Identifying linguistic differences between dialects of a language often requires expert knowledge and meticulous human analysis. This is largely due to the complexity and nuance involved in studying various dialects. We present a novel approach to extract distinguishing lexical features of dialects by utilizing interpretable dialect classifiers, even in the absence of human experts. We explore both post-hoc and intrinsic approaches to interpretability, conduct experiments on Mandarin, Italian, and Low Saxon, and experimentally demonstrate that our method successfully identifies key language-specific lexical features that contribute to dialectal variations.

Large Language Models (LLMs) exhibit impressive capabilities but also present risks such as biased content generation and privacy issues. One of the current alignment techniques includes principle-driven integration, but it faces challenges arising from the imprecision of manually crafted rules and inadequate risk perception in models without safety training. To address these, we introduce Guide-Align, a two-stage approach. Initially, a safety-trained model identifies potential risks and formulates specific guidelines for various inputs, establishing a comprehensive library of guidelines and a model for input-guidelines retrieval. Subsequently, the retrieval model correlates new inputs with relevant guidelines, which guide LLMs in response generation to ensure safe and high-quality outputs, thereby aligning with human values. An additional optional stage involves fine-tuning a model with well-aligned datasets generated through the process implemented in the second stage. Our method customizes guidelines to accommodate diverse inputs, thereby enhancing the fine-grainedness and comprehensiveness of the guideline library. Furthermore, it incorporates safety expertise from a safety-trained LLM through a lightweight retrieval model. We evaluate our approach on three benchmarks, demonstrating significant improvements in LLM security and quality. Notably, our fine-tuned model, Labrador, even at 13 billion parameters, outperforms GPT-3.5-turbo and surpasses GPT-4 in alignment capabilities.

Large-scale high-resolution (HR) land-cover mapping is a vital task to survey the Earth's surface and resolve many challenges facing humanity. However, it is still a non-trivial task hindered by complex ground details, various landforms, and the scarcity of accurate training labels over a wide-span geographic area. In this paper, we propose an efficient, weakly supervised framework (Paraformer) to guide large-scale HR land-cover mapping with easy-access historical land-cover data of low resolution (LR). Specifically, existing land-cover mapping approaches reveal the dominance of CNNs in preserving local ground details but still suffer from insufficient global modeling in various landforms. Therefore, we design a parallel CNN-Transformer feature extractor in Paraformer, consisting of a downsampling-free CNN branch and a Transformer branch, to jointly capture local and global contextual information. Besides, facing the spatial mismatch of training data, a pseudo-label-assisted training (PLAT) module is adopted to reasonably refine LR labels for weakly supervised semantic segmentation of HR images. Experiments on two large-scale datasets demonstrate the superiority of Paraformer over other state-of-the-art methods for automatically updating HR land-cover maps from LR historical labels.

On an overcast day in Tokyo this week, three dozen men and women strolled through a botanical garden in groups of four, making awkward conversation as they searched for clues to a mystery-solving game -- and a potential partner for life. They are participants in one of the many matchmaking events the Tokyo Metropolitan Government has been hosting for years in an attempt, so far unsuccessful, to reverse declines in marriages and births. Having organized parties and offered dating and fashion advice, the metropolis of 14 million now hopes for a broader reach and better results by releasing an artificial intelligence-powered dating app as early as this spring.

Elon Musk casually dropped that he has another Neuralink project in the works which he says will bestow sight upon people born blind -- and the tech is already being tested on monkeys. True to form, Musk announced the project's official name, 'Blindsight,' while replying to users on his social site X, first in late January, then with fresh details Wednesday. Musk claimed the tech will be lo-rez at first, 'like early Nintendo graphics' from the 1980s era of 8-bit video games. But ultimately, he hopes it will actually'exceed normal human vision.' If Blindsight remains true to its first unnamed tease, presented during a Neuralink'Show and Tell' in late 2022, the implant will be able to repackage digital camera data into electrical impulses compatible for delivery straight into the visual cortex.

Rep. Jay Obernolte was selected to lead the House task force on AI. Fox News Digital speaks with the California Republican about his goals for the panel and his own thoughts about the rapidly advancing technology. Soon after Italian watchdog Garante took on ChatGPT with a temporary shutdown locally last year, it tried to strengthen its team by hiring four artificial intelligence (AI) experts. But Italy's data protection agency could not recruit the people it wanted, with a dozen candidates dropping out over issues including pay, highlighting a growing challenge facing regulators around the world. "The search process went worse than our low expectations," Garante board member Guido Scorza told Reuters, adding: "We will come up with something else, but so far we have lost."

The governor of Tennessee has approved a law that aims to protect musical artists from exploitation or replication by artificial intelligence. Gov. Bill Lee signed into law the Ensuring Likeness, Voice, and Image Security (ELVIS) Act on Thursday at a honky-tonk bar in Nashville. "There are certainly many things that are positive about what AI does," Lee said during the event. "It also, when fallen into the hands of bad actors, it can destroy this industry." "It can rob an individual, these individual artists to whose unique God-given gifts transform people's lives," the governor added.

Illinois advertising professor Michelle Nelson says voters should expect to see a lot more generative AI in political ads during the 2024 election cycle, warning that it might be difficult to impossible to tell what's real and what's fake. It's estimated that 12 billion will be spent on political ads this [USA] election cycle – 30% more than in 2020. The sheer volume of ads is remarkable, and there is vast potential to use this political information to contribute to democracy: to reach more potential voters and provide accurate information. There's also more potential than ever for generative artificial intelligence to misrepresent candidates and policies, leading to confusion in the voting booth. News Bureau editor Lois Yoksoulian spoke with advertising professor and department head Michelle Nelson about the topic.

Heritage Foundation tech policy director Kara Frederick joins'America's Newsroom' to discuss pornographic AI photos of Taylor Swift sparking conversations about deepfake regulation. Italian Premier Giorgia Meloni has been asked to testify in court July 2 in the trial of two men who are accused of making deepfake pornographic images using her face and posting them online. Meloni, who is listed as an injured party in the trial in Sassari in Sardinia, is seeking 108,212 in symbolic damages and will donate any award to an Interior Ministry fund for women victims of domestic violence, her attorney Maria Giulia Marongiu said in an email Friday to The Associated Press. "The crime in question is particularly odious, as it allegedly involves the uploading of fabricated pornographic images that could affect any unsuspecting woman with damaging consequences for her reputation and private life," Marongiu said. Italian Premier Giorgia Meloni arrives in the courtyard of the Italian government office Chigi Palace, to meet Kazakhstan President Kassym-Jomart Tokayev, in Rome, on Jan. 18, 2024. Meloni has been asked to testify in court on July 2, 2024, in the trial of two men who are accused of making deepfake pornographic images using her face and posting them online.

The Department of Justice and more than a dozen states have filed a lawsuit against Apple in the US federal court, accusing the company of violating antitrust laws. It says Apple's hardware and software products are largely inaccessible to competitors, making it difficult for rivals to compete and for customers to switch to other companies' products. The lawsuit comes after the European Commission fined Apple 1.8 billion ( 1.95 billion) for stopping music-streaming developers from "informing iOS users about alternative and cheaper music subscription services available" outside the App Store. The DOJ suggests Apple used its control over iOS to block innovative apps and cloud streaming services from the public. The suit also suggests Apple has obstructed rival payment platforms, made it harder for Android messages to appear on iPhones and restricted how competing smartphones integrated with iOS devices.