#App Development With Stable Diffusion Model | Explore Tumblr Posts and Blogs

gacha-incels · 17 days

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below is a machine translation of the article into english. If you see any discrepancies lmk and I’ll fix it asap. Thanks everyone for your help and continued patience

Ten Million Downloads for the Photo App 'SODA'… Criticism Over AI Being Out of Control Subsidiary of Naver, Snow, Responds Mechanically to AI-Generated Inappropriate Content

Snow, a subsidiary of Naver and the creator of the camera application 'SODA', has come under fire for generating sexually inappropriate images using its AI editing function. The company has stated that it "cannot 100% control AI-generated content," sparking criticism from experts who argue that commercializing an uncontrollable AI service is irresponsible. SODA is a popular camera app with over 10 million downloads on the Google Play Store.

Ms. G, an office worker, complained in an online messenger conversation with Hankyoreh on the 9th, “I didn't expect to feel shame while using the app. It's so unpleasant and traumatizing.” On the 4th, she applied the 'AI background expansion' feature, a paid service of the Soda app, to her photo. The intention was to correct the photo, which was cropped in the middle of her shoulders, to show her entire upper body, but the AI generated a result that made her appear to be clutching her chest with both hands. The rest of the results were normal, but Ms. G said it was hard to get over the shock of the image she suddenly received while using the app.

In response, Snow explained, “Due to the nature of the service that applied A.I. technology, the result was unexpected.” Snow explained that the AI-generated images are filtered to remove offensive or sexualized images as much as possible before they are finally displayed to the user, but this feature did not work perfectly in G's case.

However, experts argue that the issue is more complex. The core problem lies in the AI image generation engine applied to the SODA app, called 'Stable Diffusion'. Developed primarily by the UK startup Stability AI, it was revealed that this model had included explicit content in its training data. Professor Kim Myung-joo of Seoul Women’s University (Information Security) explained, “Unlike other AI models, Stable Diffusion was designed to generate graphic images and included pornographic content in its training data, which has raised concerns since its release.”

Experts are calling for measures like age restrictions on the app to prevent irresponsible commercialization. At the moment, SODA is rated for use by individuals aged 3 and older. Jang Yeo-gyeong, the director of the Information Rights Research Institute, stated, "Even if it doesn't lead to sexual exploitation, consumers who suffer mental harm from AI tools should be able to hold the companies that release these services accountable. Snow's response that 'current technology can't prevent this' is irresponsible."

In response to The Hankyoreh, a Snow representative said, "All companies utilizing AI are struggling to address issues like this. We are working to enhance the service by strengthening filters to prevent similar cases in the future."

plain text in the original Korean

카메라 애플리케이션(앱) ‘소다’(SODA)의 인공지능(AI) 편집 기능이 성적 불쾌감을 일으키는 사진을 생성한 사례가 발생한 것에 대해 이 앱을 만든 네이버의 자회사 스노우가 ‘인공지능 생성물을 100% 통제할 수 없다’는 입장을 내놨다. 통제할 수 없는 인공지능 서비스를 상업화한 것에 대해 무책임한 행태라는 전문가들의 지적이 나온다. 소다는 스마트폰 앱 장터인 ‘구글 플레이 스토어’에서 1000만회 이상 다운로드된 인기 카메라 앱이다.

직장인 ㄱ씨는 9일 한겨레와 온라인 메신저 대화를 통해 “앱을 사용하다 수치심을 느낄 줄 몰랐다. 너무 불쾌하고 정신적 충격이 크다”고 호소했다. 그는 지난 4일 소다 앱의 유료 서비스인 ‘인공지능 배경 확장’ 기능을 자신의 증명사진에 적용했다. 어깨 부분 중간에 잘린 증명사진을 상반신 전체가 나오는 모습으로 보정하려는 의도였는데, 실제 인공지능이 생성한 결과물에선 자신이 가슴을 양손으로 움켜쥐고 있는 듯한 모습이 나왔다. 이 이미지를 제외한 다른 나머지 결과에선 정상적인 사진이 나왔지만, ㄱ씨는 앱을 사용하다 갑자기 받은 이미지의 충격에서 벗어나기 힘들었다고 했다.

이에 대해 스노우 쪽은 “인공지능 기술이 적용된 서비스의 특성상 결과물이 예상치 못한 형태로 구현된 것”이라고 설명했다. 인공지능이 생성한 이미지를 사용자에게 최종적으로 노출하기 전 필터 기술을 통해 모욕적이거나 선정적인 이미지를 최대한 제거하고 있지만, ㄱ씨의 사례에선 이 기능이 완벽하게 작동하지 않았다고도 설명했다.

하지만 문제가 간단치 않다는 게 전문가들의 지적이다. 소다 앱에 적용된 인공지능 이미지 생성 엔진인 ‘스테이블 디퓨전’ 자체에 문제가 있다는 이유에서다. 스테이블 디퓨전은 영국 스타트업 ‘스태빌리티 에이아이(AI)’가 개발을 주도한 모델인데, 개발 단계에서 음란물을 학습 데이터에 포함시킨 것으로 알려져 있다. 김명주 서울여대 교수(정보보호학)는 “다른 인공지능 모델과 달리 스테이블 디퓨전은 그래픽 이미지를 생성하기 위한 목적으로 포르노 영상물을 학습 데이터에 포함했기 때문에 공개될 때부터 많은 우려가 제기됐다”고 말했다.

전문가들은 소다 앱의 이용자 연령을 제한하는 등의 방식으로 기업의 무책임한 상업화를 막아야 한다고 지적했다. 현재 소다 앱은 3살 이상이면 누구나 사용할 수 있다. 장여경 정보인권연구소 상임이사는 “성착취물로 연결되지 않는다고 해도 인공지능 도구로 정신적 피해를 입은 소비자들이 서비스를 출시한 기업에 대해 최소한의 주의 의무를 요구할 수 있어야 한다”며 “‘현재 기술로는 막을 수 없다’는 스노우의 태도는 무책임하다”고 꼬집었다.

스노우 관계자는 한겨레에 “인공지능을 활용하는 모든 회사가 이번과 같은 이슈를 해결하기 위해 분투하고 있다. 유사한 사례가 발생하지 않도록 필터를 더욱 강화하는 등 서비스 고도화를 노력하겠다”고 했다.

#South korea #deepfake crimes #naver #snow app #soda app #Beauty filter app #Ai filter #deepfake ai #stable diffusion

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businesscommunicationposts · 19 days

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AI Image Generation Today

Today, AI image generation capabilities have advanced significantly. Leading models like DALL-E 3, Midjourney, and Stable Diffusion continue to produce increasingly realistic and creative images from text prompts. These systems can generate a wide array of styles, from photorealistic scenes to abstract art, and have become valuable tools for artists, designers, and content creators. Recent improvements focus on enhancing image quality, increasing resolution, and providing better control over specific elements within generated images. Some models now offer features like outpainting (extending images beyond their original borders) and inpainting (selectively modifying parts of an image). The integration of AI image generation into popular software and platforms has accelerated its adoption. Many graphic design tools, social media apps, and content creation platforms now incorporate some form of AI image generation, making the technology accessible to a broader audience. Ethical and legal concerns surrounding AI-generated images persist, particularly regarding copyright issues, potential misuse for creating deepfakes, and the impact on human artists and photographers. Efforts to address these concerns include developing better detection methods for AI-generated images and establishing clearer guidelines for their use and attribution. Research continues in areas such as multimodal AI, which combines text, image, and sometimes audio understanding to create more context-aware and sophisticated image generation systems. There's also ongoing work to reduce computational requirements, making high-quality AI image generation more efficient and accessible on consumer-grade hardware. While AI image generation has made remarkable strides, it still has limitations. Complex scenes, consistent text rendering, and accurate human anatomy remain challenging in some cases. However, the rapid pace of development suggests further improvements will occur in the near future. See the brochure for Excellence in Business Communication, 14th Edition: https://lnkd.in/eCSg9rv6. Video: https://lnkd.in/eJE9K28f. How Does Your Text Compare? https://lnkd.in/et2Mvp9v. To request examination copies of Bovee and Thill's award-winning business communication textbooks (instructors only), visit https://lnkd.in/bvxGGmT.

