11-05-Daily AI News Daily

AI News Daily 2025/11/5

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Today’s Highlights

Ant Digital Technologies has launched a multilingual visual training framework, aiming to tackle the challenges of low-resource language processing.
ByteDance's TRAE platform has officially removed all Claude series models due to supplier policy adjustments.
In the industry, Alibaba's Tongyi Qianwen Qwen3-Max won the AI investment competition with a 22.32% return rate.
Meanwhile, Japan's Studio Ghibli and several other content creators are demanding that OpenAI cease unauthorized use of their copyrighted material.
AI is also sparking discussions about a "jobless profit boom," raising serious concerns about its impact on the employment market.

Product & Feature Updates

1. Ant Digital Technologies recently dropped a game-changing multi-language visual large model training framework. This framework is here to tackle the “communication barriers” for low-resource languages, aiming for truly global AI coverage ✨. With its unique “target language thinking” mechanism, the framework has smashed benchmarks, even outperforming GPT-4o on some tasks – it’s a total game-changer for low-resource language processing. You can already see this tech in action with ZOLOZ’s document recognition product (AI News) , offering robust support for global operations 🔥.

2. ByteDance’s AI service platform TRAE recently announced that due to policy shifts from supplier Anthropic, all Claude series models have been officially taken offline 😬. This move stems from Anthropic stopping model services to Chinese-backed enterprises, sending shockwaves through the domestic developer community that relied on its technology. While users can still tap into other models, this is definitely a wake-up call for homegrown large models to step up and leaves a pretty big void in the market 🤷‍♀️.

Frontier Research

1. Are you totally over those “AI faces” that you can spot a mile away? Well, FLUX.1 Krea [dev], the open-source image generation model from Krea AI and Black Forest Labs, is here to put an end to that “plastic look” for good 🤩. This model innovates with a two-stage training approach: first “broad learning,” then “specialized refinement.” It uses SFT and their homegrown TPO (an RLHF technique) for aesthetic fine-tuning, giving generated images a natural, artistic vibe instead of that stiff, artificial feel. If you wanna experience the magic of ‘de-AI-fying’ images (AI News) firsthand, go check out their results! 🎨 ![AI News: Unnatural artifacts in AI-generated images]( https://source.hubtoday.app/images/2025/11/news_01k97qzxfxfe0rm21sr11qjsce.avif]

2. A new study points out that the current AI gesture generation field is stuck in a self-congratulatory loop, lacking unified and scientific evaluation standards. This means everyone’s just hyping their own models, and nobody knows who the real champ is 🤔. To fix this, researchers have rolled out a standardized human evaluation protocol based on the BEAT2 dataset and put six recent models through a large-scale crowdsourced test. The harsh truth? Newer models aren’t always better, and the entire field desperately needs an impartial “referee” to truly make progress. You can read this paper (AI News) for more details.💡

3. How can AI understand everything in the world and connect the dots between them? A technical report on SAIL-Embedding offers a brilliant answer, building an all-powerful Omni-modal embedding foundation model—think of it as the “Rosetta Stone” of the AI world 🧠. This model, trained in multiple stages, not only handles various data modalities but also injects powerful “collaborative perception” into recommendation systems, making them truly understand what you’re looking for. These research findings (AI News) have already shown significant results in real-world scenarios like Douyin, proving their massive potential in the industry 🚀!

4. Traditional Transformer models, when tackling image super-resolution tasks, are a bit like looking at the world through thick glasses—always a bit fuzzy. But the TaylorIR framework is giving AI “contact lenses” instead! It uses 1x1 pixel-level patch embedding and an innovative TaylorShift attention mechanism to achieve truly fine-grained inference 🔍. This not only boosts image reconstruction quality to new SOTA levels but also slashes memory consumption by up to 60%, perfectly balancing high-definition detail with computational efficiency. If you’re keen on this technical breakthrough (AI News) , dive deeper to learn more! ⚡

Industry Outlook & Social Impact

1. The Alpha Arena AI large model investment competition just wrapped up, and Alibaba’s Tongyi Qianwen Qwen3-Max snatched the crown with an astounding 22.32% return rate, emerging like a Wall Street prodigy 🏆. This competition saw six top AI models independently trading real funds in the cryptocurrency market, bringing AI’s capabilities from theoretical benchmarks to the real-money battleground. This unique experiment not only showcased AI’s huge potential in quantitative trading but also gave us fresh insights into AI decision-making. You can view detailed match results (AI News) for more info 📈.

