Google takes a page out of Meta’s book, announces new audio-powered smart glasses
Google is back in the glasses game with “audio glasses” out this fall.
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BEVMAPMATCH: Multimodal BEV Neural Map Matching for Robust Re-Localization of Autonomous Vehicles
arXiv:2603.25963v1 Announce Type: new Abstract: Localization in GNSS-denied and GNSS-degraded environments is a challenge for the safe widespread deployment of autonomous vehicles. Such GNSS-challenged environments require alternative methods for robust localization. In this work, we propose BEVMapMatch, a framework for robust vehicle re-localization on a known map without the need for GNSS priors. BEVMapMatch uses a context-aware lidar+camera fusion method to generate multimodal Bird’s Eye View (BEV) segmentations around the ego vehicle in both good and adverse weather […]
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The Fluid Interface: A Paradigm Shift to Agent-Driven Experience
1. Introduction: The Dematerialization of the User Interface The history of Human-Computer Interaction (HCI) is a chronicle of our relentless pursuit to reduce the friction between human intent and machine execution. We began with the command line interface (CLI), a domain of rigorous syntax. The graphical user interface (GUI) democratized computing with visual metaphors, and the mobile era calcified logic into the “app model.” We now stand on the precipice of the next major discontinuity: the transition to […]
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Deepening our collaboration with the U.S. Department of Energy
OpenAI and the U.S. Department of Energy have signed a memorandum of understanding to deepen collaboration on AI and advanced computing in support of scientific discovery. The agreement builds on ongoing work with national laboratories and helps establish a framework for applying AI to high-impact research across the DOE ecosystem.
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Building a Web-Based Traveling Salesman Solver That Earned a 21 Proof of Usefulness Score
The Traveling Salesman Problem (TSP) is one of the most famous problems in combinatorial optimization. Given a set of cities and the distances between them, the task is to find the shortest possible route that visits each city exactly once and returns to the starting point. Despite its simple formulation, TSP is NP-hard,and understanding how algorithms search for optimal solutions can be difficult for students encountering the problem for the first time. To make this process more tangible, […]
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What Really Gets in the Way of Change
In the May 18, 2026, edition of The Insider, managing editor Gretchen Gavett highlights the traps that quietly undermine senior leaders.
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Rethinking Soft Compression in Retrieval-Augmented Generation: A Query-Conditioned Selector Perspective
arXiv:2602.15856v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) effectively grounds Large Language Models (LLMs) with external knowledge and is widely applied to Web-related tasks. However, its scalability is hindered by excessive context length and redundant retrievals. Recent research on soft context compression aims to address this by encoding long documents into compact embeddings, yet they often underperform non-compressed RAG due to their reliance on auto-encoder-like full-compression that forces the encoder to compress all document information regardless of relevance […]
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Flow Matching for Tabular Data Synthesis
arXiv:2512.00698v3 Announce Type: replace-cross Abstract: Synthetic data generation is an important tool for privacy-preserving data sharing. Although diffusion models have set recent benchmarks, flow matching (FM) offers a promising alternative. This paper presents different ways to implement FM for tabular data synthesis. We provide a comprehensive empirical study that compares flow matching (FM and variational FM) with a state-of-the-art diffusion method (TabDDPM and TabSyn) in tabular data synthesis. We evaluate both the standard Optimal Transport (OT) and the […]
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Zero-Trust Data Warehousing for Agentic AI: Why Trusting the Pipeline No Longer Scales
Most of the difficult conversations I have around data do not start with disagreement; they start with alignment that feels reassuring at first and only later reveals its cost, because everyone in the room wants roughly the same thing: fresher data, fewer delays between signal and action, less manual intervention, and yet the moment you actually begin to design for those outcomes, the assumptions underneath them start to pull in different directions. The request is usually framed as […]
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PDF: PUF-based DNN Fingerprinting for Knowledge Distillation Traceability
arXiv:2602.23587v1 Announce Type: new Abstract: Knowledge distillation transfers large teacher models to compact student models, enabling deployment on resource-limited platforms while suffering minimal performance degradation. However, this paradigm could lead to various security risks, especially model theft. Existing defenses against model theft, such as watermarking and secure enclaves, focus primarily on identity authentication and incur significant resource costs. Aiming to provide post-theft accountability and traceability, we propose a novel fingerprinting framework that superimposes device-specific Physical Unclonable Function (PUF) […]
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