---
linkTitle: 07-20-Daily
title: 07-20-Daily AI News Daily
weight: 11
breadcrumbs: false
comments: true
description: Researchers from top institutions like Shanghai AI Lab and Tsinghua University
  have just dropped REST, a brand-new, "pressure cooker" evaluation framework. W.
---
## AI Daily Briefing 2025/7/20

> AI Daily | 8 AM Updates | All-Network Data Aggregation | Cutting-Edge Scientific Exploration | Industry Free Speech | Open-Source Innovation Power | AI and Human Future | [Access Web Version ↗️](https://ai.hubtoday.app/)

### **AI Content Summary**

```
Cutting-edge AI research reveals model limitations through high-pressure tests and develops new models with self-reflection and correction capabilities.
The industry is experiencing an increasingly fierce AI talent war, while multiple institutions have jointly released a new data protection grading system.
The developer community's philosophy is shifting from prompt engineering to context engineering, aiming to build more robust and reliable AI applications.
OpenAI drives innovation with its unique fast-paced culture and cleverly pre-heats new model releases through expectation management.
The industry is also starting to reflect deeply, believing that the R&D focus for AI Agents should be practical value rather than flashy demonstrations.
```

### AI Frontier Research

1. Researchers from top institutions like **Shanghai AI Lab** and **Tsinghua University** have just dropped **REST**, a brand-new, "pressure cooker" evaluation framework. When AI models are acing standardized tests like straight-A students, don't we feel like giving them a real "reality check"? These folks aren't playing nice, making models solve one problem at a time. Instead, they're cramming a gazillion questions into a single prompt, simulating those crazy, multi-tasking scenarios we face in the real world. The results? Absolutely mind-blowing: even battle-hardened top models like **DeepSeek-R1** saw their accuracy on the AIME24 test set nosedive by nearly **30%**! This [AI News: Research](https://arxiv.org/abs/2507.10541) doesn't just mercilessly expose the "greenhouse effect" of current evaluation methods; it also proves that under high pressure, a model's "**overthinking**" tendency and **context allocation** ability are the true litmus tests that separate the contenders. It also gives us a more precise ruler to measure AI's actual steps toward general intelligence. 🤯
<br/>![AI News: AI Stress Test](https://raw.githubusercontent.com/justlovemaki/imagehub/refs/heads/main/images/2025/07/news_01k0hwb125f86v5rpm7csv82r4.avif)<br/>

2. Researchers from the **Chinese Academy of Sciences Institute of Automation** (CASIA) got super creative and proposed a brand-new model, **GThinker**, that "looks before it leaps." Do large multimodal models also fall into the trap of "tunnel vision" when trying to grasp our complex world? To cure AI's increasingly severe "**confirmation bias**," **GThinker**'s killer feature is an innovative mechanism called "**clue-guided reflection**." This gem gives AI the precious ability to proactively "look back" during reasoning, constantly verifying and correcting its initial understanding of visual information. For example, it can realize the creature in an image isn't a "crab" but a "shrimp" because it can self-reflect and conclude: "that red triangular structure actually looks more like a shrimp's head." This powerful self-correction and deep-thinking capability has enabled it to [Surpassing the Latest O4-mini Model - AI News](https://arxiv.org/abs/2506.01078) in several complex reasoning benchmarks, signaling that AI is moving beyond a mere "knowledge output machine" and taking a giant leap toward a "deep-thinking partner" closer to human intelligence. 🧠
<br/>![AI News: AI Self-Reflection](https://raw.githubusercontent.com/justlovemaki/imagehub/refs/heads/main/images/2025/07/news_01k0hwb4f0e3n81zcefqp9x3y4.avif)<br/>

3. Researchers from six top institutions, including **Zhejiang University**, **Nanyang Technological University**, and **IBM**, have jointly released a highly [AI News: Forward-Looking Paper](https://arxiv.org/abs/2507.03034), proactively proposing a brand-new **data protection grading system**. Have you ever stayed up late, quietly worrying that the business secrets or personal data you feed to AI might accidentally become global headlines? As AI tech permeates every corner of our lives and work, traditional data firewalls are practically useless, as flimsy as a paper screen. This system creatively categorizes data protection strategies into four levels: **unavailable, privacy-protected, traceable, and deletable**. It aims to equip the fast-flowing, ubiquitous data of the AI era with an impenetrable "four-level armor." This isn't just a systematic review and elevation of existing technologies and regulations; it also provides a crucial core strategic framework for tackling the immense challenges of future AI data governance, which is precisely the focus of the latest **AI News** deep dive. 🔒

