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AI’s Dirty Little Secret: Stanford Researchers Expose Flaws in Text Detectors

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AI Breakfast
September 06, 2023

Good morning. It’s Wednesday, September 6th.

Did you know: On this day in 1998, Google was founded.

In today’s email:

  • Integration of AI with Other Tools and Platforms

  • Economic Impact of AI

  • AI in Government and Regional Adoption

  • AI in Scientific Research

  • Concerns and Issues with AI

  • 5 New AI Tools

  • Latest AI Research Papers

You read. We listen. Let us know what you think of this edition by replying to this email, or DM us on Twitter.

Today’s trending AI news stories

OpenAI Plugs ChatGPT Into Canva to Sharpen Its Competitive Edge in AI: OpenAI has introduced a Canva plugin for ChatGPT, simplifying visual content creation for businesses and entrepreneurs. This integration streamlines the process of generating visuals like logos and banners. Users can describe the visuals they need for ChatGPT, which generates options for editing in Canva. This feature is exclusive to ChatGPT Plus subscribers, enhancing its capabilities and responsiveness. Despite some initial limitations, OpenAI’s efforts aim to keep ChatGPT competitive in the evolving AI landscape, with integrations like this aligning their strategy to meet diverse user needs.

AI Startups Create Digital Demand for Anguilla's Website Domain Name: Anguila, a tiny Caribbean territory, is experiencing a digital gold rush as demand for .ai domain names skyrockets due to the artificial intelligence frenzy. The .ai domain, previously overlooked, has gained immense popularity with startups like X.ai and Character.ai, as well as tech giants like Google and Facebook. Anguilla is set to earn up to $30 million from domain registration fees in 2023, significantly boosting its economy. This surge reflects the broader AI boom and the importance of branding in the tech industry.

Japan’s Prefectural Governments Adopting or Trialing ChatGPT for Work Purposes: Several Japanese prefectures, including Tokyo, Fukushima, and Tochigi, have either adopted or are trialing ChatGPT, a generative AI developed by OpenAI, for various work purposes. Tokyo Metropolitan Government now permits around 50,000 employees to use ChatGPT for tasks like summarizing documents and proposing ideas. In total, over half of Japan’s prefectures have introduced generative AI, creating a significant adoption trend in the country. The use of ChatGPT is more prevalent in eastern regions, with some western regions still considering its implementation.

OpenAI CEO Sam Altman First Person to Get Indonesia Golden Visa: OpenAI Sam Altman has become the first person to receive an Indonesian golden visa, which grants him a 10-year stay in Indonesia with various benefits such as priority screening at airports. This new visa aims to attract foreign investors to the country, requiring substantial investments in Indonesia, such as investing $350,000 in local public company shares, savings accounts, or government bonds. It’s unclear whether Altman applied for the visa or plans to invest in Indonesia.

Bybit debuts AI-powered ‘TradeGPT’ for market analysis and data-driven Q&A: Bybit, a cryptocurrency exchange has launched ‘TradeGPT’, an AI-powered trading assistant that offers real-time market analysis and answers user queries in multiple languages. TradeGPT uses ChatGPT language model and Bybit’s ToolsGPT to provide market insights and product strategies. Bybit aims to enhance the trading experience for its users by integrating AI into its platform, joining other exchanges like Crypto.com and Binance in offering AI-powered tools for market analysis and insights.

IBM spinoff sees ASEAN companies rapidly adopting generative AI: Kyndryl, an IT infrastructure service provider, anticipates that Southeast Asian companies will soon catch up with their U.S. and European counterparts in adopting generative AI technology. The company, which operates in six Southeast Asian countries, is seeing significant interest in generative AI among its ASEAN customers, particularly in sectors like healthcare and manufacturing. A partnership with Microsoft aims to facilitate the adoption of enterprise-grade AI solutions in the region. While some Southeast Asian companies are still working on data governance, Kyndryl expects rapid growth in tech spending in the region.

AI identifies top predictors of adolescent suicide and self-harm: Researchers have utilized AI to identify key predictors of adolescent self-harm and suicide attempts, surpassing conventional risk assessment methods. By analyzing data from over 2,800 adolescents, machine learning identified factors such as mental health, physical health, relationships, and environmental elements. The model outperformed approaches solely based on past self-harm or suicide attempts, offering the potential for individualized care for vulnerable youth. This research challenges the notion that poor mental health alone drives self-harm and suicide. Further validation is needed before implementing these models in clinical settings.

AI algorithm learns microscopic details of nematicity in moiré systems: Researchers have employed AI to comprehend microscopic details of nematicity in moiré systems, especially in twisted bilayer and twisted double bilayer graphene structures. These systems have been of great interest in the condensed matter physics community due to their unique properties. AI, specifically a convolutional neural network (CNN), was trained to recognize features of nematicity and distinguish them from strain, offering a new tool for studying complex materials and phenomena. This AI-powered tool helps scientists better understand and manipulate special materials, potentially leading to the development of new technologies and discoveries.