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jcmarchi · 1 month

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Black Forest Labs

New Post has been published on https://thedigitalinsider.com/black-forest-labs/

Black Forest Labs

The startup powering image generation for xAI’s Grok.

Image Credit: Black Forest Labs

Next Week in The Sequence:

Edge 425: Our series about SSMs dives into Mamba, the best known SSM model. We review the original Mamba paper by Carnegie Mellon University and Princeton and dive into the GridTape framework for building LLM apps.

Edge 426: We discuss Gemma Scope and ShieldGemma, two new tools for interpretability and guardrailing released by Google DeepMind.

You can subscribe to The Sequence below:

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📝 Editorial: Black Forest Labs

One of the ideas I like about The Sequence is that it helps bring awareness to AI labs that may not have the media profile or the billions in fundraising of the big AI incumbents but are truly doing unique work in AI research. Today, I’d like to talk about a small startup called Black Forest Labs, which is loaded with world-class AI talent. Even though you might not have heard of Black Forest Labs, there’s a chance you’ve interacted with their work.

Have you used xAI’s Grok’s new image generation features in X? If so, then you’ve been using Black Forest Labs’ models. Grok-2’s new image generation capabilities are powered by a model called FLUX.1, created by Black Forest Labs. Who are these guys? Well, what if I told you that they are part of the team behind the famous Stable Diffusion model and also contributed to research breakthroughs like VQGAN and Latent Diffusion?

Black Forest Labs’ main model is FLUX, which comes in three main variants:

FLUX.1 [schnell]: The fastest model, mostly used for local development and personal use.

FLUX.1 [dev]: An open-weight model for non-commercial usage.

FLUX.1 [pro]: The largest, state-of-the-art image generation model available via APIs.

The company recently raised $31 million from marquee firms like Andreessen Horowitz and General Catalyst, with participation from renowned angel investors such as Michael Ovitz and Gary Tan. Given their research talent, top-tier backers, and partnership with xAI, Black Forest Labs is one of the new startups likely to make some noise in the near future. For now, Grok-2 images are incredibly entertaining.

🔎 ML Research

Phi 3.5

Microsoft published the technical report around Phi 3.5 family of small language models. The new release includes Phi-3.5-MoE as well as new versions of Phi-3.5-mini, Phi-3.5-vision —> Read more.

FermiNet

Google DeepMind published a paper discussing FermiNet, a neural network architecture that can solve fundamental equations of quantum mechanics. FermiNet is the first neural network applied to computing the energy of atoms and molecules —> Read more.

DeepSeek-Prover-V1.5

DeepSeek-AI published a paper unveileing DeepSeek-Prover-V1.5, an LLM optimized for theorem proving. The model uses DeepSeekMath-Base as a baseline and fine-tunes it in theorem proving adn proof generation usign reinforcement learning —> Read more.

xGen-MM (BLIP-3)

Salesforce Research published a paper introducing xGen-MM, also known as BLIP-3, a framework for developing multimodal LLMs. The model showcases strong in-context learning capabilities and includes versions fine-tuned for instructions and safety —> Read more.

Hermes 3

Nous Research published the technical report behind its Hermes 3 family of models specialized in reasoning and creative capabilities. Hermes 3 scales up to 405B parameters and leverages a 128k context windows —> Read more.

Speculative RAG

Google Research published a paper detailing Speculative RAG, a technique that tries to address the effectiveness vs. efficiency dilemma in RAG solutions. The method uses a RAG fine-tuned LLM to complement a generalist LLM in RAG workflows —> Read more.

🤖 AI Tech Releases

Jamba 1.5

AI21 released Jamba 1.5, an SSM-Transformer model that enables long context handling capabilities —> Read more.

NVIDIA Llama-3.1 Minitron

NVIDIA open sourced Minitron, an 4B and 8B distilled versions of Llama 3.1 —> Read more.

🛠 Real World AI

Google AI Edge’s MediaPipe

Google provided a deep dive into the techniques for serving 7B parameter models in the browser —> Read more.

AI Infrastructure Videos

The videos from the @Scale AI infrastructure conference are now online —> Read more.

📡AI Radar

MidJourney released a new web experience for its image generation models.

OpenAI established a partnership with Conde Nast.

AI ERP platform Opkey raised a $47 million Series B.

AI-blockchain startup Story raised $80 million in a new round.

AI construction platform Trunk Tools raised a $20 million Series A.

Payments for AI agents platform Skyfire Systems, raised $8.5 million in a new round.

Dropbox acquired AI scheduling tool Reclaim.ai.

xAI started using SGLang for Grok 2 and became 2x faster.

Vectara released Portal, a new no-code interface for creating generative AI applications.

AI-legend Andrew Ng is transitioning to executive chairman in its role at Landing AI.

AI agent for business travel Otto raised $6 million.

Boston Dynamics new Atlas can do push ups.

AI ad platform Creatory raised a $10 million Series A.

Tidal, Google’s AI agriculture spinoff, raised new funding for its expansion plans.

AI fintech platform Magie raised $4 million.

LambdaTest introduced Kane AI, an AI testing assistant.

TheSequence is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

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marketingprofitmedia · 2 months

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Note: This is a paid software, but the one-time fee is $17 for lifetime

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juealhossain · 2 months

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One AI Review: All-In-One Access to Premium AI Tools

Welcome to our comprehensive review of Premium AI. In this article, we'll explore the amazing features and benefits of One AI, a revolutionary platform that offers access to the world's most advanced AI tools from a single dashboard.

What is One AI?

One AI is a never-seen-before app that lets you access the world's leading and most advanced Premium AIs from a single dashboard. This cloud-based platform is designed to help you create world-class content and AI-driven solutions without paying any monthly fees.

Benefits of Using One AI

ChatGPT 4.0 & ChatGPT 4: These AI tools offer advanced reasoning and logic, making them perfect for creating high-quality content.

Gemini Pro: Get AI-driven insights, improved text-to-image coherence, and enhanced realism with this powerful tool.

DALL.E 3: Generate high-quality images with improved understanding and generation capabilities.

Leonardo AI: Enjoy improved inpainting and efficient processing for creating ultra-HD 8K AI videos and realistic paintings.

Microsoft Copilot Pro: Write HTML, CSS, and programming codes easily with this leading AI tool.

Meta Llama 3: Translate any language and get answers to complex questions with this advanced AI.

Why Choose One AI?