### AI Industry Outlook and Social Impact

1. The dazzling AI programming startup, **Windsurf**, went through a hell of a rollercoaster ride—from heaven to hell and back to being acquired—all within a mere 96 hours! This is literally a live-action "Game of Thrones" playing out in Silicon Valley, with a plot so tight it's suffocating! The story began with **Google**'s almost barbaric move, poaching over 40 of Windsurf's core engineers in a flash with double salaries and a generous $2.4 billion licensing deal. It was a textbook-level "talent acquisition" drama for the industry. Just as **Windsurf** was on the brink of collapse, its competitor, **Cognition**, swooped in like a savior, announcing it would take over all remaining assets and employees. This breathtaking flash acquisition starkly reveals the brutal truth of the current **AI talent war**: for tech giants, acquiring a company is far less cost-effective than directly acquiring its smartest "brains." Top talent is the ultimate strategic resource, far more valuable than any tangible asset. 🤯
<br/>![AI News: AI Talent War](https://raw.githubusercontent.com/justlovemaki/imagehub/refs/heads/main/images/2025/07/news_01k0hwb7f2feka6rf2czm9vmzh.avif)<br/>

2. Former **OpenAI** engineer Calvin French-Owen peeled back the mysterious veil for us outsiders in a [AI News Deep Dive: Profound Reflection Article](https://www.jiqizhixin.com/articles/2025-07-19-5), revealing what it's truly like to work at the world's most scrutinized AI company, tasked with humanity's AGI dreams. Is it some divine experience, or a hellish grind? He painted a picture of a "bottom-up" culture driven by **Slack** channels, almost devoid of traditional emails, with lightning-fast strategic shifts, and an extreme encouragement to "just do it." In this atmosphere, teams could successfully launch the world-changing **Codex** in a mere **7 weeks** through extreme sprints, working till the wee hours every day. This unique cultural vibe, akin to early **Meta**'s hacker spirit, is brimming with "action-first" momentum and a certain "organized chaos." This article offers us a peek into how the AGI dream is powered: by the astonishing, world-shaking creativity that erupts within such a high-intensity, high-flux "pressure cooker." 🔥
<br/>![AI News: OpenAI Work Culture](https://raw.githubusercontent.com/justlovemaki/imagehub/refs/heads/main/images/2025/07/news_01k0hwba78f67a7qmn3fa4gx09.avif)<br/>

### Open-Source TOP Projects

1. **remote-jobs** (32.6k Stars) - This detailed [Remote-Work Friendly Companies List - AI News](https://github.com/remoteintech/remote-jobs) is your first step on the "escape plan" to freedom. Are you already sick of the 9-to-5 office grind, dreaming of a digital nomad life where you work while traveling? It's not just a simple collection of links; it's a microcosm of the global remote work culture's rise, carefully curating quality companies that truly embrace distributed team philosophies. Say goodbye to crowded commutes and embrace a more flexible way of working. Start by bookmarking this treasure trove! ✈️

2. **shadPS4** (24.4k Stars) - This meticulously crafted [PS4 Emulator - AI News](https://github.com/shadps4-emu/shadPS4), built in C++, lets your PC relive those unforgettable classic gaming memories. Do you miss those thrilling times spent on **PlayStation 4**? Developing a fully functional game console emulator is a massive technical challenge, involving a deep understanding of underlying hardware and intricate software replication. This project isn't just a paradise for tech enthusiasts; it's also a crucial vehicle for preserving and passing down gaming culture in the digital age. 🎮

3. **pytorch-deep-learning** (14.6k Stars) - This project is your free **PyTorch** deep learning crash course, offering [Complete Learning Resources - AI News](https://github.com/mrdbourke/pytorch-deep-learning) from zero-to-hero for mastering the field. In the age of AI, grasping deep learning frameworks has become an essential skill. It includes detailed tutorials, practical code, and clear theoretical explanations, simplifying complex concepts. Instead of getting lost in a sea of information, follow this structured learning path to systematically build your AI knowledge fortress and powerfully empower your career. 🚀

