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@memeorandum@universeodon.com
2025-10-20 18:55:44

Portfolio: The Trap at 26 Federal Plaza (New York Magazine)
nymag.com/intelligencer/articl
memeorandum.com/251020/p85#a25

@Techmeme@techhub.social
2025-12-07 07:01:53

Excelsior Sciences, which aims to use AI and robots for small-molecule drug discovery and development, raised a $70M Series A from Khosla Ventures and others (Aayushi Pratap/Chemical & Engineering News)
cen.acs.org/physical-chemistry

New York AI chemistry start-up raises $95 million 
Excelsior Sciences cofounders say the company will make new molecules using robots and artificial intelligence

@carlos@perceptiveconstructs.com
2025-12-04 15:28:23
@… @…

Yeah, for the truly portable laptop there isn't.
For the laptop in form-factor but nearly always plugged to the mains and placed on a desk Intel/AMD could be O…
@carlos@social.perceptiveconstructs.com
2025-12-04 15:28:23
@… @…

Yeah, for the truly portable laptop there isn't.
For the laptop in form-factor but nearly always plugged to the mains and placed on a desk Intel/AMD could be O…
@arXiv_csCL_bot@mastoxiv.page
2025-09-29 11:15:47

Exploratory Semantic Reliability Analysis of Wind Turbine Maintenance Logs using Large Language Models
Max Malyi, Jonathan Shek, Andre Biscaya
arxiv.org/abs/2509.22366

Exploratory Semantic Reliability Analysis of Wind Turbine Maintenance Logs using Large Language Models
A wealth of operational intelligence is locked within the unstructured free-text of wind turbine maintenance logs, a resource largely inaccessible to traditional quantitative reliability analysis. While machine learning has been applied to this data, existing approaches typically stop at classification, categorising text into predefined labels. This paper addresses the gap in leveraging modern large language models (LLMs) for more complex reasoning tasks. We introduce an exploratory framework t…

@arXiv_csCV_bot@mastoxiv.page
2025-09-26 10:25:41

A Sentinel-3 foundation model for ocean colour
Geoffrey Dawson, Remy Vandaele, Andrew Taylor, David Moffat, Helen Tamura-Wicks, Sarah Jackson, Rosie Lickorish, Paolo Fraccaro, Hywel Williams, Chunbo Luo, Anne Jones
arxiv.org/abs/2509.21273

A Sentinel-3 foundation model for ocean colour
Artificial Intelligence (AI) Foundation models (FMs), pre-trained on massive unlabelled datasets, have the potential to drastically change AI applications in ocean science, where labelled data are often sparse and expensive to collect. In this work, we describe a new foundation model using the Prithvi-EO Vision Transformer architecture which has been pre-trained to reconstruct data from the Sentinel-3 Ocean and Land Colour Instrument (OLCI). We evaluate the model by fine-tuning on two downstrea…

@arXiv_csCR_bot@mastoxiv.page
2025-09-23 10:16:50

AdaptiveGuard: Towards Adaptive Runtime Safety for LLM-Powered Software
Rui Yang, Michael Fu, Chakkrit Tantithamthavorn, Chetan Arora, Gunel Gulmammadova, Joey Chua
arxiv.org/abs/2509.16861

AdaptiveGuard: Towards Adaptive Runtime Safety for LLM-Powered Software
Guardrails are critical for the safe deployment of Large Language Models (LLMs)-powered software. Unlike traditional rule-based systems with limited, predefined input-output spaces that inherently constrain unsafe behavior, LLMs enable open-ended, intelligent interactions--opening the door to jailbreak attacks through user inputs. Guardrails serve as a protective layer, filtering unsafe prompts before they reach the LLM. However, prior research shows that jailbreak attacks can still succeed ove…

@arXiv_csCY_bot@mastoxiv.page
2025-09-23 11:07:10

Tenure Under Pressure: Simulating the Disruptive Effects of AI on Academic Publishing
Shan Jiang
arxiv.org/abs/2509.16925 arxiv.org/pdf/250…

Tenure Under Pressure: Simulating the Disruptive Effects of AI on Academic Publishing
Generative artificial intelligence (AI) has begun to reshape academic publishing by enabling the rapid production of submission-ready manuscripts. While such tools promise to enhance productivity, they also raise concerns about overwhelming journal systems that have fixed acceptance capacities. This paper uses simulation modeling to investigate how AI-driven surges in submissions may affect desk rejection rates, review cycles, and faculty publication portfolios, with a focus on business school …

@arXiv_csCV_bot@mastoxiv.page
2025-09-25 07:31:52

Vision-Based Perception for Autonomous Vehicles in Off-Road Environment Using Deep Learning
Nelson Alves Ferreira Neto
arxiv.org/abs/2509.19378

Vision-Based Perception for Autonomous Vehicles in Off-Road Environment Using Deep Learning
Low-latency intelligent systems are required for autonomous driving on non-uniform terrain in open-pit mines and developing countries. This work proposes a perception system for autonomous vehicles on unpaved roads and off-road environments, capable of navigating rough terrain without a predefined trail. The Configurable Modular Segmentation Network (CMSNet) framework is proposed, facilitating different architectural arrangements. CMSNet configurations were trained to segment obstacles and traf…