One AI offers an array of benefits that make it a must-have tool for freelancers, businesses, and AI enthusiasts. Here are some of its amazing benefits:

ChatGPT 4.0 & ChatGPT 4: AI-powered advanced Premium AI's with improved text-to-image coherence and diverse AI models.

Gemini Pro: AI-driven insights with enhanced realism, high resolution, and advanced reasoning.

DALL.E 3: High-quality image generation with multimodal capabilities and advanced understanding of context.

Leonardo. AI: Improved inpainting, efficient processing, and enhanced AI capabilities.

Microsoft Copilot Pro: Enhanced AI capabilities available in multiple languages ensuring data integrity and protection.

Meta Llama 3: Advanced capabilities improving computational efficiency with enhanced realism and multimodal abilities.

How Does One AI Work?

Using One AI is simple and straightforward. Follow these three easy steps to get started:

Give keyword or prompt commands to create Premium AIs.

Publish and profit.

Key Features of One AI

One AI is packed with features that make it the ultimate tool for creating AI content and skyrocketing your business. Here are some key features:

World's 1st cloud-based AI app supercharged with the world's Premium AI apps in a single dashboard.

Stop paying any monthly fees on expensive AI tools and apps.

Start your very own monthly-based AI subscription platform and charge any amount.

Access the most advanced Premium 8 AI apps - ChatGPT 4, Gemini Pro, DALL E 3, Leonardo AI, Copilot Pro, Meta Llama 3, Stable Diffusion, and PaLM 2 - with zero monthly fees.

Create world-class content and sales copies using the Premium version of ChatGPT 4.

Craft stunning 4K HD AI images and art using Open AI’s Premium “DALL E” AI.

Create ultra-HD 8K AI videos and realistic paintings using the Premium version of Leonardo AI.

Write high-in-demand HTML, CSS, and programming codes using Microsoft’s leading AI “Copilot Pro.”

Translate any language and get answers to your complex questions with Meta’s most advanced Premium AI “Llama 3.”

Transform text into stunning AI images and realistic portraits using Stable Diffusion XL AI.

Develop powerful AI tools and apps using Google’s revolutionary AI Palm 2.

Live chat with AI assistants and get answers to all your questions in real-time.

Save over $12,717 annually without having to pay any amount on Premium AIs.

AI-driven live chat support for real-time assistance.

Fire all your expensive tools and services.

Say goodbye to monthly fees.

Commercial license included - create and sell as many assets as you like to your clients.

Newbie-friendly, easy-to-use dashboard.

Iron-clad 30-day money-back guarantee.

Who Needs One AI?

One AI is perfect for anyone looking to leverage the power of AI to boost their business. Here are some specific use cases:

Freelancers who want to create high-quality content for their clients.

Businesses looking to automate their content creation process.

AI enthusiasts who want to experiment with different AI models.

Developers who need powerful AI tools for coding and app development.

Marketing professionals who need to create engaging and high-converting sales copies.

Artists who want to create stunning AI-generated images and videos.

Language translators who need accurate and fast translations.

Frequently Asked Questions

What Is Premium Ai?

Premium AI refers to advanced, high-quality artificial intelligence tools offering superior performance and features.

How Does Premium Ai Improve Productivity?

Premium AI automates tasks, enhances accuracy, and provides valuable insights, significantly boosting productivity and efficiency.

Can I Access Multiple Ai Tools In One Platform?

Yes, One AI offers access to multiple premium AI tools from a single, user-friendly dashboard.

What Are The Benefits Of Using Premium Ai?

Premium AI offers advanced reasoning, high-resolution outputs, and enhanced realism, making it ideal for various applications.

How Does One Ai Ensure Data Security?

One AI ensures data integrity and protection, complying with industry standards for security and privacy.

Conclusion

One AI is a game-changer in the world of AI. It offers access to the most advanced AI tools from a single dashboard, eliminating the need for multiple subscriptions. Whether you're a freelancer, business owner, or AI enthusiast, One AI has something to offer you. Don't miss this life-changing opportunity to start profiting like never before.

To learn more about One AI and start your journey with Premium AI, visit One AI.

#oneai #oneaiapp #Premium Ai #chatgpt4

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govindhtech · 3 months

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The NVIDIA Canvas App: An Introduction Guide to AI Art

NVIDIA Canvas App

This article is a part of the AI Decoded series, which shows off new RTX PC hardware, software, tools, and accelerations while demystifying AI by making the technology more approachable.

AI has totally changed as a result of generative models, which are highlighted by well-known apps like Stable Diffusion and ChatGPT.

Foundational AI models and generative adversarial networks (GANs) spurred a productivity and creative leap, paving the stage for this explosion.

One such model is NVIDIA’s GauGAN, which drives the NVIDIA Canvas app and use AI to turn crude sketches into stunning artwork.

NVIDIA Canvas

AI may be used to create realistic landscape photographs from basic brushstrokes. Make backgrounds fast, or explore concepts more rapidly so you may devote more time on idea visualisation.

Utilise AI’s Potential

Utilise a palette of realistic elements, such as grass or clouds, to paint basic forms and lines. Next, observe in real time how the screen is filled with jaw-dropping outcomes thanks to NVIDIA’s ground-breaking AI model. Dislike what you observe? Change the material from snow to grass, and observe how the whole scene transforms from a wintry paradise to a tropical paradise. There are countless innovative options.

Adaptable Styles

With NVIDIA Canvas app, you can alter your image to precisely what you require. Using nine Standard Mode styles, eight Panorama Mode styles, and a variety of materials from sky and mountains to rivers and stone you may alter the appearance and feel of your painting. Additionally, you can paint on many levels to distinguish distinct elements. One of the included sample scenarios can serve as inspiration, or you can start from scratch.

A Whole 360° Inspiration

With the addition of 360° panoramic functionality, artists can now quickly construct wraparound environments with Canvas and export them as equirectangular environment maps into any 3D application. These maps can be used by artists to alter the surrounding lighting in a 3D scene and add reflections for more realism.

Save as PSD or EXR

After you’ve produced the perfect image, Canvas allows you to upload it into Adobe Photoshop for further editing or blending with other pieces of art. Additionally, pictures can be imported into Blender, NVIDIA Omniverse USD Composer (previously Create), and other 3D programmes using Panorama.

How Everything Started

A generator and a discriminator are two complementing neural networks used in deep learning models called GANs.

There is competition between these neural networks. While the discriminator strives to distinguish between created and actual imagery, the generator aims to produce realistic, lifelike imagery. GANs get increasingly adept at producing realistic-looking samples as long as their neural networks continue to challenge one another.

GANs are excellent at deciphering intricate data patterns and producing output of the highest calibre. Applications for them include data augmentation, style transfer, image synthesis, and picture-to-image translation.

NVIDIA’s AI demonstration for creating lifelike images is called GauGAN, after the post-Impressionist painter Paul Gauguin. Developed by NVIDIA Research, it served as a direct inspiration for the creation of the NVIDIA Canvas app and is available for free download via the NVIDIA AI Playground.

NVIDIA AI Playground

Use NeVA to Unlock Image Insights

A multimodal vision-language model called NVIDIA NeMo Vision and Language Assistant (NeVA) can comprehend text and images and provide insightful answers.

Create Text-Based Images with SDXL

With shorter prompts, Stable Diffusion XL (SDXL) enables you to create expressive visuals and add text to photos.

