Artificial Kuramoto Oscillatory Neurons (AKOrN) differ from traditional artificial neurons by oscillating, rather than just turning on or off. Each neuron is represented by a rotating vector on a sphere, influenced by its connections to other neurons. This behavior is based on the Kuramoto model, which describes how oscillators (like neurons) tend to synchronize, similar to pendulums swinging in unison.
Key points:
Oscillating Neurons: Each AKOrN’s rotation is influenced by its connections, and they try to synchronize or oppose each other. Synchronization: When neurons synchronize, they "bind," allowing the network to represent complex concepts (e.g., "a blue square toy") by compressing information. Updating Mechanism: Neurons update their rotations based on connected neurons, input stimuli, and their natural frequency, using a Kuramoto update formula. Network Structure: AKOrNs can be used in various network layers, with iterative blocks combining Kuramoto layers and feature extraction modules. Reasoning: This model can perform reasoning tasks, like solving Sudoku puzzles, by adjusting neuron interactions. Advantages: AKOrNs offer robust feature binding, reasoning capabilities, resistance to adversarial data, and well-calibrated uncertainty estimation. In summary, AKOrN's oscillatory neurons and synchronization mechanisms enable the network to learn, reason, and handle complex tasks like image classification and object discovery with enhanced robustness and flexibility.
✨ Launched All-Scenario Reasoning Model (language, visual, and search reasoning capabilities) , with medical expertise as one of its key highlights. https://ying.baichuan-ai.com/chat
✨ Released Baichuan-M1-14B Medical LLM on the hub Available in both Base and Instruct versions, support English & Chinese.
📢 HuggingFace Daily Paper Newsletter (Multilingual) 🎯 Project Link: https://github.com/2404589803/hf-daily-paper-newsletter-multilingual 🌟 What is it? An innovative open-source project that automatically collects the latest AI research papers from HuggingFace and translates them into multiple languages using InternLM-3, making cutting-edge AI research accessible to a global audience! 🚀 Key Features: - 🤖 Automatic daily paper collection from HuggingFace - 🌐 Supports 5 languages: - 🇯🇵 Japanese - 🇰🇷 Korean - 🇪🇸 Spanish - 🇫🇷 French - 🇬🇧 English (original) - ⚡ Powered by InternLM-3 for high-quality translations - 🔄 Daily automated updates via GitHub Actions - 📊 Structured JSON data format - ⏰ Synchronized with Beijing time (UTC+8) - 📝 Complete activity logging 🛠️ Technical Stack: - Python - InternLM-3 API - GitHub Actions - requests - pytz - openai - gTTS 🔧 Easy Setup: 1. Clone the repository 2. Install dependencies with pip install -r requirements.txt 3. Set up your InternLM API key 4. Let GitHub Actions handle the rest! 📂 Data Organization: - /Paper_metadata_download: Original English papers - /Translated_papers: - /ja: Japanese translations - /ko: Korean translations - /es: Spanish translations - /fr: French translations 🤝 Powered By: - [InternLM](https://internlm.org/) - Advanced translation model - [HuggingFace](https://huggingface.co/) - Paper source
What happened yesterday in the Chinese AI community? 🚀
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