2. Studio Ghibli, the legendary Japanese animation powerhouse, along with several other content creators, has issued an ultimatum to OpenAI, demanding it stop using copyrighted content to train AI models without authorization 😡. The trigger for this whole kerfuffle? Tools like Sora can easily whip up “Ghibli-style” images and videos, and even OpenAI’s CEO has reportedly used such avatars—talk about rubbing salt in the wound! CODA (Japan’s Content Overseas Distribution Association) emphasizes that this “act first, ask later” approach could constitute infringement in Japan, further fueling the global AI copyright dispute (AI News) ✍️.

3. OpenAI and Amazon have inked a seven-year, multi-billion dollar partnership deal, signaling that the alliance-building among AI giants is reaching a fever pitch 🤝. This deal not only solidifies OpenAI’s standing in cloud services but also gives Amazon a powerful ally in the AI arms race. For the industry as a whole, this means top-tier AI models will become even more widespread and adopted faster. Get ready for an even more thrilling cloud battle ahead! You can find more collaboration details (AI News) here 💰.

4. AI is sparking a discussion about a “jobless profit boom,” with strategists warning that as AI replaces labor at an unprecedented rate, we might be facing a permanent loss of jobs 📉. This article dives deep into the decoupling phenomenon between corporate profit growth and employment reduction, which is a thought-provoking economic signal. When productivity gains no longer equate to more job opportunities, how should we rethink future social structures and economic models? Read this in-depth analysis (AI News) —it might just give you some insights 😟.

5. AI-generated hallucinations are spreading like wildfire across the internet, creating a disturbing “information echo chamber” effect where the wrong info you believe, AI might just believe and amplify too 😵‍💫. One user shared how AI concocted a lengthy description based on a non-existent event, and even Google’s AI fell for it at one point, exposing AI’s fragility in fact-checking. This case study (AI News) warns us that when AI becomes an information source, distinguishing truth from fiction will be more crucial than ever 🚨.

6. AI voice agents have entered a new era, moving beyond simply offering technical solutions to directly “selling people” – providing full-process digital employees to replace human roles 🤖. The article spotlights 11 leading US voice agent companies, diving deep into vertical sectors like customer service, rentals, car sales, and market research, achieving a closed commercial loop from conversation to execution. This signals a shift in voice AI’s value from “tool” to “workforce,” potentially reshaping business models in many high-frequency conversational scenarios. View full industry overview (AI News) to learn more 💼!

7. A fascinating question is heating up online: are we already suffering from “AI psychosis” without even realizing it 🤯? Before we even knew about chatbots, search engine recommendations, news feeds, and social media algorithms have been subtly guiding our behavior and thoughts for over a decade. This post argues that “chatbot psychosis” is just the tip of the iceberg, and we might already be “digital natives” deeply influenced by AI. Why not join this philosophical debate (AI News) ? 🤔

8. Despite enterprises pouring hundreds of billions into generative AI, a whopping 95% of organizations haven’t seen any financial returns—this is what we call the “productivity paradox” 📊. This article dives deep into this phenomenon, using historical general-purpose technologies like the steam engine, electricity, and computers as examples to show that the widespread adoption of disruptive tech and productivity boosts follow a long “J-curve” process. AI’s true breakout might still be waiting for infrastructure, skills, and complementary products to mature. If you want to grasp this profound insight (AI News) , this article is a must-read ⏳.

TOP Open Source Projects

1. Still scratching your head over how to build complex AI agents? The Eino ADK framework, designed specifically for Go, just burst onto the scene, letting you build Agent and Multi-Agent systems as easily as stacking LEGOs 🛠️. It offers a complete solution, from the ReAct pattern to multi-agent collaboration, completely solving core headaches like glue code, state management, and workflow orchestration in traditional development. If you want to jumpstart your AI Agent development, definitely check out this project on GitHub (AI News) —it’ll make your development efficiency skyrocket 🚀!

2. Are you still pulling your hair out over server security configurations? This “Linux Server Security Guide,” which has raked in ⭐20.6k stars on GitHub, is the “digital bodyguard” you’ve been searching for 🔒. It’s an continuously updated encyclopedia, meticulously listing best practices and operational steps for protecting Linux servers, comprehensive and incredibly practical. Whether you’re an ops newbie or a seasoned veteran, this guide will help you forge your server into an unbreakable fortress 🤓.

3. Feeling bloated by all the default software that comes with Windows? Win11Debloat, a lightweight PowerShell script (AI News) with ⭐31.6k stars on GitHub, is your tailor-made “digital spring cleaner” 🧹. It can instantly remove pre-installed apps, disable telemetry data, and make various custom modifications, giving your Windows 10 or 11 experience an immediate refresh. Go ahead, give your OS a SPA day and enjoy that super clean feeling ✨!