Handle AI Models Real-Time

With the AI Playground on NGC, you can easily experiment with generative AI models like NeVA, SDXL, Llama 2, and CLIP right from your web browser thanks to its user-friendly interface.

Since its 2019 NVIDIA GTC premiere, GauGAN has gained enormous popularity and is utilised online by millions of people in addition to art educators, creative agencies, and museums.

Adding Sketch to Gogh’s Scenery

With the help of GauGAN and nearby NVIDIA RTX GPUs, NVIDIA Canvas app employs AI to convert basic brushstrokes into lifelike landscapes, with real-time outcomes displayed.

Using a palette of real-world objects like grass or clouds referred as in the app as “materials” users can begin by drawing basic lines and shapes.

The improved image is then produced in real time by the AI model on the other side of the screen. A few triangle shapes drawn with the “mountain” material, for instance, will appear as an amazing, lifelike range. Alternatively, users can choose the “cloud” material and change the weather from sunny to cloudy with a few mouse clicks.

There are countless innovative options. Draw a pond so that the water will reflect other visual features like the rocks and trees. When the material changes from snow to grass, the scene becomes a tropical paradise instead of a warm winter’s environment.

With Canvas’s Panorama mode, artists may produce 360-degree pictures that can be used in 3D applications. Greenskull AI, a YouTuber, painted a cove in the ocean to illustrate Panorama mode before importing it into Unreal Engine 5.

Read more on Govindhtech.com

#nvidiacanvasapp #aimodel #chatgpt #nvidia #NVIDIAOmniverse #nvidianemo #aiplayground #Llama2 #nvidiagtc #nvidiartxgpus #artificialintelligence #news #technews #technology #technologynews #technologytrends #govindhtech

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secourses · 3 months

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Zero to Hero Stable Diffusion 3 Tutorial with Amazing SwarmUI SD Web UI that Utilizes ComfyUI

Zero to Hero Stable Diffusion 3 Tutorial with Amazing SwarmUI SD Web UI that Utilizes ComfyUI : https://youtu.be/HKX8_F1Er_w

youtube

Do not skip any part of this tutorial to master how to use Stable Diffusion 3 (SD3) with the most advanced generative AI open source APP SwarmUI. Automatic1111 SD Web UI or Fooocus are not supporting the #SD3 yet. Therefore, I am starting to make tutorials for SwarmUI as well. #StableSwarmUI is officially developed by the StabilityAI and your mind will be blown after you watch this tutorial and learn its amazing features. StableSwarmUI uses #ComfyUI as the back end thus it has all the good features of ComfyUI and it brings you easy to use features of Automatic1111 #StableDiffusion Web UI with them. I really liked SwarmUI and planning to do more tutorials for it.

🔗 The Public Post (no login or account required) Shown In The Video With The Links ➡️ https://www.patreon.com/posts/stableswarmui-3-106135985

0:00 Introduction to the Stable Diffusion 3 (SD3) and SwarmUI and what is in the tutorial 4:12 Architecture and features of SD3 5:05 What each different model files of Stable Diffusion 3 means 6:26 How to download and install SwarmUI on Windows for SD3 and all other Stable Diffusion models 8:42 What kind of folder path you should use when installing SwarmUI 10:28 If you get installation error how to notice and fix it 11:49 Installation has been completed and now how to start using SwarmUI 12:29 Which settings I change before start using SwarmUI and how to change your theme like dark, white, gray 12:56 How to make SwarmUI save generated images as PNG 13:08 How to find description of each settings and configuration 13:28 How to download SD3 model and start using on Windows 13:38 How to use model downloader utility of SwarmUI 14:17 How to set models folder paths and link your existing models folders in SwarmUI 14:35 Explanation of Root folder path in SwarmUI 14:52 VAE of SD3 do we need to download? 15:25 Generate and model section of the SwarmUI to generate images and how to select your base model 16:02 Setting up parameters and what they do to generate images 17:06 Which sampling method is best for SD3 17:22 Information about SD3 text encoders and their comparison 18:14 First time generating an image with SD3 19:36 How to regenerate same image 20:17 How to see image generation speed and step speed and more information 20:29 Stable Diffusion 3 it per second speed on RTX 3090 TI 20:39 How to see VRAM usage on Windows 10 22:08 And testing and comparing different text encoders for SD3 22:36 How to use FP16 version of T5 XXL text encoder instead of default FP8 version 25:27 The image generation speed when using best config for SD3 26:37 Why VAE of the SD3 is many times better than previous Stable Diffusion models, 4 vs 8 vs 16 vs 32 channels VAE 27:40 How to and where to download best AI upscaler models 29:10 How to use refiner and upscaler models to improve and upscale generated images 29:21 How to restart and start SwarmUI 32:01 The folders where the generated images are saved 32:13 Image history feature of SwarmUI 33:10 Upscaled image comparison 34:01 How to download all upscaler models at once 34:34 Presets feature in depth 36:55 How to generate forever / infinite times

37:13 Non-tiled upscale caused issues 38:36 How to compare tiled vs non-tiled upscale and decide best 39:05 275 SwarmUI presets (cloned from Fooocus) I prepared and the scripts I coded to prepare them and how to import those presets 42:10 Model browser feature 43:25 How to generate TensorRT engine for huge speed up 43:47 How to update SwarmUI 44:27 Prompt syntax and advanced features 45:35 How to use Wildcards (random prompts) feature 46:47 How to see full details / metadata of generated images 47:13 Full guide for extremely powerful grid image generation (like X/Y/Z plot) 47:35 How to put all downloaded upscalers from zip file 51:37 How to see what is happening at the server logs 53:04 How to continue grid generation process after interruption 54:32 How to open grid generation after it has been completed and how to use it 56:13 Example of tiled upscaling seaming problem

1:00:30 Full guide for image history 1:02:22 How to directly delete images and star them 1:03:20 How to use SD 1.5 and SDXL models and LoRAs 1:06:24 Which sampler method is best 1:06:43 How to use image to image 1:08:43 How to use edit image / inpainting 1:10:38 How to use amazing segmentation feature to automatically inpaint any part of images 1:15:55 How to use segmentation on existing images for inpainting and get perfect results with different seeds 1:18:19 More detailed information regarding upscaling and tiling and SD3 1:20:08 Seams perfect explanation and example and how to fix it 1:21:09 How to use queue system 1:21:23 How to use multiple GPUs with adding more backends 1:24:38 Loading model in low VRAM mode 1:25:10 How to fix colors over saturation 1:27:00 Best image generation configuration for SD3 1:27:44 How to apply upscale to your older generated images quickly via preset 1:28:39 Other amazing features of SwarmUI 1:28:49 Clip tokenization and rare token OHWX

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jason23016 · 5 months

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AI Revolution: 3D Art Enhancements, ChatGPT Earbuds, and Stable Diffusion 3 API Launch

