April 2026 TLDR setup for Ollama + Gemma 4 on a Mac mini (Apple Silicon) — auto-start, preload, and keep-alive
- Mac mini with Apple Silicon (M1/M2/M3/M4/M5)
- At least 16GB unified memory for Gemma 4 (default 8B)
- macOS with Homebrew installed
| """ | |
| The most atomic way to train and run inference for a GPT in pure, dependency-free Python. | |
| This file is the complete algorithm. | |
| Everything else is just efficiency. | |
| @karpathy | |
| """ | |
| import os # os.path.exists | |
| import math # math.log, math.exp |
April 2026 TLDR setup for Ollama + Gemma 4 on a Mac mini (Apple Silicon) — auto-start, preload, and keep-alive
Verified Spec-Driven Development (VSDD) is a unified software engineering methodology that fuses three proven paradigms into a single AI-orchestrated pipeline:
| theme = "dark_plus" | |
| [editor] | |
| # Sync clipboard with system clipboard | |
| default-yank-register = "+" | |
| line-number = "absolute" | |
| [editor.file-picker] | |
| hidden = false |
| set nocompatible | |
| filetype off | |
| set rtp+=~/.vim/bundle/Vundle.vim | |
| call vundle#begin() | |
| Plugin 'gmarik/Vundle.vim' | |
| Plugin 'ElmCast/elm-vim' | |
| Plugin 'cespare/vim-toml' | |
| Plugin 'ctrlpvim/ctrlp.vim' | |
| Plugin 'elixir-lang/vim-elixir' |
| [user] | |
| name = Toby DiPasquale | |
| email = xxx | |
| [alias] | |
| co = checkout | |
| ci = commit | |
| st = status | |
| pu = push | |
| pl = pull | |
| b = branch |
| # Tmux settings | |
| unbind-key C-b | |
| set-option -g prefix C-l | |
| set-option -g default-command "reattach-to-user-namespace -l zsh" | |
| # Set XTerm key bindings | |
| setw -g xterm-keys on | |
| # Set colors | |
| set -g default-terminal "screen-256color" |
| # Color shortcuts | |
| RED=$fg[red] | |
| YELLOW=$fg[yellow] | |
| GREEN=$fg[green] | |
| WHITE=$fg[white] | |
| BLUE=$fg[blue] | |
| CYAN=$fg[cyan] | |
| RED_BOLD=$fg_bold[red] | |
| YELLOW_BOLD=$fg_bold[yellow] | |
| GREEN_BOLD=$fg_bold[green] |
I was at Amazon for about six and a half years, and now I've been at Google for that long. One thing that struck me immediately about the two companies -- an impression that has been reinforced almost daily -- is that Amazon does everything wrong, and Google does everything right. Sure, it's a sweeping generalization, but a surprisingly accurate one. It's pretty crazy. There are probably a hundred or even two hundred different ways you can compare the two companies, and Google is superior in all but three of them, if I recall correctly. I actually did a spreadsheet at one point but Legal wouldn't let me show it to anyone, even though recruiting loved it.
I mean, just to give you a very brief taste: Amazon's recruiting process is fundamentally flawed by having teams hire for themselves, so their hiring bar is incredibly inconsistent across teams, despite various efforts they've made to level it out. And their operations are a mess; they don't real
| #!/usr/bin/env python | |
| import os, os.path, stat, sys, base64 | |
| # TOTP lib inlined | |
| import time, hmac, base64, hashlib, struct | |
| def pack_counter(t): | |
| return struct.pack(">Q", t) |