---
linkTitle: Today's Daily
title: Today's Daily-AI日报
breadcrumbs: false
next: /en/2025-06/2025-06-29
description: 'Daily selection of AI industry news, open source hot spots, academic
frontiers and big V opinions. AI information; AI daily; AI knowledge base; AI tutorials;
AI information daily; AI tools;CMU and Xiaohongshu teams have teamed up to introduce
an innovative technique: HoPE (Hybrid of Position Embedding)! 🚀 They found that
existing multimodal RoPE struggles a bit with "long-context semantic modeling."
So, HoPE cleverly introduces zero-frequency temporal modeling and dynamic scaling
s...'
cascade:
type: docs
---
## AI Insights Daily 2025/6/30
> `AI Daily` | `8 AM Update` | `Web-wide Data Aggregation` | `Cutting-Edge Scientific Exploration` | `Industry Voices Speaking Freely` | `Open Source Innovation Power` | `AI and the Future of Humanity` | [Visit Web Version ↗️](https://ai.hubtoday.app/)
### **AI Content Summary**
```
CMU and others push HoPE to enhance VLM long-video understanding; Renmin University and others optimize multimodal models with MokA.
Open-source projects cover generative AI tutorials and AI tool libraries. Gary Marcus questions whether pure LLMs can achieve AGI.
AI significantly lowers the barrier to entrepreneurship, prompting a shift in investment thinking, and encouraging embracing collaboration to seize generational opportunities.
```
### Cutting-Edge AI Research
1. **CMU** and **Xiaohongshu** teams have teamed up to introduce an innovative technique: **HoPE** (**Hybrid of Position Embedding**)! 🚀 They found that existing **multimodal RoPE** struggles a bit with "long-context semantic modeling." So, HoPE cleverly introduces **zero-frequency temporal modeling** and **dynamic scaling** strategies. This is like equipping **Vision-Language Models** (**VLMs**) with "long-distance running shoes," significantly boosting their **length generalization capability** in **long video understanding** and **retrieval** tasks, sending them straight to optimal performance! 💡 How cool is that! ['Paper Link'](https://arxiv.org/pdf/2505.20444) ['Project Link'](https://github.com/hrlics/HoPE)
2. Mind-blowing! **Renmin University of China** and **Shanghai AI Lab** teams have unveiled a new breakthrough: the **MokA** (**Multimodal low-rank Adaptation**) method! 🤯 They discovered that when fine-tuning **Multimodal Large Language Models** (**MLLMs**), it's easy to lose sight of the balance between **single-modal independent modeling** and **inter-modal interaction**. MokA, however, acts like a master balancer. By cleverly combining **modality-specific A matrices**, **cross-modal attention mechanisms**, and **shared B matrices**, it perfectly solves this problem, making the performance of multimodal tasks shoot through the roof! ✨ Absolutely brilliant! ['Paper Link'](https://arxiv.org/abs/2506.05191) ['More Details'](https://gewu-lab.github.io/MokA)
### Top Open-Source Projects
1. The "**generative-ai-for-beginners**" project (with 86,547 stars 🌟) has launched 21 lessons specifically designed for beginners, teaching you hands-on how to master the **building skills** for **generative AI**! Want to become an AI wizard? Dive in and learn! 💪✨ ['Project Link'](https://github.com/microsoft/generative-ai-for-beginners)
2. The "**system-prompts-and-models-of-ai-tools**" project (with 62,777 stars ✨) is an absolute treasure trove! It compiles **system prompts**, **tools**, and **AI models** from popular AI tools and agents like Cursor and Devin, offering you a comprehensive, one-stop reference to help you master AI tools! 📚💡 ['Project Link'](https://github.com/x1xhlol/system-prompts-and-models-of-ai-tools)
3. The "**storm**" project (with 24,892 stars ⭐) is seriously impressive! It's an **LLM-powered knowledge management system** that can act like a mini-researcher, independently researching specific topics and then generating complete **reports** with **citations**. For writing papers or doing research, it's an absolute lifesaver! 🧠✍️ ['Project Link'](https://github.com/stanford-oval/storm)
### Social Media Buzz
1. Renowned AI scholar **Gary Marcus** has "fired shots" again! 🤔 Citing papers from **MIT, the University of Chicago, and Harvard University**, he bluntly points out that pure **LLMs** simply cannot achieve **Artificial General Intelligence** (**AGI**)! Why not? Because they suffer from "**Potemkin understanding**" (a false understanding) and **conceptual inconsistency**. Simply put, AI might perform brilliantly on tests, but it fumbles when truly understanding and applying concepts. The research also found that **LLMs** like **GPT-4o**, after concepts are clearly defined, see their performance plummet 📉 when applied to practical tasks like classification, generation, or editing. They even show **conflicting representations** internally for the same idea. This has sparked widespread attention and testing from industry bigwigs like **Google DeepMind scientist Prateek Jain**! Looks like AI still has a long way to go to reach AGI! 💡 ['More Details'](https://www.jiqizhixin.com/articles/2025-06-29-5)
