FractalCloud: A Fractal-Inspired Architecture for Efficient Large-Scale Point Cloud Processingcs.AI updates on arXiv.org arXiv:2511.07665v1 Announce Type: cross
Abstract: Three-dimensional (3D) point clouds are increasingly used in applications such as autonomous driving, robotics, and virtual reality (VR). Point-based neural networks (PNNs) have demonstrated strong performance in point cloud analysis, originally targeting small-scale inputs. However, as PNNs evolve to process large-scale point clouds with hundreds of thousands of points, all-to-all computation and global memory access in point cloud processing introduce substantial overhead, causing $O(n^2)$ computational complexity and memory traffic where n is the number of points}. Existing accelerators, primarily optimized for small-scale workloads, overlook this challenge and scale poorly due to inefficient partitioning and non-parallel architectures. To address these issues, we propose FractalCloud, a fractal-inspired hardware architecture for efficient large-scale 3D point cloud processing. FractalCloud introduces two key optimizations: (1) a co-designed Fractal method for shape-aware and hardware-friendly partitioning, and (2) block-parallel point operations that decompose and parallelize all point operations. A dedicated hardware design with on-chip fractal and flexible parallelism further enables fully parallel processing within limited memory resources. Implemented in 28 nm technology as a chip layout with a core area of 1.5 $mm^2$, FractalCloud achieves 21.7x speedup and 27x energy reduction over state-of-the-art accelerators while maintaining network accuracy, demonstrating its scalability and efficiency for PNN inference.
arXiv:2511.07665v1 Announce Type: cross
Abstract: Three-dimensional (3D) point clouds are increasingly used in applications such as autonomous driving, robotics, and virtual reality (VR). Point-based neural networks (PNNs) have demonstrated strong performance in point cloud analysis, originally targeting small-scale inputs. However, as PNNs evolve to process large-scale point clouds with hundreds of thousands of points, all-to-all computation and global memory access in point cloud processing introduce substantial overhead, causing $O(n^2)$ computational complexity and memory traffic where n is the number of points}. Existing accelerators, primarily optimized for small-scale workloads, overlook this challenge and scale poorly due to inefficient partitioning and non-parallel architectures. To address these issues, we propose FractalCloud, a fractal-inspired hardware architecture for efficient large-scale 3D point cloud processing. FractalCloud introduces two key optimizations: (1) a co-designed Fractal method for shape-aware and hardware-friendly partitioning, and (2) block-parallel point operations that decompose and parallelize all point operations. A dedicated hardware design with on-chip fractal and flexible parallelism further enables fully parallel processing within limited memory resources. Implemented in 28 nm technology as a chip layout with a core area of 1.5 $mm^2$, FractalCloud achieves 21.7x speedup and 27x energy reduction over state-of-the-art accelerators while maintaining network accuracy, demonstrating its scalability and efficiency for PNN inference. Read More
Uhale Android-based digital picture frames come with multiple critical security vulnerabilities and some of them download and execute malware at boot time. […] Read MoreUhale Android-based digital picture frames come with multiple critical security vulnerabilities and some of them download and execute malware at boot time. […]
AIA Forecaster: Technical Reportcs.AI updates on arXiv.org arXiv:2511.07678v1 Announce Type: new
Abstract: This technical report describes the AIA Forecaster, a Large Language Model (LLM)-based system for judgmental forecasting using unstructured data. The AIA Forecaster approach combines three core elements: agentic search over high-quality news sources, a supervisor agent that reconciles disparate forecasts for the same event, and a set of statistical calibration techniques to counter behavioral biases in large language models. On the ForecastBench benchmark (Karger et al., 2024), the AIA Forecaster achieves performance equal to human superforecasters, surpassing prior LLM baselines. In addition to reporting on ForecastBench, we also introduce a more challenging forecasting benchmark sourced from liquid prediction markets. While the AIA Forecaster underperforms market consensus on this benchmark, an ensemble combining AIA Forecaster with market consensus outperforms consensus alone, demonstrating that our forecaster provides additive information. Our work establishes a new state of the art in AI forecasting and provides practical, transferable recommendations for future research. To the best of our knowledge, this is the first work that verifiably achieves expert-level forecasting at scale.
arXiv:2511.07678v1 Announce Type: new
Abstract: This technical report describes the AIA Forecaster, a Large Language Model (LLM)-based system for judgmental forecasting using unstructured data. The AIA Forecaster approach combines three core elements: agentic search over high-quality news sources, a supervisor agent that reconciles disparate forecasts for the same event, and a set of statistical calibration techniques to counter behavioral biases in large language models. On the ForecastBench benchmark (Karger et al., 2024), the AIA Forecaster achieves performance equal to human superforecasters, surpassing prior LLM baselines. In addition to reporting on ForecastBench, we also introduce a more challenging forecasting benchmark sourced from liquid prediction markets. While the AIA Forecaster underperforms market consensus on this benchmark, an ensemble combining AIA Forecaster with market consensus outperforms consensus alone, demonstrating that our forecaster provides additive information. Our work establishes a new state of the art in AI forecasting and provides practical, transferable recommendations for future research. To the best of our knowledge, this is the first work that verifiably achieves expert-level forecasting at scale. Read More
CISA warned federal agencies to fully patch two actively exploited vulnerabilities in Cisco Adaptive Security Appliances (ASA) and Firepower devices. […] Read MoreCISA warned federal agencies to fully patch two actively exploited vulnerabilities in Cisco Adaptive Security Appliances (ASA) and Firepower devices. […]
The Race for Every New CVE Based on multiple 2025 industry reports: roughly 50 to 61 percent of newly disclosed vulnerabilities saw exploit code weaponized within 48 hours. Using the CISA Known Exploited Vulnerabilities Catalog as a reference, hundreds of software flaws are now confirmed as actively targeted within days of public disclosure. Each new […]
Malware families like Rhadamanthys Stealer, Venom RAT, and the Elysium botnet have been disrupted as part of a coordinated law enforcement operation led by Europol and Eurojust. The activity, which is taking place between November 10 and 13, 2025, marks the latest phase of Operation Endgame, an ongoing operation designed to take down criminal infrastructures […]
Law enforcement authorities from 9 countries have taken down 1,025 servers used by the Rhadamanthys infolstealer, VenomRAT, and Elysium botnet malware operations in the latest phase of Operation Endgame, an international action targeting cybercrime. […] Read MoreLaw enforcement authorities from 9 countries have taken down 1,025 servers used by the Rhadamanthys infolstealer, VenomRAT, and Elysium botnet […]
Behind every click, there’s a risk waiting to be tested. A simple ad, email, or link can now hide something dangerous. Hackers are getting smarter, using new tools to sneak past filters and turn trusted systems against us. But security teams are fighting back. They’re building faster defenses, better ways to spot attacks, and stronger […]
CISA has ordered federal agencies to patch an actively exploited vulnerability in WatchGuard Firebox firewalls, which allows attackers to gain remote code execution on compromised devices. […] Read MoreCISA has ordered federal agencies to patch an actively exploited vulnerability in WatchGuard Firebox firewalls, which allows attackers to gain remote code execution on compromised devices. […]
When I’m teachning FOR610[1], I always say to my students that reverse engineering does not only apply to “executable files” (read: PE or ELF files). Most of the time, the infection path involves many stages to defeat the Security Analyst or security controls. Here is an example that I found yesterday. An email was received […]
