kibotu

#!/usr/bin/env bash
set -Eeo pipefail

# Safely remove selected iOS Simulator runtimes and devices orphaned
# by those removals.
#
# Requires macOS, Xcode Command Line Tools, and Python 3.

# ------------------------------------------------------------
# Colors

karpathy

LLM Wiki

A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

The core idea

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.

kibotu

#!/usr/bin/env python3
"""macOS Developer Cleanup — allowlist-based, dry-run by default, agent-friendly.

Usage:
    dev-cleanup.sh                       # dry-run plan of the safe default sweep
    dev-cleanup.sh --apply               # interactive apply (asks before deleting)
    dev-cleanup.sh --apply --yes         # non-interactive apply (agent mode)
    dev-cleanup.sh --all --json          # machine-readable plan
    dev-cleanup.sh --all --apply --yes --json --report cleanup.json

karpathy

"""
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

JolandaVerhoef

/*
* Copyright 2023 The Android Open Source Project
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
*   https://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software

coolaj86

Chat GPT "DAN" (and other "Jailbreaks")

• https://chat.openai.com/
• Is ChatGPT "DAN" Real? Gonna find out [Part 1]
  (https://www.youtube.com/watch?v=-q8woRG9FrI)
• Part 2: I thought ChatGPT DAN was a hoax, but...
  (https://www.youtube.com/watch?v=rHZRrDu3A2U&lc=UgxfrxX8aK7gnCzkend4AaABAg)

surajsau

@Composable
fun ParallaxScreen(modifier: Modifier = Modifier) {
    val context = LocalContext.current
    val scope = rememberCoroutineScope()

    var data by remember { mutableStateOf<SensorData?>(null) }

    DisposableEffect(Unit) {
        val dataManager = SensorDataManager(context)
        dataManager.init()

darvld

package cu.spin.catalog.ui.components

import android.annotation.SuppressLint
import androidx.compose.animation.core.animateFloat
import androidx.compose.animation.core.updateTransition
import androidx.compose.runtime.State
import androidx.compose.ui.Modifier
import androidx.compose.ui.composed
import androidx.compose.ui.draw.drawWithCache
import androidx.compose.ui.geometry.Offset

devadvance

#######################################
# Displays a yes/no prompt to continue that repeats until input matches.
# Arguments:
#   $1 - (optional) a string representing the yes/no question to ask
#   $2 - (optional) a string representing the prompt style.
# Returns:
#   0 to proceed further (indicates "yes"), 1 to stop (indicates "no").
#######################################
continue_prompt() {
    local prompt default reply

kevinvanmierlo

package nl.kevinvanmierlo.testtransitiondrawable;

import android.graphics.Canvas;
import android.graphics.ColorFilter;
import android.graphics.PixelFormat;
import android.graphics.Rect;
import android.graphics.drawable.Drawable;
import android.os.SystemClock;

import androidx.annotation.NonNull;