A selection of the most important recent news, articles, and papers about AI.
General News, Articles, and Analyses
Verizon hasn’t forgotten about the old AI
https://www.fierce-network.com/cloud/verizon-hasnt-forgotten-about-old-ai
(Friday, September 20, 2024) “Verizon is leveraging a full spectrum of AI, including predictive AI, computer vision and generative AIPredictive AI and computer vision help Verizon optimize | Verizon is reinventing its network using “a combination of predictive, prescriptive and generative AI.””
Hitachi Rail Advances Real-Time Railway Analysis With AI | NVIDIA Blog
https://blogs.nvidia.com/blog/hitachi-rail-igx-real-time-analysis/
Author: Isha Salian
(Monday, September 23, 2024) “The global transportation company is adopting NVIDIA IGX, the enterprise-ready platform for industrial edge computing, to improve railway operations, lower maintenance costs and reduce energy use.”
Google Funds New AI-Assisted Satellites to Detect Wildfires Faster
https://aibusiness.com/data/google-funds-new-ai-assisted-satellites-to-detect-wildfires-faster
Author: Heidi Vella
(Monday, September 23, 2024) “Google Research has partnered with fire community leaders to launch a new purpose-built satellite constellation designed to detect and track small wildfires within 20 minutes. Called FireSat, the system will use AI and satellite imagery to spot fires as small as a classroom – around 16 by 16 feet. Once detected, the technology will provide near real-time information about the location, size and intensity of early-stage wildfires so firefighters can respond quickly and effectively.”
Decoding How AI Can Accelerate Data Science | NVIDIA Blog
https://blogs.nvidia.com/blog/rtx-ai-rapids-cudf-pandas/
Author: Prachi Goel
(Wednesday, September 25, 2024) “To help data scientists with increasing workload demands, NVIDIA announced that RAPIDS cuDF, a library that allows users to more easily work with data, accelerates the pandas software library with zero code changes. Pandas is a flexible, powerful and popular data analysis and manipulation library for the Python programming language. With cuDF, data scientists can now use their preferred code base without compromising on data processing speed.”
23 generative AI terms and what they really mean | CIO
https://www.cio.com/article/3535552/generative-ai-terms-and-what-they-really-mean.html
Author: Maria Korolov
“From agentic systems to zero-shot prompting, generative AI can feel like a new language. Here are the terms CIOs need to know.”
Technical Papers, Articles, and Preprints
[2403.20329] ReALM: Reference Resolution As Language Modeling
https://arxiv.org/abs/2403.20329
Authors: Moniz, Joel Ruben Antony; Krishnan, Soundarya; Ozyildirim, Melis; Saraf, Prathamesh; Ates, Halim Cagri; Zhang, Yuan; and Yu, Hong
(Friday, March 29, 2024) “Reference resolution is an important problem, one that is essential to understand and successfully handle context of different kinds. This context includes both previous turns and context that pertains to non-conversational entities, such as entities on the user’s screen or those running in the background. While LLMs have been shown to be extremely powerful for a variety of tasks, their use in reference resolution, particularly for non-conversational entities, remains underutilized. This paper demonstrates how LLMs can be used to create an extremely effective system to resolve references of various types, by showing how reference resolution can be converted into a language modeling problem, despite involving forms of entities like those on screen that are not traditionally conducive to being reduced to a text-only modality. We demonstrate large improvements over an existing system with similar functionality across different types of references, with our smallest model obtaining absolute gains of over 5% for on-screen references. We also benchmark against GPT-3.5 and GPT-4, with our smallest model achieving performance comparable to that of GPT-4, and our larger models substantially outperforming it.”
[2409.13524] Contextualized AI for Cyber Defense: An Automated Survey using LLMs
https://arxiv.org/abs/2409.13524
Authors: Haryanto, Christoforus Yoga; Elvira, Anne Maria; Nguyen, Trung Duc; Vu, Minh Hieu; Hartanto, Yoshiano; Lomempow, Emily; and Arakala, Arathi
(Friday, September 20, 2024) “This paper surveys the potential of contextualized AI in enhancing cyber defense capabilities, revealing significant research growth from 2015 to 2024. We identify a focus on robustness, reliability, and integration methods, while noting gaps in organizational trust and governance frameworks. Our study employs two LLM-assisted literature survey methodologies: (A) ChatGPT 4 for exploration, and (B) Gemma 2:9b for filtering with Claude 3.5 Sonnet for full-text analysis. We discuss the effectiveness and challenges of using LLMs in academic research, providing insights for future researchers.”
