Commentary and a selection of the most important recent news, articles, and papers about AI.
Today’s Brief Commentary
Today’s links give an idea of how AI is being used across the arts, academia, and business. That sounds better than saying they are a bunch of odds and ends as we approach the end of 2024, doesn’t it?
Just as NVIDIA is often the center of attention for GPUs, AWS is frequently the partner of choice for companies deploying their applications. Moreover, it looks after its own offerings via investments like those in Anthropic while also supporting the IBM Granite LLM on its cloud, for example. AWS gets powerful generative AI tools for its users and applications, and it helps control the further market growth of OpenAI. Or that’s the theory, at least.
Saudi Arabia is launching its Project Transcendence AI initiative with $100B. There is a new focus word that crops up again and again with both AI and quantum computing: sovereign. Countries do not want to be beholden to other nations for their most advanced tech. Ideally, it should be home-grown with local talent and intellectual property, they believe.
Again, that’s the theory.
In reality, in-country companies may need to bring in essential workforce members from elsewhere, which gets political and sometimes bombastic. Supply chains are international and are affected by treaties and tariffs. It’s a new world, with innovations happening globally. Tech sovereignty is now an important issue that must be considered and respected by government and business people.
For hardcore scientists and engineers, it is another factor in the big picture that makes starting and running a successful business that much more complicated. You may want to keep your mind on your hardware and software, but the sooner you learn about issues like this, the better you may be able to compete on the big stage.
General News, Articles, and Analyses
Digital Twin of St. Peter’s Basilica Brings Interactive Experience to Homes
Author: Liz Hughes
(Wednesday, November 20, 2024) “The Vatican has teamed with Microsoft to create an AI-powered digital twin of St. Peter’s Basilica allowing those celebrating the Holy Year in 2025 to experience it virtually, no matter where they are.”
Music and the Arts
Royal Shakespeare Company to look at AI and immersive technology in theatre
https://uk.news.yahoo.com/royal-shakespeare-company-look-ai-000100606.html
Author: Charlotte McLaughlin
(Tuesday, November 26, 2024) “The Royal Shakespeare Company will look at using artificial intelligence (AI) and immersive technology in future productions, the Government announced as part of other projects and funding measures for the West Midlands as well as Merseyside.
Based at playwright William Shakespeare’s birthplace in Stratford-upon-Avon, Warwickshire, as well as London, the theatre company will lead R&D pilot production projects in collaboration with the US tech and media festival South by Southwest (SXSW).”
Semiconductor Chipsets and Infrastructure
The 10 Hottest Semiconductor Startups Of 2024
https://www.crn.com/news/components-peripherals/2024/the-10-hottest-semiconductor-startups-of-2024
Author: Dylan Martin
(Friday, November 22, 2024) “CRN rounds up the 10 hottest semiconductor startups of 2024, which includes firms building AI chips such as Groq and Tenstorrent as well as those building complementary silicon like Celestial AI and Enfabrica.”
Generative AI and Models
Amazon to invest another $4 billion in Anthropic, OpenAI’s biggest rival
Author: Hayden Field
(Friday, November 22, 2024) “Amazon on Friday announced it would invest an additional $4 billion in Anthropic, the artificial intelligence startup founded by ex-OpenAI research executives.”
IBM and AWS Accelerate Partnership to Scale Responsible Generative AI
https://newsroom.ibm.com/blog-ibm-and-aws-accelerate-partnership-to-scale-responsible-generative-ai
(Monday, November 25, 2024) “During AWS re:Invent, IBM and AWS will unveil new milestones in our collaboration to help businesses adopt responsible AI. Together, we are combining our strengths to ensure that organizations can harness the power of generative AI with an emphasis on transparency, security and trust.”
What Is Generative AI? Everything to Know About the Tech Behind ChatGPT and Gemini | CNET
Author: Barbara Pazur
(Tuesday, November 26, 2024) “At its core, generative AI refers to artificial intelligence systems that are designed to produce new content based on patterns and data they’ve learned. Instead of just analyzing numbers or predicting trends, these systems generate creative outputs like text, images music, videos and software code.”
Sovereign Initiatives
Saudi Arabia Launches $100B Initiative to Develop AI Ecosystem
https://aibusiness.com/responsible-ai/saudi-arabia-launches-100b-initiative-to-develop-ai-ecosystem
Author: Heidi Vella
(Wednesday, November 20, 2024) “Saudi Arabia has announced it is launching a $100 billion-backed initiative to develop an extensive AI ecosystem in the country spanning innovation, infrastructure and talent development.
Named Project Transcendence, the initiative would see the country’s Public Investment Fund put money into data center expansion, tech startups, workforce development and partnerships with leading technology firms.”
Technical Papers, Articles, and Preprints
[2411.15477] Towards Robust Evaluation of Unlearning in LLMs via Data Transformations
https://arxiv.org/abs/2411.15477
Authors: Joshi, Abhinav; Saha, Shaswati; Shukla, Divyaksh; Vema, Sriram; Jhamtani, Harsh; Gaur, Manas; and Modi, Ashutosh
(Saturday, November 23, 2024) “Large Language Models (LLMs) have shown to be a great success in a wide range of applications ranging from regular NLP-based use cases to AI agents. LLMs have been trained on a vast corpus of texts from various sources; despite the best efforts during the data pre-processing stage while training the LLMs, they may pick some undesirable information such as personally identifiable information (PII). Consequently, in recent times research in the area of Machine Unlearning (MUL) has become active, the main idea is to force LLMs to forget (unlearn) certain information (e.g., PII) without suffering from performance loss on regular tasks. In this work, we examine the robustness of the existing MUL techniques for their ability to enable leakage-proof forgetting in LLMs. In particular, we examine the effect of data transformation on forgetting, i.e., is an unlearned LLM able to recall forgotten information if there is a change in the format of the input? Our findings on the TOFU dataset highlight the necessity of using diverse data formats to quantify unlearning in LLMs more reliably.”
[2411.17614] Automating Chapter-Level Classification for Electronic Theses and Dissertations
https://arxiv.org/abs/2411.17614
Authors: Banerjee, Bipasha; Ingram, William A.; and Fox, Edward A.
(Tuesday, November 26, 2024) “Traditional archival practices for describing electronic theses and dissertations (ETDs) rely on broad, high-level metadata schemes that fail to capture the depth, complexity, and interdisciplinary nature of these long scholarly works. The lack of detailed, chapter-level content descriptions impedes researchers’ ability to locate specific sections or themes, thereby reducing discoverability and overall accessibility. By providing chapter-level metadata information, we improve the effectiveness of ETDs as research resources. This makes it easier for scholars to navigate them efficiently and extract valuable insights. The absence of such metadata further obstructs interdisciplinary research by obscuring connections across fields, hindering new academic discoveries and collaboration. In this paper, we propose a machine learning and AI-driven solution to automatically categorize ETD chapters. This solution is intended to improve discoverability and promote understanding of chapters. Our approach enriches traditional archival practices by providing context-rich descriptions that facilitate targeted navigation and improved access. We aim to support interdisciplinary research and make ETDs more accessible. By providing chapter-level classification labels and using them to index in our developed prototype system, we make content in ETD chapters more discoverable and usable for a diverse range of scholarly needs. Implementing this AI-enhanced approach allows archives to serve researchers better, enabling efficient access to relevant information and supporting deeper engagement with ETDs. This will increase the impact of ETDs as research tools, foster interdisciplinary exploration, and reinforce the role of archives in scholarly communication within the data-intensive academic landscape.”
