Llm

State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGI | Lex Fridman Podcast #490 - YouTube RLVR (Reinforcement Learning with Verifiable Rewards): We still haven’t seen the limits of Scaling Laws here. if you learn more, you forget more (No Free Lunch): LLMs also tend to forget previously learned information as they learn new things. Is the dream of AGI dying?: The dream of achieving AGI with a single model is dying; instead, we are moving towards realizing AGI through the collaboration of multiple specialized agents. rasbt/LLMs-from-scratch: Implement a ChatGPT-like LLM in PyTorch from scratch, step by step

Highlight of the week: I chipped my front tooth (3rd time in 5 years) Best Ways to Build Better Habits & Break Bad Ones | James Clear - Huberman Lab How to form good habits and break bad ones. Standard advice that sounds familiar but is solid: Good habits: Make it obvious, attractive, easy, satisfying Bad habits: Make it invisible, unattractive, difficult, unsatisfying Personally, I wanted to break the habit of mindlessly checking LINE News, but I couldn’t delete the LINE app itself. Inspired by this podcast, I looked it up and found this method to hide just the News tab. (Game changer!) Tweet from Andrej Karpathy A few random notes from claude coding quite a bit last few weeks. Coding workflow. Given the latest lift in LLM coding capability, like many others I rapidly went from about 80% manual+autocomplete coding and 20% agents in November to 80% agent coding and 20% edits+touchups in… ...

The Best Way to Read a Book (That Nobody’s Doing) A video where Jeremy Howard explains his close reading workflow with Solveit. The core idea: “load a lot of relevant context first, then read chapter-by-chapter while chatting with an AI, carrying context forward each time”. It feels close to what I’ve been doing with gptel for papers/books, but the explicit chapter-level context handoff was new to me. (Related) Past post: A refined Emacs LLM setup

I haven’t been updating my blog for a while, so I’m restarting with a lightweight weekly memo: things I read/watched this week that I enjoyed. Onoguchi Snow Dome A collector’s site showcasing their snow globe collection with photos. The early-Heisei-web vibe is oddly charming. The security paradox of local LLMs - Quesma Blog (HN) Local LLMs feel “more secure” than cloud LLMs at first glance, but it’s not that simple. The example attack prompts are fun to read (especially Attack #2). Love Generation filming locations (map) A fan-made location guide for a classic 90s drama I got hooked on again via Netflix. Kimura Takuya is way too cool.

Figure 1: At 27, I have worries I can’t tell anyone. Introduction: The Problem with the “AI Replaces Experts” Narrative In recent years, we hear everywhere that specialized white-collar jobs will be taken by AI. I’ve been deeply immersed in Data Science (DS) since my undergrad—through work, research, and hobbies. Lately, tech-illiterate family members and friends with no programming experience have started asking me (without any malice), “Are you still doing programming?” or “Can’t AI do everything now?” ...

As shown under another article, I’m using uvx to run some mcp servers needed by mcp.el. However, when I first started them on NixOS, I encountered an error. After consulting Gemini for solutions and a root cause analysis, here are my notes. Symptoms and Error Message Checking the *Mcp-Hub/ buffer with mcp-hub-view-log, the following error appeared: [stderr] Could not start dynamically linked executable: /home/bk/.cache/uv/archive-v0/unI5q9QapqXHm9fPXna4G/bin/python [stderr] NixOS cannot run dynamically linked executables intended for generic [stderr] linux environments out of the box. For more information, see: [stderr] https://nix.dev/permalink/stub-ld [jsonrpc] D[14:56:49.461] Connection state change: `exited abnormally with code 127 Solution: Enable nix-ld Adding the following to your nix configuration resolved the issue for me: ...

Introduction The integration of large language models (LLMs) into Emacs has rapidly evolved over the past few years. My first encounter with an LLM inside Emacs was in November 2022, through AI-powered code completion with copilot.el. I still vividly remember how impressed I was at that moment. Shortly after, ChatGPT was launched, and tools like ChatGPT.el made it possible to interact with AI within Emacs—though, at that time, the features were few, and I didn’t really feel the advantages of using LLMs in Emacs. ...