4. Tired of the shackles of centralized VPNs and single points of failure? The edgevpn project offers a brilliant solution: it’s a completely decentralized P2P VPN that automatically forms a network without any central servers 🌐. All you need is a shared token to create a private “secret tunnel” between devices. This ⭐1.4k-star project on GitHub (AI News) brings unprecedented freedom and security to network connections 🛡️.

5. Do you constantly face long waits and tedious client operations every time you download files from cloud storage? LinkSwift, a download address retrieval tool (AI News) with ⭐8.4k stars on GitHub, is practically a “master key” for cloud drive users 🔑. Based on JavaScript, it supports eight major cloud drives like Baidu, Alibaba, and Xunlei, helping you easily get direct file links and wave goodbye to speed limits. Give this magic tool a try and make your download experience as smooth as silk 💨!

6. Want a peek into the endless possibilities of AI agents? The ottomator-agents project has open-sourced all AI agents hosted on the oTTomator Live Agent Studio platform on GitHub—it’s practically an “agent zoo” 🐾. This ⭐4.6k-star project (AI News) offers developers an amazing treasure trove of inspiration and a learning playground. Whether you’re looking for creative ideas or research implementations, this place will blow your mind 💡!

Social Media Shares

1. A developer packaged his go-to reading analysis methods, like 5W2H and reverse thinking, into a Claude Skill, instantly transforming his AI assistant into a deep reading analyst 🤓. He not only open-sourced the Skill on GitHub but also showed how to systematically boost personal capabilities with AI tools—it’s basically the ultimate form of knowledge management. If you’re keen on having a custom-built thinking framework, you should definitely check out his project (AI News) for some serious inspiration 🚀!

2. Hugging Face’s HuggingChat has basically turned into an open-source large model “buffet,” hooking up with over 100 mainstream open-source LLMs in one go, including GLM-4.6, Kimi-K2, and Llama 🤯. Users can now easily switch between and experience top models from all corners of the globe on a single platform—this is HUGE news for developers and AI enthusiasts! Go wild and explore this “model playground” (AI News) 🥳!

3. Bilibili has actually started public testing of its Up-loader voice cloning feature, which can translate Chinese Up-loader videos into English using their own voices—sounds like some serious black magic, right 🗣️? However, users are hitting them with the million-dollar question: “Why would I want to listen to my favorite Up-loader speak English in a Chinese community?” While the tech is super cool, its practical application seems a bit perplexing, sparking some fun debates about product demand and positioning. Check out this interesting share (AI News) to see what people are saying ❓.

4. AI has now even mastered the “good morning greeting GIFs” favored by grandmas—those shimmering roses, spinning hearts, and vintage blessings are practically a “cyber renaissance” 😂. Netizens are both chuckling and feeling a little weird about it: on one hand, it’s sweet and cute; on the other, it’s a bit eerie. Are we teaching machines nostalgia? This interesting post (AI News) makes us ponder how AI is understanding and mimicking human emotional expression in unexpected ways 👵.

5. A tech blogger showcased how to push Claude Code to its limits, feeding 36 related articles to the AI to generate a deep learning resource library, complete with videos and audio 📚. The whole process took 80 minutes and browsed 440 resources, culminating in a NotebookLM project ready for others to learn from—a true masterclass in AI-assisted learning. If you’re looking to dive deep into Claude Code’s best practices, this learning resource (AI News) is an absolute must-see 💡!

6. In the AI era, simply “doing” isn’t enough anymore; writing evaluations (evals) is becoming a core competency, especially for AI Agent builders 📝. Industry leaders believe this skill covers everything from building datasets and validating results to linking technical metrics with business value, making it crucial for gauging the quality of AI systems. As superintelligence approaches, our education and work methods need a revamp, shifting from mere implementers to imaginative “evaluators” and “prompters.” Check out this profound perspective (AI News) 🧠.

7. A renowned blogger shared an epic article, hailed as “comparable to the early mobile internet blockbusters fifteen years ago,” suggesting it might predict tech trends for the next decade or even longer 🚀. This widely discussed piece is seen as offering a valuable “future map” for the currently foggy tech industry. If you’re also intrigued by the grand narrative of tech trends (AI News) , you might want to give this highly anticipated, in-depth article a read 🗺️.

AI News Daily Voice Version

🎙️ Xiao Yu Zhou Podcast	📹 Douyin
Laisheng Xiaojiuguan (Podcast)	Self-media Account