4. **mediamtx** (15.2k Stars) - **Mediamtx** is a plug-and-play [Streaming Media Swiss Army Knife - AI News](https://github.com/bluenviron/mediamtx), allowing you to easily handle a dazzling array of audio and video protocols like SRT, WebRTC, and RTSP, just like building blocks. In fields like live streaming, video conferencing, and security monitoring, the complexity of media processing is often a headache. It encapsulates complex underlying technologies into simple, easy-to-use interfaces, significantly lowering the barrier for developers to build real-time audio and video applications. It's truly a streaming media development accelerator. ⚙️

5. **bknd** (2.4k Stars) - **bknd** offers you a lightweight, self-deployable perfect alternative, allowing your backend to travel [Lightweight and Self-Deployable - AI News](https://github.com/bknd-io/bknd). Tired of being "held hostage" by large cloud service providers like **Firebase/Supabase**? Craving complete control over your backend services and data? It represents a "back to basics" development philosophy, emphasizing data sovereignty and flexibility, letting you deploy your services anywhere and break free from vendor lock-in to truly achieve technical freedom. ✨

### Social Media Shares

1. **OpenAI** recently pulled off a masterful act of expectation management on social media, cleverly kicking off a "pre-heating" round for the highly anticipated **GPT-5**. Through official channels, they [AI News Flash: Clear Statement](https://x.com/OpenAI/status/1946594933470900631) that while GPT-5's release is on the horizon, the model that shone brightly and amazed the world at the International Mathematical Olympiad was actually an independent experimental version using new tech that won't be widespread until the future. More critically, they emphasized that its extraordinary capabilities at that level won't be publicly released for several more months. This rhetoric is simply textbook-level PR: it unapologetically flaunts their unfathomable research depth while successfully hyping everyone up to the max, hinting that the true ace (**GPT-5**) is still coming. Stay tuned! 😉

2. A mysterious new model named "**o3-alpha**" recently [Sudden Appearance - AI News](https://x.com/op7418/status/1946585176920002897) on the **Web Arena** benchmark platform. Its powerful frontend code generation capabilities practically stunned everyone, shaking the entire developer community. Demo videos circulating online show this model seamlessly generating a fully functional and highly customizable SVG application "in one go," with an unprecedented level of code completeness and logical coherence. Tech gurus in the community are speculating that this could very well be another giant leap for **OpenAI** in code generation, perhaps even an inadvertent "tech leak" of **GPT-5**'s terrifying programming prowess. 😲
<br/><video src="https://raw.githubusercontent.com/justlovemaki/imagehub/refs/heads/main/images/2025/07/news_01k0hwbqr3eh6agxtzrh94y4v5.mp4" controls="controls" width="100%"></video><br/>

3. AI developers, pay attention! "**Prompt engineering**" might already be an outdated concept; the true future belongs to the era of "**context engineering**." This profound idea is rapidly spreading across the global developer community, endorsed by industry big shots like Shopify CEO and Andrej Karpathy. As multiple [AI News: In-depth Article](https://baoyu.io/translations/context-engineering-prompt-engineering-by-addy) and [Practical Summary - AI News](https://m.okjike.com/originalPosts/687aeaec7ee613ba5a60ddd2) reveal, building a reliable, stable AI application is no longer just about a single, brilliant "magical incantation" (i.e., prompt). The more crucial work involves meticulously constructing a complete, rich information environment (**context**) for the AI, just like an operating system efficiently loads necessary data for the CPU. This valuable art, described as "worth tens of millions of dollars in tuition," demands developers transform from "alchemists" into "architects," systematically providing AI with code, documentation, examples, and tools. This isn't just a shift in mindset; it's the only path to robust AI agents. 🏗️
<br/>![AI News: AI Context Engineering](https://raw.githubusercontent.com/justlovemaki/imagehub/refs/heads/main/images/2025/07/news_01k0hwbwbmfbjr02fphpagpdv6.avif)<br/>

4. This [Incisive Question - AI News](https://x.com/Yangyixxxx/status/1946440743314395151) hits the nail on the head regarding the common pain points and development dilemmas in the current **AI Agent** field. In the extremely resource and time-constrained early stages of a startup, do you choose to pour all your effort into developing a "flashy but useless pretty young thing," or a "plain-looking but diligently value-delivering old workhorse"? It has triggered profound reflection across the entire industry: are we chasing those "**AI showpieces**" that can easily secure venture capital with cool demo videos, or are we down-to-earth creating "**AI pragmatists**" that genuinely solve real user problems and create business value? Behind this question lies a tough choice between technological ideals, business realities, and industry bubbles, and it's a critical crossroads determining whether a project ultimately leads to greatness or simply fizzles out. 🤔

---

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