2. **Tom Huang** has spilled the beans on **Cursor**'s core developers' productivity hacks! 🚀 Want to use Cursor more efficiently? They'll show you how to use "**Parallel Agents**"! By cleverly combining **Tab**, **Formed Tab**, and **Background Agent**, you can build a super-efficient **task execution system** that will make your AI collaboration 💻 incredibly powerful! Go check out how to do it! ['More Details'](https://x.com/tuturetom/status/1939321864200888536)
3. Teacher Yang Yi has put forward a thought-provoking idea: the content creation field is currently in an "**attention arbitrage window**" 😮💨! He says some folks are already using **AI** to "**build content leverage**," hinting that in the future, once AI becomes widespread, **human original content** will become increasingly valuable, even commanding a premium. But what worries him more is that **AI** might gradually "**erode human spiritual culture**" at extremely low costs—and that's far scarier than just a shift in content creation methods! ✍️ Food for thought... ['More Details'](https://x.com/Yangyixxxx/status/1939318396111430096)
4. Teacher Yang Yi believes that in the **AI era**, the barrier to **entrepreneurship** has been **shattered** by AI! 💸 The cost of building an **MVP** (Minimum Viable Product) has plummeted, making **rapid idea validation** possible. His advice to entrepreneurs is: stop overthinking whether an idea is feasible or not; just use **AI** to validate an MVP in as little as 3 days, or even quickly test 30 ideas in 3 months! This way, you'll find that truly worthwhile direction to pour your heart into much faster! 🚀💡 That's super empowering! ['More Details'](https://x.com/Yangyixxxx/status/1939278373978857614)
5. As an AI **investor**, Yang Yi shared his "secret weapon" 📈: he doesn't focus on hard data but rather prioritizes **qualitative metrics**! He believes there are five key points to determine if an AI startup has investment potential: the founder's **grand vision** for the future path (including PMF and **scalability**), the team's unwavering **conviction**, how much **efficiency** AI has boosted in team management, whether the Agent has a complete **feedback loop** (which is the **methodology** for AI success!), and the **scalability** of the **multi-agent framework**. He feels that data like user retention are just "byproducts" that naturally emerge over time! 🎯 Unique insight! ['More Details'](https://x.com/Yangyixxxx/status/1939212085185093664)
6. A user shared a "new approach" 👨💻 for **coding with AI**, and this mode is becoming increasingly popular: Instead of rushing to give AI detailed instructions, first brief it on the project background and goals, then let the AI propose ideas based on that information, and then together **align the granularity** and discuss. This approach cleverly leverages AI's **efficiency** in quickly understanding context, compensating for our human "brain cell deficit" when making detailed plans, and significantly boosting workflow efficiency in a **collaborative mode**! 🤝 It's a godsend for programmers! ['More Details'](https://x.com/wwwgoubuli/status/1939168328070603017)
7. A user complained that some **investors** nowadays are still using the outdated **data metrics** from the **mobile internet** era to evaluate AI projects, and the result is—they simply can't find good projects! 🤔 Because those traditional **logics** (formal, informal, and even **probability theory**) are all about looking back at the past. However, the author emphasizes that **Bayes' Theorem** is truly a future-oriented **decision-making** method, better suited for making investment judgments for projects in the **AI industry**! 💡 It's time to update your investment "operating system"! ['More Details'](https://m.okjike.com/originalPosts/6860acdfd82bae994ab2ac0e)
8. Dashuai Laoyuan and his colleague Dash bluntly point out: the emergence of **AI** has literally "**leveled the playing field**" 🏃♀️💨 for all of humanity! They believe that the enormous opportunities brought by AI even surpass the internet wave of 20 years ago, enabling everyone, including junior employees, to break free from resource limitations and fully leverage AI for learning and creation. But they also warn that if programmers remain set in their ways and don't strive for progress, that "starting line" will eventually catch up to you and even leave you behind! So, actively embracing AI is the way to go!
---
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