<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Llm on Onur Baydaş</title><link>https://onurbaydas.com/en/tags/llm/</link><description>Recent content in Llm on Onur Baydaş</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Sat, 17 Oct 2026 12:15:22 +0300</lastBuildDate><atom:link href="https://onurbaydas.com/en/tags/llm/index.xml" rel="self" type="application/rss+xml"/><item><title>AutoSynthData: Generating Training Data for Enterprise Agents</title><link>https://onurbaydas.com/en/news/2026-10-17-autosynthdata-enterprise-agent-training/</link><pubDate>Sat, 17 Oct 2026 12:15:22 +0300</pubDate><guid>https://onurbaydas.com/en/news/2026-10-17-autosynthdata-enterprise-agent-training/</guid><description>AutoSynthData is a tool focused on generating training data for enterprise agents. This tool aims to create synthetic data to improve the performance of AI models.</description></item><item><title>Developing Gemini 4 Argon responsibly and safely</title><link>https://onurbaydas.com/en/news/2026-10-17-gemini-4-argon-responsible-development/</link><pubDate>Sat, 17 Oct 2026 12:15:22 +0300</pubDate><guid>https://onurbaydas.com/en/news/2026-10-17-gemini-4-argon-responsible-development/</guid><description>Google DeepMind states that it prioritizes responsibility and safety in the development process of its new AI model, Gemini 4 Argon. This approach aims to minimize potential risks of the model and ensure its compliance with ethical standards.</description></item><item><title>How Oracle turns days of work into minutes with ChatGPT and Codex</title><link>https://onurbaydas.com/en/news/2026-10-17-oracle-chatgpt-codex-automation/</link><pubDate>Sat, 17 Oct 2026 12:15:22 +0300</pubDate><guid>https://onurbaydas.com/en/news/2026-10-17-oracle-chatgpt-codex-automation/</guid><description>Oracle is transforming specialist knowledge into fast, repeatable workflows across recruiting, engineering, and operations by using ChatGPT Work and Codex. This integration enhances efficiency by automating manual processes.</description></item><item><title>Linus Torvalds's First AI-Assisted Patch Series</title><link>https://onurbaydas.com/en/news/2026-10-17-linus-torvalds-llm-patches/</link><pubDate>Sat, 17 Oct 2026 12:15:22 +0300</pubDate><guid>https://onurbaydas.com/en/news/2026-10-17-linus-torvalds-llm-patches/</guid><description>Linus Torvalds announced that he used a large language model to address a long-standing problem. He has now submitted this patch series for review.</description></item><item><title>LWN.net Weekly Edition: 2026 Maintainers Summit and Other Topics</title><link>https://onurbaydas.com/en/news/2026-10-17-lwn-weekly-edition-2026/</link><pubDate>Sat, 17 Oct 2026 12:15:22 +0300</pubDate><guid>https://onurbaydas.com/en/news/2026-10-17-lwn-weekly-edition-2026/</guid><description>LWN.net&amp;#39;s weekly edition covers important topics from the 2026 Maintainers Summit. Additionally, various technical subjects like Rust goals and GCC with LLMs are discussed.</description></item><item><title>Qwen3.8-27B-Defiance: Uncensored and Modded Local LLM</title><link>https://onurbaydas.com/en/news/2026-10-17-qwen-defiance-uncensored-llm/</link><pubDate>Sat, 17 Oct 2026 12:15:22 +0300</pubDate><guid>https://onurbaydas.com/en/news/2026-10-17-qwen-defiance-uncensored-llm/</guid><description>This model combines an uncensored version of Qwen3.8-27B with various &amp;#34;AI Construct&amp;#34; modes. Users can select a specific personality mode for each request, and the model provides uncensored responses.</description></item><item><title>Tyger: Streaming ASR and Full-Duplex Turn-Control in One Model</title><link>https://onurbaydas.com/en/news/2026-10-17-tyger-asr-turn-control/</link><pubDate>Sat, 17 Oct 2026 12:15:22 +0300</pubDate><guid>https://onurbaydas.com/en/news/2026-10-17-tyger-asr-turn-control/</guid><description>Tyger has been released as a small model that manages full-duplex turn-control for voice agents. This model is based on NVIDIA Nemotron 3.5 ASR Streaming, with an additional 14M causal GRU layer.</description></item><item><title>Intel LLM-Scaler-vLLM PV 1.5 Update</title><link>https://onurbaydas.com/en/news/2026-10-16-intel-llm-scaler-vllm-update/</link><pubDate>Fri, 16 Oct 2026 19:56:22 +0300</pubDate><guid>https://onurbaydas.com/en/news/2026-10-16-intel-llm-scaler-vllm-update/</guid><description>Intel released LLM-Scaler-vLLM PV 1.5, a containerized Docker stack for AI/LLM experiences on Intel Arc Graphics hardware. This version, developed under Project Battlematrix, brings significant improvements.</description></item><item><title>Replit CEO Defines Future Work Model as 'Self-Driving Company'</title><link>https://onurbaydas.com/en/news/2026-10-16-replit-ai-self-driving-company/</link><pubDate>Fri, 16 Oct 2026 19:56:22 +0300</pubDate><guid>https://onurbaydas.com/en/news/2026-10-16-replit-ai-self-driving-company/</guid><description>Replit CEO Amjad Masad envisions a future where AI agents handle day-to-day tasks. In this model, people will focus on higher-level decisions.</description></item><item><title>Asana Cuts Model Costs 76x in Browser Tests with GPT-6.1 Sol</title><link>https://onurbaydas.com/en/news/2026-10-16-asana-gpt-61-sol-cost-reduction/</link><pubDate>Fri, 16 Oct 2026 00:17:33 +0300</pubDate><guid>https://onurbaydas.com/en/news/2026-10-16-asana-gpt-61-sol-cost-reduction/</guid><description>Asana achieved significant cost and performance improvements in its browser agent tests by using the GPT-6.1 Sol model. This enables them to offer more capable models to their customers at a much lower cost.</description></item></channel></rss>