced by government maritime organizations. Adapting these commercial technologies can save governments from having to undergo highly expensive and time-consuming development cycles that start from scratch. To find out more about how commercial maritime AI solutions can be adapted to the needs of government organizations, download the full whitepaper here.

Samsung Electronics today released the second edition of its private 5G networks whitepaper, highlighting the architectures, features and benefits of private 5G networks for industrial scenarios--such as smart factories, smart hospitals, smart logistics and transportation, among others. With the growing interest in private networks, Samsung explores how enterprises can successfully deploy private 5G networks to meet business goals and service demands. The whitepaper outlines various architectural options for building private networks that enable 5G services -- such as Enhanced Mobile Broadband (eMBB), Ultra-Reliable Low Latency Communications (URLLC) and Massive Machine Type Communications (mMTC) -- which can bring new innovation to a range of sectors rapidly transitioning to Industry 4.0. The paper spotlights Samsung's complete set of private 5G network solutions, which enable enterprises to simplify network deployment and operation. With a portfolio and capability to build highly reliable private 5G networks, Samsung offers solutions for small, medium to large-scale enterprises.

Technological advancements continue to create new opportunities in Ontario's electricity sector, and many businesses are turning to artificial intelligence (AI) to enhance their operations. If you're an organization that is currently using AI, or exploring the use of it, the IESO wants to hear from you. By taking a short survey, you can help inform a whitepaper the IESO is developing that will provide insight into the opportunities AI can provide for Ontario's electricity market participants and ratepayers. The whitepaper is the latest in the Innovation and Sector Evolution White Paper Series, and an overview was presented to stakeholders at a webinar held yesterday. The survey is a key first step that will provide a foundational understanding of where various segments of Ontario's electricity sector are in their AI journey, and where they expect to be in five years.