A study published in Nature Human Behavior reveals that general anesthesia suppresses unique functional connectivity patterns in the brain, making it difficult to distinguish individuals based on their neural activity. This effect is strongest in uniquely human brain regions and has implications for understanding and potentially aiding consciousness recovery.
This blog post details an experiment testing the ability of LLMs (Gemini, ChatGPT, Perplexity) to accurately retrieve and summarize recent blog posts from a specific URL (searchresearch1.blogspot.com). The author found significant issues with hallucinations and inaccuracies, even in models claiming live web access, highlighting the unreliability of LLMs for even simple research tasks.
A follow-up article to a previous piece on Gen AI usage, noting a roughly even split between personal and business applications.
Spammers leveraged OpenAI's GPT-4o-mini to generate unique messages, bypassing spam filters and successfully delivering unwanted messages to over 80,000 websites over a four-month period. The framework, named AkiraBot, used the LLM to personalize messages, making detection more difficult.
Google Code Assist, now powered by Gemini 2.5, shows significant improvement in coding capabilities and introduces AI agents to assist across the software development lifecycle. The article details the features available in the free, standard, and enterprise tiers, and raises questions about agent availability and practical implementation.
Details the development and release of DeepCoder-14B-Preview, a 14B parameter code reasoning model achieving performance comparable to o3-mini through reinforcement learning, along with the dataset, code, and system optimizations used in its creation.
This document details how to run and fine-tune Gemma 3 models (1B, 4B, 12B, and 27B) using Unsloth, covering setup with Ollama and llama.cpp, and addressing potential float16 precision issues. It also highlights Unsloth's unique ability to run Gemma 3 in float16 on machines like Colab notebooks with Tesla T4 GPUs.
This document details how to run Qwen models locally using the Text Generation Web UI (oobabooga), covering installation, setup, and launching the web interface.
AIやテクノロジーの進化に伴い、教育現場では何をどう学ぶべきかが問われる時代。学習環境デザイナー／学習科学者の美馬のゆりさんにインタビューし、AI時代に生きるために必要な力について語ってもらいました。
LLM 0.24 introduces fragments and template plugins to better utilize long context models, improving storage efficiency and enabling new features like querying logs by fragment and leveraging documentation. It also details improvements to template handling and model support.