Blockade Labs improves quality AI-generated 3D art for 360-degree apps

AI News Blockade Labs has announced significant updates to its Skybox AI, enhancing its capability as the leading platform for creating 360-degree AI-generated environment art. With these updates, Skybox AI now supports 8K resolution, providing even higher-quality visuals for immersive applications. This upgrade makes it ideal for use with advanced mixed-reality headsets like the Apple Vision Pro. Marguerite deCourcelle, CEO of Blockade Labs, shared these insights in an interview with GamesBeat, where she is also slated to speak at the upcoming GamesBeat Summit 2024. She highlighted the technological advancements in Skybox AI, which now includes features such as remix, sketch-to-skybox, depth maps, HDRIs, and the conversion of skyboxes to 3D mesh, enhancing the platform’s versatility and user engagement. Since its initial launch a year ago, Skybox AI has been adopted by over 1.5 million users across various industries, including entertainment, gaming, VR, and education, generating more than 10 million Skyboxes. Major corporations like NVIDIA, Accenture, and T-Mobile have utilized this technology for product demonstrations, showcasing its wide-ranging applicability. The latest Model 3 update of Skybox AI not only enhances the visual fidelity of the skyboxes but also integrates new artistic styles and functionalities, allowing creators to produce and download art in 8K quality. This significant resolution upgrade, representing a 77% increase in pixels over the previous model, positions Skybox AI as a crucial tool for developers creating applications for the Apple Vision Pro and similar platforms. DeCourcelle, who has a background in both fine arts and cryptocurrency, also discussed her journey from creating crypto-puzzles to founding Blockade Labs. The company aims to simplify the creation of complex art assets that are typically challenging and time-consuming to produce, thus addressing the ongoing shortage of artists and technical challenges in the industry. Looking ahead, Blockade Labs plans to integrate Skybox AI more extensively with major platforms like Unity to expand its reach and utility. This strategic direction is aimed at supporting metaverse companies and other users who require robust, creative tools to develop immersive and interconnected digital worlds efficiently. With its commitment to innovation and user-centric design, Blockade Labs continues to lead in the field of generative AI for 3D art, providing scalable and customizable solutions that revolutionize how digital environments are created and experienced. SOURCE

ChatGPT is a squeeze away with Nothing’s upgraded earbuds

AI News Nothing has released new earbuds, with some interesting adjustments to their selection. The Nothing Ear (a) is the spiritual heir to the Nothing Ear Stick, while the recently released Nothing Ear updates the Nothing Ear (2). The incorporation of ChatGPT inside the earphones, however, is the centerpiece of today’s announcement. The London-based startup made a risky decision by integrating ChatGPT right into its most recent earbuds, eschewing the usual AI smartphone competitors. Pinching the earphones’ stem to communicate with the AI is now possible for users of the ChatGPT app on a connected Nothing device. This is comparable to using voice assistants like Siri or Google Assistant. Furthermore, Nothing is using Nothing OS’s system-level ChatGPT functionality to improve the user experience on Nothing handsets. This allows integrating widgets with a distinctive Nothing style and instantly sending screenshots to ChatGPT. The new earbuds will be the only ones with these features, raising the bar for AI-integrated personal audio devices. The new Nothing Ear and Ear (a) earphones with major improvements are now available for preorder. Thanks to an upgraded driver technology, the new Ear Buds provide better audio quality and up to 25% longer battery life than their predecessors, the Ear (2). A “smart” active noise-canceling system that dynamically adapts to ambient noise levels and detects fit leakage between the ear canal and the buds is included with them. In the meantime, Ear (a) deviates from the standard black and white designs of earlier versions by sporting a vivid yellow coloring that draws attention to its enhanced noise-canceling capabilities. The Ear retails for $149, while the Ear (a) is priced competitively at $99. For both, shipping begins on April 22nd SOURCE

Stable Diffusion 3 API is Now Available

AI News We’re excited to launch Stable Diffusion 3 and its Turbo variant on the Stability AI Developer Platform API. According to our latest research, Stable Diffusion 3 matches or surpasses leading text-to-image generators like DALL-E 3 and Midjourney v6 in typography fidelity and prompt compliance, based on user preferences. This version introduces the Multimodal Diffusion Transformer (MMDiT) architecture, which enhances text comprehension and spelling by utilizing distinct weight sets for image and language processing, an improvement over previous iterations. Available now via API, we are dedicated to refining this model before its broader release. Consistent with our open AI ethos, we plan to provide model weights for self-hosting to Stability AI Members in the near future. For details on deployment, please contact us directly. To begin using Stable Diffusion 3 API, check out our documentation page. Additionally, we are offering a limited number of spots for early access to our Stable Assistant Beta, which integrates our latest image and language models for advanced content creation.

Performance

AI News We’re thrilled to announce our partnership with Fireworks AI, renowned for being the quickest and most reliable API platform available. Together, we are offering Stable Diffusion 3 and Stable Diffusion 3 Turbo through an enterprise-grade API solution that guarantees 99.9% service availability. This robust reliability is vital for enterprises that depend on our developer platform for their critical generative AI workloads, ensuring our customers can confidently execute their mission-critical tasks.

Safety

At Stability AI, we are committed to safe and responsible AI practices. From the onset of training our model to testing, evaluation, and deployment, we ensure rigorous steps are taken to prevent misuse of Stable Diffusion 3 by malicious actors. Our commitment to safety is reinforced through ongoing collaborations with researchers, experts, and the community, fostering innovation with integrity as we enhance the model. Stable Diffusion 3 is designed to provide flexible solutions that empower individuals, developers, and enterprises to maximize their creative potential, fully aligning with our mission to unlock human possibilities. SOURCE

Conclusion:

Blockade Labs, Nothing, and Stability AI are spearheading transformative innovations in their respective fields. Blockade Labs continues to redefine immersive environment creation with Skybox AI, while Nothing integrates cutting-edge AI in personal audio devices, and Stability AI enhances image generation with Stable Diffusion 3. These advancements demonstrate the dynamic integration of AI technologies, pushing the boundaries of creativity, efficiency, and user engagement across diverse sectors. Stay connected with Arcot Group for more AI News into how such collaborations are reshaping the tech landscape and paving the way for future innovations. For further reading on similar breakthroughs and the impact of AI and robotics, explore our blog.

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newsblog12 · 5 months

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AI Revolution: 3D Art Enhancements, ChatGPT Earbuds, and Stable Diffusion 3 API Launch

Blockade Labs improves quality AI-generated 3D art for 360-degree apps

ChatGPT is a squeeze away with Nothing’s upgraded earbuds

Stable Diffusion 3 API is Now Available

Performance

Safety

Conclusion:

#artificial intelligence #app development #python #AI #Arcot Group

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perfectiongeekstech · 6 months

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#snapseed qrcodes #blockchain development

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infoshakil260 · 8 months

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The "wonderful duck" priced at 9 yuan won't fly for long.

Recently, an AI application called Miaoya Camera has become popular due to its unique gameplay. Photos generated by it can be seen on social media, and have aroused intense discussions among users. So can Miaoya Camera maintain its popularity and continue to develop? Let’s take a look at how the author analyzes it.

Even if you can't fly, at least you have flown.

If your circle of friends is flooded with various photos of "friends", don't panic. For only 9 yuan, 9 yuan, the price of a cup of Luckin coffee, you can have a complete set.

If you prefer to drink a glass of Luckin, or you really can’t find 20 personal selfies as material, don’t panic, because this small program that “generates professional-quality blockbusters online” shouldn’t be popular for long.

"Miaoya Camera" suddenly became popular, and many people used it to create various personal portraits - business style, ancient costume style, Japanese campus style. Because there were so many people experiencing it, “the server was overcrowded.”

