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- 🚀 AI技術の最新動向 – 2026年3月9日 世界中から収集したAI・機械学習の最新情報をお届けします 📑 目次 💻 注目のGitHubプロジェクト livehl/aimirror hanxiao/mlx-vis SamYbarra/Polymarket-AI-Trading-Bot caramaschiHG/awesome-ai-agents-2026 mechramc/Orion 📌 関連記事もチェック 📚 最新研究論文 1. BEVLM: Distilling Semantic Knowledge from LLMs into Bird's-Eye View Representations 著者: Thomas Monninger, Shaoyuan Xie, Qi Alfred Chen The integration of Large Language Models (LLMs) into autonomous driving has attracted growing interest for their strong reasoning and semantic understanding abilities, which are essential for handling complex decision-making and long-tail scenarios. However, existing methods typically feed LLMs with… 論文を読む → 2. Fly360: Omnidirectional Obstacle Avoidance within Drone View 著者: Xiangkai Zhang, Dizhe Zhang, WenZhuo Cao Obstacle avoidance in unmanned aerial vehicles (UAVs), as a fundamental capability, has gained increasing attention with the growing focus on spatial intelligence. However, current obstacle-avoidance methods mainly depend on limited field-of-view sensors and are ill-suited for UAV scenarios which re… 論文を読む → 3. SCOPE: Scene-Contextualized Incremental Few-Shot 3D Segmentation 著者: Vishal Thengane, Zhaochong An, Tianjin Huang Incremental Few-Shot (IFS) segmentation aims to learn new categories over time from only a few annotations. Although widely studied in 2D, it remains underexplored for 3D point clouds. Existing methods suffer from catastrophic forgetting or fail to learn discriminative prototypes under sparse superv… 論文を読む → 💻 注目のGitHubプロジェクト 1. livehl/aimirror 🚀 200倍速！AI时代的下载神器 | Docker/PyPI/HuggingFace/CRAN 全加速 | 并行分片+智能缓存，让下载飞起来 ⭐ 109 stars | 🔀 0 forks リポジトリを見る → 2. hanxiao/mlx-vis Pure MLX implementations of UMAP, t-SNE, PaCMAP, TriMap, DREAMS, CNE, and NNDescent for Apple Silicon. Metal GPU for computation and video rendering. ⭐ 61 stars | 🔀 1 forks リポジトリを見る → 3. SamYbarra/Polymarket-AI-Trading-Bot Polymarket trading bot based on AI | ML ⭐ 56 stars | 🔀 55 forks リポジトリを見る → 4. caramaschiHG/awesome-ai-agents-2026 🤖 The most comprehensive list of AI agents, frameworks & tools in 2026. 300+ resources · 20+ categories · Updated monthly. ⭐ 28 stars | 🔀 6 forks リポジトリを見る → 5. mechramc/Orion Local AI runtime for training & running small LLMs directly on Apple Neural Engine (ANE). No CoreML. No Metal. Offline, on-device fine-tuning & inference on M-series silicon. ⭐ 19 stars | 🔀 2 forks リポジトリを見る → 📚 あわせて読みたい 【AI最新動向】一歩先の未来へ！私が触れた最先端AIの世界 「プロンプトは戦略だ！」と学んで劇的効率UP！私のAI活用術 私が実感！AIで物流の悩み解消、時間もコストも浮いた話。
🚀 AI技術の最新動向 – 2026年3月9日
世界中から収集したAI・機械学習の最新情報をお届けします
📑 目次
- 💻 注目のGitHubプロジェクト
- livehl/aimirror
- hanxiao/mlx-vis
- SamYbarra/Polymarket-AI-Trading-Bot
- caramaschiHG/awesome-ai-agents-2026
- mechramc/Orion
- 📌 関連記事もチェック
📚 最新研究論文
1. BEVLM: Distilling Semantic Knowledge from LLMs into Bird's-Eye View Representations
著者: Thomas Monninger, Shaoyuan Xie, Qi Alfred Chen
The integration of Large Language Models (LLMs) into autonomous driving has attracted growing interest for their strong reasoning and semantic understanding abilities, which are essential for handling complex decision-making and long-tail scenarios. However, existing methods typically feed LLMs with…
2. Fly360: Omnidirectional Obstacle Avoidance within Drone View
著者: Xiangkai Zhang, Dizhe Zhang, WenZhuo Cao
Obstacle avoidance in unmanned aerial vehicles (UAVs), as a fundamental capability, has gained increasing attention with the growing focus on spatial intelligence. However, current obstacle-avoidance methods mainly depend on limited field-of-view sensors and are ill-suited for UAV scenarios which re…
3. SCOPE: Scene-Contextualized Incremental Few-Shot 3D Segmentation
著者: Vishal Thengane, Zhaochong An, Tianjin Huang
Incremental Few-Shot (IFS) segmentation aims to learn new categories over time from only a few annotations. Although widely studied in 2D, it remains underexplored for 3D point clouds. Existing methods suffer from catastrophic forgetting or fail to learn discriminative prototypes under sparse superv…
💻 注目のGitHubプロジェクト
1. livehl/aimirror
🚀 200倍速！AI时代的下载神器 | Docker/PyPI/HuggingFace/CRAN 全加速 | 并行分片+智能缓存，让下载飞起来
⭐ 109 stars | 🔀 0 forks
2. hanxiao/mlx-vis
Pure MLX implementations of UMAP, t-SNE, PaCMAP, TriMap, DREAMS, CNE, and NNDescent for Apple Silicon. Metal GPU for computation and video rendering.
⭐ 61 stars | 🔀 1 forks
3. SamYbarra/Polymarket-AI-Trading-Bot
Polymarket trading bot based on AI | ML
⭐ 56 stars | 🔀 55 forks
4. caramaschiHG/awesome-ai-agents-2026
🤖 The most comprehensive list of AI agents, frameworks & tools in 2026. 300+ resources · 20+ categories · Updated monthly.
⭐ 28 stars | 🔀 6 forks
5. mechramc/Orion
Local AI runtime for training & running small LLMs directly on Apple Neural Engine (ANE). No CoreML. No Metal. Offline, on-device fine-tuning & inference on M-series silicon.
⭐ 19 stars | 🔀 2 forks
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