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- 🚀 AI技術の最新動向 – 2026年2月17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 milanm/AutoGrad-Engine vixhal-baraiya/microgpt-c Kuberwastaken/picogpt doramirdor/NadirClaw benoitc/erlang-python 📌 関連記事もチェック 📚 最新研究論文 1. Symmetry in language statistics shapes the geometry of model representations 著者: Dhruva Karkada, Daniel J. Korchinski, Andres Nava Although learned representations underlie neural networks' success, their fundamental properties remain poorly understood. A striking example is the emergence of simple geometric structures in LLM representations: for example, calendar months organize into a circle, years form a smooth one-dimension… 論文を読む → 2. Long Context, Less Focus: A Scaling Gap in LLMs Revealed through Privacy and Personalization 著者: Shangding Gu Large language models (LLMs) are increasingly deployed in privacy-critical and personalization-oriented scenarios, yet the role of context length in shaping privacy leakage and personalization effectiveness remains largely unexplored. We introduce a large-scale benchmark, PAPerBench, to systematical… 論文を読む → 3. Rethinking Diffusion Models with Symmetries through Canonicalization with Applications to Molecular Graph Generation 著者: Cai Zhou, Zijie Chen, Zian Li Many generative tasks in chemistry and science involve distributions invariant to group symmetries (e.g., permutation and rotation). A common strategy enforces invariance and equivariance through architectural constraints such as equivariant denoisers and invariant priors. In this paper, we challeng… 論文を読む → 💻 注目のGitHubプロジェクト 1. milanm/AutoGrad-Engine A complete GPT language model (training and inference) in ~600 lines of pure C#, zero dependencies ⭐ 290 stars | 🔀 31 forks リポジトリを見る → 2. vixhal-baraiya/microgpt-c The most atomic way to train and inference a GPT in pure, dependency-free C ⭐ 162 stars | 🔀 31 forks リポジトリを見る → 3. Kuberwastaken/picogpt GPT in a QR Code ; The actual most atomic way to train and inference a GPT in pure, dependency-free JS/Python. ⭐ 84 stars | 🔀 9 forks リポジトリを見る → 4. doramirdor/NadirClaw Open-source LLM router that saves you money. Routes simple prompts to cheap/local models, complex ones to premium — automatically. OpenAI-compatible proxy. ⭐ 29 stars | 🔀 5 forks リポジトリを見る → 5. benoitc/erlang-python Execute Python from Erlang using dirty NIFs with GIL-aware execution, rate limiting, and free-threading support ⭐ 13 stars | 🔀 1 forks リポジトリを見る → 📚 あわせて読みたい 「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三つ巴！Geminiと私が出会って、ストーリー作りは変わった？。
🚀 AI技術の最新動向 – 2026年2月17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
- milanm/AutoGrad-Engine
- vixhal-baraiya/microgpt-c
- Kuberwastaken/picogpt
- doramirdor/NadirClaw
- benoitc/erlang-python
- 📌 関連記事もチェック
📚 最新研究論文
1. Symmetry in language statistics shapes the geometry of model representations
著者: Dhruva Karkada, Daniel J. Korchinski, Andres Nava
Although learned representations underlie neural networks' success, their fundamental properties remain poorly understood. A striking example is the emergence of simple geometric structures in LLM representations: for example, calendar months organize into a circle, years form a smooth one-dimension…
2. Long Context, Less Focus: A Scaling Gap in LLMs Revealed through Privacy and Personalization
著者: Shangding Gu
Large language models (LLMs) are increasingly deployed in privacy-critical and personalization-oriented scenarios, yet the role of context length in shaping privacy leakage and personalization effectiveness remains largely unexplored. We introduce a large-scale benchmark, PAPerBench, to systematical…
3. Rethinking Diffusion Models with Symmetries through Canonicalization with Applications to Molecular Graph Generation
著者: Cai Zhou, Zijie Chen, Zian Li
Many generative tasks in chemistry and science involve distributions invariant to group symmetries (e.g., permutation and rotation). A common strategy enforces invariance and equivariance through architectural constraints such as equivariant denoisers and invariant priors. In this paper, we challeng…
💻 注目のGitHubプロジェクト
1. milanm/AutoGrad-Engine
A complete GPT language model (training and inference) in ~600 lines of pure C#, zero dependencies
⭐ 290 stars | 🔀 31 forks
2. vixhal-baraiya/microgpt-c
The most atomic way to train and inference a GPT in pure, dependency-free C
⭐ 162 stars | 🔀 31 forks
3. Kuberwastaken/picogpt
GPT in a QR Code ; The actual most atomic way to train and inference a GPT in pure, dependency-free JS/Python.
⭐ 84 stars | 🔀 9 forks
4. doramirdor/NadirClaw
Open-source LLM router that saves you money. Routes simple prompts to cheap/local models, complex ones to premium — automatically. OpenAI-compatible proxy.
⭐ 29 stars | 🔀 5 forks
5. benoitc/erlang-python
Execute Python from Erlang using dirty NIFs with GIL-aware execution, rate limiting, and free-threading support
⭐ 13 stars | 🔀 1 forks
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