This application is not complicated to operate. Upload about 20 personal selfies, choose a template to determine the style, and then wait for AI to generate it. I won’t go into details about the specific film production effects here. If you search for “Miaoya” in your circle of friends, there should be case studies.

What deserves more attention is that this is an AI application. To be precise, this is the first domestic consumer-oriented, paid, screen-swiping AI application.

This is amazing. Because since AI big models became popular at the beginning of this year, almost all large Internet companies are working on AI and throwing money into it. However, there has never been a product that ordinary people can easily get started with and use on a large scale - Baidu's Wen Xin Yi Yan and Alibaba's Tong Yi Qian Wen. These chat robots are not open to the public; Huawei's Pangu model, Tencent's The Hunyuan model is for B-side enterprises and has nothing to do with ordinary people.

But Miaoya is changing this situation, and it comes with a fee.

9 yuan may not seem like much, but almost all similar photo apps that appeared in the past were free at the beginning - Face Meng, ZAO, etc. were all very popular, and no one charged money right away.

While Miaoya is generating photos for users, it is also slapping investors in the face: “Who said big AI models don’t make money?”

This makes the wonderful duck a good research sample. Although a flash in the pan is almost inevitable, it still brings inspiration to AI entrepreneurs.

1. AI photo-taking starts with "alchemy"

Before discussing Miaoya, we first zoomed in on "Little Book", where a bunch of people were showing "alchemy".

The so-called "refining elixir" does not mean refining the elixir of life, but training an AI model. The process of "alchemy" relies heavily on the graphics card. The computer is running at full speed and may take dozens of hours at a time, hence the name "alchemy".

What about making alchemy? ——Use AI to generate high-quality portraits.

After AI painting became popular, the foreign open source Stable Diffusion model (hereinafter referred to as "SD") and Midjourney, which ordinary people can use, began to be used by more people. These two software are extremely powerful and produce stunning photo effects. In particular, the SD model is now the underlying technical support for many Vincentian graph applications.

Some "crab-loving" people grabbed early bird tickets and used SD and Midjourney to first generate cartoon-style avatars for themselves, then try to generate more realistic real-person avatars, and then unlock more complex scenes and generate some real-life avatars. A blockbuster film that cannot be shot anywhere else in the world.

Before Miaoya appeared, some people had already changed their WeChat avatars to AI portraits. There are also some people who have turned this skill into a business - teaching others AI portraits, or customizing AI portraits for others. The price of customized photos ranges from more than ten yuan to dozens of yuan.

A group of wild "alchemists" have embarked on a vigorous journey of training AI.

The "Little Fairy's Tool Man" (for the sake of memory, let's call him "Gong Juren") started thinking about and tinkering with some programs in May, and then made his own LoRA model. It took him more than half a month to make a LoRA model for his wife using hundreds of real photos. In early June, he used the model to generate the first AI photo.

LoRA model, you can understand it as a plug-in, which can customize and fine-tune the SD large model. It requires only a small amount of data to train the style and characteristics of the model.

For example, the beautiful girl AI pictures that were very popular in the first half of the year were created by someone using the avatars of Japanese and Korean beautiful girls to train the corresponding LoRA model. Other developers could quickly generate beautiful girl-style photos after taking them.

Using SD as the bottom layer and LoRA to make elixirs, this method is used by many developers. The technologies and codes involved are basically open source. The threshold for AI photography has been lowered in the first half of the year.

Gong Guren is not a computer major, nor is he engaged in AI-related work. Before doing AI portraits, his only foundation was a little Python, which he learned by himself. The starting point for him doing this is to take good-looking photos of his wife. He used to use a camera, but now he uses AI.

He told Dingjiao that he paid attention to Miaoya as soon as it went online on July 17. He believes that Miaoya's product implementation method is the same as what he does.

"It should be made by SD. Combined with LoRA character models, several character templates are fixed, allowing users to upload 20 photos to practice LoRA, and then use the generated LoRA to insert them into the templates made in the large model to change faces." Gong Ju Ren analysis.

Many investors who follow the AI track also believe that Miaoya’s technical principle is SD+LoRA.

Wang Sheng, managing partner of Inno Angel Fund, analyzed "Fixed Focus", "I guess Miaoya uses the SD open source model, and then adds a stylized training data set like LoRA. They train each person individually a small LoRA , and then fade various background content.”

Some investors told "Dingjiao" that Miaoya is "the bottom layer of LoRA alchemy + scene prompt words". Because 20 photos are the basic amount of data used to train LoRA.

Miaoya has made templates for portrait scenes, such as workplace, emotions, Jiangnan, spring, etc. Users click to select the scene, which is similar to inputting prompt words to AI to determine the photo style. After the user uploads 20 photos, the system begins to train the personal LoRA, which is what Miaoya calls a digital clone.

Based on the opinions of many investors and practitioners, Miaoya’s AI portrait is not difficult to implement and the technical threshold is not high.

2. Is the price of a cup of Luckin worth it?

Although there is no technical threshold, there is still a threshold for using Miaoya.

In fact, Miaoya’s user experience is not very good.

First of all, they have to provide more than 20 selfies, which dissuades a large group of straight men; secondly, you have to queue up to generate photos, and you have to wait for more than ten hours when there are many people; in addition, it charges 9 yuan and 9 yuan; you have to download For high-definition and uncensored photos, you have to recharge to buy diamonds; if you are not satisfied with the generated photos, we will not refund you.

As a C-end product, it almost sets up obstacles in every aspect that users are sensitive to.

Why does Miaoya dominate the screen? Just because it's a large model?

"They went in the right direction and captured the strongest point of user demand. The product actually has a threshold. This is a matter of product and operations." Wang Sheng said.

From the product perspective, in the direction of personal avatars, we have seen too many similar products in history. Ten years ago, Mian Meng focused on generating personal cartoon images. Later, the WeChat Christmas avatar became popular in WeChat Moments, and the face-swapping app ZAO incubated by Momo all captured the needs of users.

For users, whether the pictures are fresh and fun, or whether they use pictures to socialize and satisfy certain psychological needs, the underlying logic is similar.

When it comes to AI photography, the demand has already existed.

In December last year, Lensa, an overseas AI photo-taking app, became popular. Its gameplay is to allow users to upload about 20 personal photos, and AI will generate different styles of avatars or portraits for a fee. The painting model it uses is SD and the open source dataset LAION-5B. This is strictly speaking the earliest AI photo product to hit the screen.

However, domestic AI photography was mainly popular among the small circles of AI developers and photography enthusiasts before. Ordinary people could not distinguish the concepts of SD and LoRA, let alone get started. Now, through a product, Miaoya has lowered the threshold for ordinary people to use AI photography to zero. This is the prerequisite for Miaoya to become popular.

Miaoya's development team relied on Alibaba Entertainment to promote this product. On some grass-growing platforms, you can see bloggers’ promotional blog posts. "The execution power of large manufacturers is still very strong." Gong Guren commented.

Price is a controversial point.

The common way similar products have been played over the past ten years is to attract users for free first, without considering profits in the short term. As long as the user base increases, there is no need to worry about making money. In other words, swiping the screen is more important than charging.

Miaoya charges fees when it launches, and will add items later, which will shut out a large number of early adopters.

