We discuss the challenges and propose research directions for using AI to revolutionize the development of high-performance computing (HPC) software. AI technologies, in particular large language models, have transformed every aspect of software development. For its part, HPC software is recognized as a highly specialized scientific field of its own. We discuss the challenges associated with leveraging state-of-the-art AI technologies to develop such a unique and niche class of software and outline our research directions in the two US Department of Energy--funded projects for advancing HPC Software via AI: Ellora and Durban.

Online reviews help people make better decisions. Review platforms usually depend on typed input, where leaving a good review requires significant effort because users must carefully organize and articulate their thoughts. This may discourage users from leaving comprehensive and high-quality reviews, especially when they are on the go. To address this challenge, we developed Vocalizer, a mobile application that enables users to provide reviews through voice input, with enhancements from a large language model (LLM). In a longitudinal study, we analysed user interactions with the app, focusing on AI-driven features that help refine and improve reviews. Our findings show that users frequently utilized the AI agent to add more detailed information to their reviews. We also show how interactive AI features can improve users self-efficacy and willingness to share reviews online. Finally, we discuss the opportunities and challenges of integrating AI assistance into review-writing systems.

In video game design, audio (both environmental background music and object sound effects) play a critical role. Sounds are typically pre-created assets designed for specific locations or objects in a game. However, user-generated content is becoming increasingly popular in modern games (e.g. building custom environments or crafting unique objects). Since the possibilities are virtually limitless, it is impossible for game creators to pre-create audio for user-generated content. We explore the use of generative artificial intelligence to create music and sound effects on-the-fly based on user-generated content. We investigate two avenues for audio generation: 1) text-to-audio: using a text description of user-generated content as input to the audio generator, and 2) image-to-audio: using a rendering of the created environment or object as input to an image-to-text generator, then piping the resulting text description into the audio generator. In this paper we discuss ethical implications of using generative artificial intelligence for user-generated content and highlight two prototype games where audio is generated for user-created environments and objects.

As climate change issues become more pressing, their impact in Africa calls for urgent, innovative solutions tailored to the continent's unique challenges. While Artificial Intelligence (AI) emerges as a critical and valuable tool for climate change adaptation and mitigation, its effectiveness and potential are contingent upon overcoming significant challenges such as data scarcity, infrastructure gaps, and limited local AI development. This position paper explores the role of AI in climate change adaptation and mitigation in Africa. It advocates for a collaborative approach to build capacity, develop open-source data repositories, and create context-aware, robust AI-driven climate solutions that are culturally and contextually relevant.

The devastating 6.8-magnitude earthquake in Al Haouz, Morocco in 2023 prompted critical reflections on global disaster management strategies, resulting in a post-disaster hackathon, using artificial intelligence (AI) to improve disaster preparedness, response, and recovery. This paper provides (i) a comprehensive literature review, (ii) an overview of winning projects, (iii) key insights and challenges, namely real-time open-source data, data scarcity, and interdisciplinary collaboration barriers, and (iv) a community-call for further action.

Imagine if you could walk into a supermarket, grab whatever you need, and just walk out. Your account would automatically be charged and an itemized bill will be sent your way. Amazon Go stores are living examples of such a utopian dream. You can learn more about Amazon Go from the video below. And that reality is being powered by artificial intelligence.

March 8, 2023It's no secret that companies that integrate artificial intelligence (AI) into their business practices have a leg up when it comes to understanding customer needs and developing new products. For insurers, using AI could help deliver services seamlessly while breaking down silos internally and externally. McKinsey spoke with Violet Chung, a partner in the Hong Kong office, to understand more about what it takes for insurers to adopt AI into their business models and the benefits that come with adoption. McKinsey: What are the latest trends with AI that insurers should be aware of? Violet Chung: The latest McKinsey Global Survey on AI found that AI adoption continues to grow and deliver significant benefits to businesses: 50 percent of respondents reported using AI in at least one business function across their organizations.

Would you like your Salesforce projects to move each requirement to a user story, then to development, and then to "ready for QA" more quickly? Have you been hearing about AI and are looking for a use case with a clear and obvious ROI? There's no reason to wait any longer. With the right tools and processes in place, your Salesforce projects can go from requirement to ready for QA amazingly quickly – for some requirements, literally within 15 minutes. By embracing AI, you can reduce your ideation-to-production cycle from months to weeks or even to days. Let's explore how you can make it happen!

Sustainability is a leading concern for businesses today, and plastic waste is one of the most prevalent issues. Artificial intelligence (AI) has emerged as a helpful tool as companies and governments search for ways to reduce and clean up pollution.

Many enterprises have already begun using enhanced visibility through "control towers," which provide decision-makers access to real-time manufacturing data aggregated across the organization. These insights enable timely and financially-sound decision making and provide intelligence on tradeoffs. Decision intelligence processes take this process further by applying AI to the "control tower," so that these decisions can be optimized without the need for manual human analysis that may introduce latencies or errors in key decisions that need to be made quickly. An example of this would be when a procurement team learns that an excipient supplier was used in manufacturing a drug and is unable to make their shipment as planned. Through decision intelligence, procurement professionals can quickly respond by sending instructions to the manufacturing floor to slow down production on the line of that drug product.