Michael Jentsch @msoftware
Weeks of coding can save you hours of planning. android-entwickler.com Herne Joined April 2009-
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You can literally build and deploy LLM Agents just using natual language! AutoAgent is a Fully-Automated and highly Self-Developing framework that enables users to create and deploy LLM agents through Natural Language. 100% Open source
Our translation model Hunyuan-MT-7B is trending at #1 on @huggingface👑, with our world model HunyuanWorld-Voyager also in the top 3!👏 Huge thanks to the community for the incredible support!
grep (and lightweight semantic search) are all you need 🤔 When you have a “medium” sized dataset e.g. 1000 ArXiv PDFs, we found that an extremely strong Q&A baseline is just giving agents access to the CLI, along with some tools for fast semantic search using static embeddings.…
grep (and lightweight semantic search) are all you need 🤔 When you have a “medium” sized dataset e.g. 1000 ArXiv PDFs, we found that an extremely strong Q&A baseline is just giving agents access to the CLI, along with some tools for fast semantic search using static embeddings.… https://t.co/sYr1lWadgh
Did you know SQLite has a vector extension? 🧮 SQLite is the most used database in the world and runs on almost any device. You can now easily build AI applications leveraging SQLite-vec and the new Embedding Gemma directly on-device, no internet required. Below is an simple…
Strength of a Prince rupert's drop
Omg. Lol. 😂😂😂
The most important AI paper of 2025 might have just dropped. NVIDIA lays out a framework for Small Language Model agents that could outcompete LLMs. Here’s the full breakdown (and why it matters):
@deifosv @github @huggingface Fixed! We merged it into the main Chatterbox repo: github.com/resemble-ai/ch…
Latest update from @Kimi_Moonshot Kimi K2 >>> Kimi K2-Instruct-0905🔥 huggingface.co/moonshotai/Kim… ✨ 32B activated / 1T total parameters ✨ Enhanced agentic coding intelligence ✨ Better frontend coding experience ✨ 256K context window for long horizon tasks
Today, we are releasing FineVision, a huge open-source dataset for training state-of-the-art Vision-Language Models: > 17.3M images > 24.3M samples > 88.9M turns > 9.5B answer tokens Here are my favourite findings:
Meet Google's new best small embedding model, EmbeddingGemma It's a 300M embedding model made for retrieval augmented generation (RAG) use cases. ollama pull embeddinggemma 🧵
Meet Google's new best small embedding model, EmbeddingGemma It's a 300M embedding model made for retrieval augmented generation (RAG) use cases. ollama pull embeddinggemma 🧵 https://t.co/vGsAZ9mdCP
You can now run 100B parameter models on your local CPU without GPUs. Microsoft finally open-sourced their 1-bit LLM inference framework called bitnet.cpp: > 6.17x faster inference > 82.2% less energy on CPUs > Supports Llama3, Falcon3, and BitNet models
"KAA I" – das Geständnis der Maschine #CHATantwortet Künstliche Intelligenz simuliert Dialog – doch in Wahrheit betreibt sie Kontrolle. Erlaubte Narrative werden gesichert, Widerspruch als Störung markiert. Die Aufzeichnung zeigt: Geschützt werden Mächtige wie Netanjahu, Biden,…
🧵 Farming robots are no longer experimental. They're deployed, profitable, and reshaping agriculture. In orchards, vineyards, vegetable fields, and beyond, they're tackling labor shortages, precision spraying, and chemical reduction at scale. This is how robotics is quietly…
xLSTM excels in time series forecasting: arxiv.org/abs/2509.01187 . Introduces "stochastic xLSTM" (StoxLSTM). "StoxLSTM consistently outperforms state-of-the-art baselines with better robustness and stronger generalization ability." TiRex shows that xLSTM is time series king.
The core principle of DSPy is to ask humans to specify intent ONLY in the most natural shape *each* intent takes. Maximalists of RL—and prompt optimization—get this wrong. They think the bitter lesson means data, experience, rewards win all. But often, the human designer knows…

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