Some people may say that compared with offline studios such as Tianzhenlan and Haima that charge hundreds of yuan, 9 yuan is too cheap. Yes, it is indeed cheaper, but not everyone goes there just to take ID photos. “I’m just here to have fun, and I still have to charge money?”

It’s not difficult to understand the reason behind Miaoya’s collection of money. It is a recognized fact that large AI models burn money, and the inability to keep up with computing power is a pain for almost all AI companies today.

Gong Juren told "Dingjiao" that SD is an open source technology and the technical barriers are not high. What can be done is to make some optimizations on the algorithm and model.

In addition, the so-called digital avatar is to generate the user character LoRA. This model training takes time. If a large number of users pour in at the same time, the computing power will inevitably be tight, so a large number of users will queue up and wait. And once you start training the model, computing power will be consumed. This is a real cost. Miaoya should have calculated the cost, so you must charge once you use it.

In addition, the pictures generated by Miaoya generally have low pixels. If you need a large high-definition picture, you will need to consume further computing power to enlarge the image, so it costs money to export high-definition pictures.

However, this allowed Miaoya to have monetization capabilities from the beginning, becoming the first C-side monetization application among China’s large models.

Putting aside this meaningless name, the question now facing Miaoya is: How can it remain popular when the technical barriers are not high, the product experience is average, and charges limit dissemination?

3. Is Miaoya really popular?

Before discussing the prospects of Miaoya, let’s answer a question first: Is Miaoya really popular?

In comparison, Face Meng can be called very popular. It once had more than 20 million APP downloads within a week. ZAO also hit the screen. On the second day after it was launched, it rushed to the second place in the entertainment free list of the App Store and remained at the top until it was removed. Lensa dominates the App Store download lists in the United States, Canada, the United Kingdom and other countries, with the highest single-day download volume exceeding 15 million.

How are Miaoya's results?

Miaoya does not have an APP, it is now a mini program. There is a platform in China that specializes in counting the popularity of small programs called Aladdin Index. We did not see Miaoya Camera in Aladdin’s major lists.

The WeChat index shows that the index of Miaoya Camera has been very low for four days after it went online on July 17. It started to rise on the fifth day and reached a peak on July 25. However, starting from July 26, the index turned downward. A sharp decline. Its heat only lasted about a week.

Baidu Index shows that the popularity of Miaoya Camera began to rise on July 23, reaching a peak on July 24, and then began to slowly decline, with the highest peak being less than 8,000. From the perspective of urban distribution, the people paying attention are mainly concentrated in first-tier cities such as Beijing, Shanghai, and Guangzhou.

We can initially draw a conclusion: Miaoya is not considered out of the circle.

"Screening is in the media and related industries, as well as investment and financing." Liu Di, managing director of Shengjing Jiacheng, told "Dingjiao".

Above the threshold of 9 yuan and 9 yuan, the first one didn't hit it. It was very difficult for Miaoya to hit the screen again in the later period.

Gong Juren believes that when drawing full-body photos of people, existing AI models have insufficient pixels allocated to the face, hands and feet, so it is difficult to generate accurate full-body photos at once, and basically require facial restoration plug-ins such as After Detailer. To repair the face or artificially repair the fingers. Therefore, most of Miaoya’s photos are headshots and half-length photos, which focus on highlighting the characters and blurring the background. “This can also easily form a stereotype and lead to aesthetic fatigue. People will get tired of seeing it and it will be boring.”

Miaoya’s “predecessor” Lensa has already given the answer.

According to statistics from data analysis company Sensor Tower, Lensa's downloads began to increase in mid-November last year, reached a peak in mid-December, and fell back to low levels in mid-January this year. The popularity of the entire life cycle lasted only two months. Other head AI+ image applications follow almost the same trajectory.

In comparison, Miaoya is not as popular as Lensa.

Compared with discussions at the functional level, the most discussed aspects of Miaoya in the past few days are two issues that are not very beneficial to the company - data privacy and refund issues.

In Miaoya’s original user service agreement, there was an “overlord clause”. Translated, the personal selfies submitted by users to Miaoya can be used by the Miaoya team without restrictions, and the scope of use even includes virtual spaces such as the Metaverse.

20 personal selfies can completely build a face portrait model. With this model, the platform can generate selfie photos of users in any scene.

Even if the platform does not do evil, it is difficult to avoid being used by people with ulterior motives. "How can Miaoya ensure that there are no private goods in the 20 photos? Now someone has included photos of celebrities in 20 photos in order to make the photos behind them look better. " Liu Di said.

This has caused some users to express concern and ask to cancel their accounts. Now, Miaoya has deleted this clause.

There is also the issue of refunds. According to Miaoya's rules, after the user pays to generate photos, the service is deemed to be completed. Even if the user is not satisfied, there will be no refund.

This rule is not excessive. After all, if you go to a physical store to take pictures, there are very few promises of refunds if you are not satisfied. The difference is that Miaoya's service is template-based. Sometimes the photos generated by AI just don't achieve the desired effect, but you can't negotiate and fine-tune it like you can with a human. It's a bit like a one-shot deal.

Gong Juren analyzed the "fixed focus" and found that there is a problem with the LoRA model. 20 photos are not enough to produce a photo that is the same as my own. Some people will look like some people and some will not.

In response to the issue of refunds, Miaoya also issued a special response. This shows that there are many users who have requests for refunds.

These controversies, while increasing the popularity of Miaoya, are also limiting its popularity.

4. Miaoya’s inspiration for AI entrepreneurship

In any case, Miaoya has become popular in some people’s circle of friends. Today, when the "Battle of 100 Models" is in full swing, there is a product that has hit the screen, which is an encouragement to AI entrepreneurs.

In the wave of mobile Internet entrepreneurship, camera applications were the first to hit the market. Now that we are entering the AI entrepreneurship wave, camera products are also the first to take the lead. The similarity of this path excites some entrepreneurs.

However, investors remain cautiously optimistic.

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roygodfrey · 10 months

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The World Is Running Out of Data to Feed AI, Experts Warn : ScienceAlert

As artificial intelligence (AI) reaches the peak of its popularity, researchers have warned the industry might be running out of training data – the fuel that runs powerful AI systems.

This could slow down the growth of AI models, especially large language models, and may even alter the trajectory of the AI revolution.

But why is a potential lack of data an issue, considering how much there are on the web? And is there a way to address the risk?

Why high-quality data are important for AI

We need a lot of data to train powerful, accurate and high-quality AI algorithms. For instance, ChatGPT was trained on 570 gigabytes of text data, or about 300 billion words.

Similarly, the stable diffusion algorithm (which is behind many AI image-generating apps such as DALL-E, Lensa and Midjourney) was trained on the LIAON-5B dataset comprising of 5.8 billion image-text pairs. If an algorithm is trained on an insufficient amount of data, it will produce inaccurate or low-quality outputs.

The quality of the training data is also important. Low-quality data such as social media posts or blurry photographs are easy to source, but aren't sufficient to train high-performing AI models.

Text taken from social media platforms might be biased or prejudiced, or may include disinformation or illegal content which could be replicated by the model. For example, when Microsoft tried to train its AI bot using Twitter content, it learned to produce racist and misogynistic outputs.

This is why AI developers seek out high-quality content such as text from books, online articles, scientific papers, Wikipedia, and certain filtered web content. The Google Assistant was trained on 11,000 romance novels taken from self-publishing site Smashwords to make it more conversational.

Do we have enough data?