AI’s Dirty Little Secret: Stanford Researchers Expose Flaws in Text Detectors: Researchers at Stanford University have revealed flaws in AI text detectors, particularly concerning their misidentification of articles written by non-native English speakers as AI-generated, including those from the TOEFL. Such errors could significantly impact academic and professional contexts like job applications and student assignments. This study spotlights biases in AI detection systems and their potential consequences. Funding came from the National Science Foundation, the National Institutes of Health, and the Silicon Valley Community Foundation.

Crypto is in ‘arms race’ against AI-powered scams: Quantstamp co-founder: Quantstamp’s Richard Ma warns that the rapid evolution of AI empowers scammers with tools for more sophisticated attacks, raising the threat to crypto organizations. AI-enhanced phishing scams make attackers appear convincing, posing a significant risk. Ma suggests safeguarding sensitive data by using internal channels instead of email or text and investing in anti-phishing software. The scale at which AI-powered attacks can be executed is a growing concern. Solana’s resilience amid negative sentiment and YTD inflows suggests it's a favored altcoin.

5 new AI-powered tools from around the web

Beatcanvas.ai is a Spotify Canvas Maker powered by AI, enabling users to effortlessly craft custom track videos, enhancing streaming performance. It offers customizable templates, data analytics, and flexible pricing options to cater to diverse requirements.

Audiosonic is the ultimate AI generator for instant text-to-speech conversion. Ideal for marketing, education, podcasts, and more. Seamlessly integrates with Writesonic and Chatsonic, offering language support. Transform written content into engaging audio effortlessly.

Singify by FineShare is an online AI Song Cover Generator that lets music lovers and creators turn their favorite songs into personalized masterpieces with AI. It offers a wide range voice models and easy three-step creation.

Snipo is an AI notetaker for videos that seamlessly integrates with Notion. Take time-stamped notes, capture screenshots, and create AI flashcards while watching videos. Perfect for students and online learners, it simplifies course content organization and enhances knowledge retention. Integrated with top video platforms, including YouTube and Udemy.

Talklab offers AI-powered chat analytics for valuable customer insights. This platform analyzes customer chats, providing actionable reports with sentiment scores and behavioral tags. It enhances customer service by lowering churn rates and boosting satisfaction levels. Perfect for businesses seeking data-driven improvements in customer communication.

arXiv is a free online library where scientists share their research papers before they are published. Here are the top AI papers for today.

The paper discusses the significance of 3D vision and its applications in autonomous driving, navigation, scene understanding, and robotics. It introduces Point-Bind, a unified 3D framework aligning point clouds with multi-modalities, allowing for various 3D-centric multi-modal tasks. It presents Point-LLM, a 3D large language model, and highlights its applications in 3D question-answering and multi-modal reasoning. The paper emphasizes data- and parameter efficiency, aligning 3D with ImageBind, any-to-3D generation, 3D embedding-space arithmetic, and 3D zero-shot understanding. The research contributes to enhancing 3D learning and cross-modal reasoning.

MVDream introduces a multi-view diffusion model for generating geometrically consistent multi-view images based on text prompts. This model combines pre-trained image diffusion models with a multi-view dataset, addressing 3D consistency challenges in 2D-lifting methods. It enhances 3D content creation, particularly for complex objects. MVDream resolves multi-face and content drifting issues and improves 3D generation stability. It also enables personalized 3D generation through identity assimilation. The methodology involves training the model on multi-view images rendered from 3D datasets, resulting in a robust multi-view prior for 3D generation. This innovation promises to streamline 3D content creation and improve consistency in various applications.

This paper investigates the emergence of segmentation models for computer vision tasks. While previous research has observed segmentation properties in vision transformers (ViTs) trained using self-supervised methods like DINO, this study dives into whether similar properties can arise through simpler supervised training methods, employing a specially designed white-box transformer architecture known as crate. The results demonstrate that crate exhibits segmentation properties with minimalistic supervised training, challenging the prevailing notion that complex self-supervised pipelines are necessary. This research highlights the significance of thoughtful architecture design in achieving interpretable foundation models for computer vision.

The paper introduces CityDreamer, a novel generative model designed for creating lifelike 3D city environments. Addressing the challenge of 3D city generation, CityDreamer separates building instances from background elements such as roads and green areas, using bird’s eye-view representations. It employs neural hash grids and periodic positional encoding to handle diverse building appearances. The authors introduce two datasets, OSM and GoogleEarth, providing real-world city layouts and images. Extensive experiments demonstrate CityDreamer’s superiority over existing methods in generating diverse and realistic 3D cities. Google Earth, with diverse real-world images and annotations, stands as a valuable resource for computer vision research.

YaRN (Yet another RoPE extensioN method) offers a compute-efficient solution to extend the context window of transformer-based language models, such as LLaMa models. Unlike previous methods, YaRN achieves this extension with 10x fewer tokens and 2.5x fewer training steps. It enables models to effectively utilize and extrapolate to longer context lengths, benefiting tasks like summarization. Moreover, YaRN can extend beyond the fine-tuning dataset’s context limitations. This paper introduces several interpolation methods, including “NTK-aware,” “NTK-by parts,” and “Dynamic NTK,” addressing issues like high-frequency information loss and relative local distance preservation. These innovations significantly improve context window extension for transformer models.

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