Viral News - CybAI news

04 Jun

ImplicitTerrain: a Continuous Surface Model for Terrain Data Analysis

stp2y0 CommentsViral News

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Source link lol

04 Jun

Multilingual Prosody Transfer: Comparing Supervised & Transfer Learning

stp2y0 CommentsViral News

arXiv:2406.00022v1 Announce Type: new Abstract: The field of prosody transfer in speech synthesis systems is rapidly advancing. This research is focused on evaluating learning methods for adapting pre-trained monolingual text-to-speech (TTS) models to multilingual conditions, i.e., Supervised Fine-Tuning (SFT) and Transfer Learning (TL). This comparison utilizes three distinct metrics: Mean Opinion Score (MOS), Recognition Accuracy (RA), and Mel Cepstral Distortion (MCD). Results demonstrate that, in comparison to SFT, TL leads to significantly enhanced performance, with an average MOS higher by 1.53 points, a 37.5% increase in RA, and approximately a 7.8-point improvement in MCD. These findings are instrumental in helping…

04 Jun

Snowflake Gives Cloud Customers What They Need and Want at Summit 2024

stp2y0 CommentsViral News

Snowflake Sridhar Ramaswamy delivers the keynote at Data Cloud Summit 2024 Monday June 3 AI is like candy these days, enticing enterprises with the promise of amazing things to come. But AI doesn’t work without a good solid data foundation. Snowflake seems to understand this, which is why the company is spending time at its Data Cloud Summit today giving customers what they want (AI) as well as what they need (better data), all washed down with extensive enhancements to the developer experience. While AI is all the rage these days–and Snowflake CEO Sridhar Ramaswamy, hailing from AI search vendor…

04 Jun

How Science Fiction Can Help Businesses Prepare for the Future of AI

stp2y0 CommentsViral News

The below article is a summary of the 4th episode of the Synthetic Minds podcast. Science fiction author and technologist Brenda Cooper brings a unique lens by seamlessly blending her real-world tech experience with speculative storytelling to explore future possibilities. Her novels “Edge of Dark” and “Wilders” delve into themes like environmental sustainability, AI/robotics evolution, and societal shifts. Cooper's approach melds practical knowledge with imaginative projections, offering profound insights into the intricacies and responsibilities surrounding technological progress. A central focus is the convergence of rapidly advancing technologies and society's adaptability. Drawing from her construction industry background utilizing basic AI/robotics, Cooper…

04 Jun

Databricks + Tabular

stp2y0 CommentsViral News

We are excited to announce that we have agreed to acquire Tabular, Inc, a data management company founded by Ryan Blue, Daniel Weeks, and Jason Reid. This acquisition brings the original creators of Apache Iceberg™ and those of Linux Foundation Delta Lake, the two leading open source lakehouse formats, together. As one, we are going to lead the way with data compatibility so that you are no longer limited by which lakehouse format your data is in. This blog will go through how we intend to work closely with the Iceberg and Delta Lake communities to bring format compatibility to…

04 Jun

Scalable Bayesian Learning with posteriors

stp2y0 CommentsViral News

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Source link lol

04 Jun

Fairness in Autonomous Driving: Towards Understanding Confounding Factors in Object Detection under Challenging Weather

stp2y0 CommentsViral News

[Submitted on 31 May 2024] View a PDF of the paper titled Fairness in Autonomous Driving: Towards Understanding Confounding Factors in Object Detection under Challenging Weather, by Bimsara Pathiraja and 2 other authors View PDF HTML (experimental) Abstract:The deployment of autonomous vehicles (AVs) is rapidly expanding to numerous cities. At the heart of AVs, the object detection module assumes a paramount role, directly influencing all downstream decision-making tasks by considering the presence of nearby pedestrians, vehicles, and more. Despite high accuracy of pedestrians detected on held-out datasets, the potential presence of algorithmic bias in such object detectors, particularly in challenging…

04 Jun

CrossVoice: Crosslingual Prosody Preserving Cascade-S2ST using Transfer Learning

stp2y0 CommentsViral News

arXiv:2406.00021v1 Announce Type: new Abstract: This paper presents CrossVoice, a novel cascade-based Speech-to-Speech Translation (S2ST) system employing advanced ASR, MT, and TTS technologies with cross-lingual prosody preservation through transfer learning. We conducted comprehensive experiments comparing CrossVoice with direct-S2ST systems, showing improved BLEU scores on tasks such as Fisher Es-En, VoxPopuli Fr-En and prosody preservation on benchmark datasets CVSS-T and IndicTTS. With an average mean opinion score of 3.75 out of 4, speech synthesized by CrossVoice closely rivals human speech on the benchmark, highlighting the efficacy of cascade-based systems and transfer learning in multilingual S2ST with prosody transfer. Source link lol

04 Jun

From Structured to Unstructured:A Comparative Analysis of Computer Vision and Graph Models in solving Mesh-based PDEs

stp2y0 CommentsViral News

arXiv:2406.00081v1 Announce Type: new Abstract: This article investigates the application of computer vision and graph-based models in solving mesh-based partial differential equations within high-performance computing environments. Focusing on structured, graded structured, and unstructured meshes, the study compares the performance and computational efficiency of three computer vision-based models against three graph-based models across three data-sets. The research aims to identify the most suitable models for different mesh topographies, particularly highlighting the exploration of graded meshes, a less studied area. Results demonstrate that computer vision-based models, notably U-Net, outperform the graph models in prediction performance and efficiency in two (structured and graded)…

04 Jun

A-SDM: Accelerating Stable Diffusion through Model Assembly and Feature Inheritance Strategies

stp2y0 CommentsViral News

arXiv:2406.00210v1 Announce Type: new Abstract: The Stable Diffusion Model (SDM) is a prevalent and effective model for text-to-image (T2I) and image-to-image (I2I) generation. Despite various attempts at sampler optimization, model distillation, and network quantification, these approaches typically maintain the original network architecture. The extensive parameter scale and substantial computational demands have limited research into adjusting the model architecture. 1) For the tuning method, we design a model assembly strategy to reconstruct a lightweight model while preserving performance through distillation. Second, to mitigate performance loss due to pruning, we incorporate multi-expert conditional convolution (ME-CondConv) into compressed UNets to enhance network performance…