The AI industry has been training AI systems on ever-larger datasets, which is why we now have high-performing models such as ChatGPT or DALL-E 3. At the same time, research shows online data stocks are growing much slower than datasets used to train AI.

In a paper published last year, a group of researchers predicted we will run out of high-quality text data before 2026 if the current AI training trends continue. They also estimated low-quality language data will be exhausted sometime between 2030 and 2050, and low-quality image data between 2030 and 2060.

AI could contribute up to US$15.7 trillion (A$24.1 trillion) to the world economy by 2030, according to accounting and consulting group PwC. But running out of usable data could slow down its development.

Should we be worried?

While the above points might alarm some AI fans, the situation may not be as bad as it seems. There are many unknowns about how AI models will develop in the future, as well as a few ways to address the risk of data shortages.

One opportunity is for AI developers to improve algorithms so they use the data they already have more efficiently.

It's likely in the coming years they will be able to train high-performing AI systems using less data, and possibly less computational power. This would also help reduce AI's carbon footprint.

Another option is to use AI to create synthetic data to train systems. In other words, developers can simply generate the data they need, curated to suit their particular AI model.

Several projects are already using synthetic content, often sourced from data-generating services such as Mostly AI. This will become more common in the future.

Developers are also searching for content outside the free online space, such as that held by large publishers and offline repositories. Think about the millions of texts published before the internet. Made available digitally, they could provide a new source of data for AI projects.

News Corp, one of the world's largest news content owners (which has much of its content behind a paywall) recently said it was negotiating content deals with AI developers. Such deals would force AI companies to pay for training data – whereas they have mostly scraped it off the internet for free so far.

Content creators have protested against the unauthorised use of their content to train AI models, with some suing companies such as Microsoft, OpenAI and Stability AI. Being remunerated for their work may help restore some of the power imbalance that exists between creatives and AI companies.

Rita Matulionyte, Senior Lecturer in Law, Macquarie University

This article is republished from The Conversation under a Creative Commons license. Read the original article.

This content was originally published here.

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govindhtech · 4 months

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Is TensorRT Acceleration Coming For Stable Diffusion 3

NVIDIA TensorRT

Thanks to NVIDIA RTX and GeForce RTX technology, the AI PC age is arrived. Along with it comes a new language that can be difficult to understand when deciding between the many desktop and laptop options, as well as a new method of assessing performance for AI-accelerated tasks. This article is a part of the AI Decoded series, which shows off new RTX PC hardware, software, tools, and accelerations while demystifying AI by making the technology more approachable.

While frames per second (FPS) and related statistics are easily understood by PC gamers, new measures are needed to measure AI performance.

Emerging as the Best

Trillions of operations per second, or TOPS, is the initial baseline. The key term here is trillions; the processing power required for generative AI jobs is truly enormous. Consider TOPS to be a raw performance indicator, like to the horsepower rating of an engine.

Take Microsoft’s recently unveiled Copilot+ PC series, for instance, which has neural processing units (NPUs) capable of up to 40 TOPS. For many simple AI-assisted tasks, such as asking a nearby chatbot where yesterday’s notes are, 40 TOPS is sufficient.

However, a lot of generative AI tasks are more difficult. For all generative tasks, the NVIDIA RTX and GeForce RTX GPUs offer performance never seen before; the GeForce RTX 4090 GPU offers more than 1,300 TOPS. AI-assisted digital content production, AI super resolution in PC gaming, image generation from text or video, local large language model (LLM) querying, and other tasks require processing power comparable to this.

Put in Tokens to Start Playing

TOPS is just the start of the tale. The quantity of tokens produced by the model serves as a gauge for LLM performance.

The LLM’s output is tokens. A word in a sentence or even a smaller piece like whitespace or punctuation might serve as a token. The unit of measurement for AI-accelerated task performance is “tokens per second.”

Batch size, or the quantity of inputs processed concurrently in a single inference pass, is another crucial consideration. The ability to manage many inputs (e.g., from a single application or across multiple apps) will be a critical distinction, as an LLM will be at the basis of many modern AI systems. Greater batch sizes demand more memory even though they perform better for concurrent inputs, particularly when paired with larger models.

NVIDIA TensorRT-LLM

Because of their massive amounts of dedicated video random access memory (VRAM), Tensor Cores, and TensorRT-LLM software, RTX GPUs are incredibly well-suited for LLMs.

High-speed VRAM is available on GeForce RTX GPUs up to 24GB and on NVIDIA RTX GPUs up to 48GB, allowing for larger models and greater batch sizes. Additionally, RTX GPUs benefit from Tensor Cores, which are specialised AI accelerators that significantly accelerate the computationally demanding tasks necessary for generative AI and deep learning models. Using the NVIDIA TensorRT software development kit (SDK), which enables the highest-performance generative AI on the more than 100 million Windows PCs and workstations powered by RTX GPUs, an application can quickly reach that maximum performance.

RTX GPUs achieve enormous throughput benefits, particularly as batch sizes increase, because to the combination of memory, specialised AI accelerators, and optimised software.

Text to Image More Quickly Than Before

Performance can also be assessed by measuring the speed at which images are generated. Stable Diffusion, a well-liked image-based AI model that enables users to quickly translate text descriptions into intricate visual representations, is one of the simplest methods.

Users may easily build and refine images from text prompts to get the desired result with Stable Diffusion. These outcomes can be produced more quickly when an RTX GPU is used instead of a CPU or NPU to process the AI model.

When utilising the TensorRT extension for the well-liked Automatic1111 interface, that performance increases even further. With the SDXL Base checkpoint, RTX users can create images from prompts up to two times faster, greatly simplifying Stable Diffusion operations.

TensorRT Acceleration

TensorRT acceleration was integrated to ComfyUI, a well-liked Stable Diffusion user interface, last week. Users of RTX devices may now create images from prompts 60% quicker, and they can even utilise TensorRT to transform these images to videos 70% faster utilising Stable Video Diffuson.

The new UL Procyon AI Image Generation benchmark tests TensorRT acceleration and offers 50% faster speeds on a GeForce RTX 4080 SUPER GPU than the quickest non-TensorRT implementation.

The much awaited text-to-image model from Stable Diffusion 3 Stability AI will soon receive TensorRT acceleration, which will increase performance by 50%. Furthermore, even more performance acceleration is possible because to the new TensorRT-Model Optimizer. This leads to a 50% decrease in memory use and a 70% speedup over the non-TensorRT approach.

Naturally, the actual test is found in the practical application of refining an initial prompt. By fine-tuning prompts on RTX GPUs, users may improve image production much more quickly it takes seconds instead of minutes when using a Macbook Pro M3 Max. When running locally on an RTX-powered PC or workstation, users also benefit from speed and security with everything remaining private.

The Results Are Available and Can Be Shared

Recently, the open-source Jan.ai team of engineers and AI researchers integrated TensorRT-LLM into their local chatbot app, then put these optimisations to the test on their own system.Image Credit to NVIDIA

TensorRT-LLM

The open-source llama.cpp inference engine was utilised by the researchers to test TensorRT-LLM’s implementation on a range of GPUs and CPUs that the community uses. They discovered that TensorRT is more effective on consecutive processing runs and “30-70% faster than llama.cpp on the same hardware.” The group invited others to assess the performance of generative AI independently by sharing its methodology.