Archetapp

Polymarket BTC 5-Minute Up/Down Trading Bot — Build Guide

What This Bot Does

This bot trades Polymarket's "BTC Up or Down" 5-minute binary markets. Every 5 minutes, Polymarket opens a market asking: "Will BTC be higher or lower than the opening price when this 5-minute window closes?" You buy "Up" or "Down" tokens at some price (e.g. $0.50–$0.95), and if you're right, each token pays out $1.00. If you're wrong, you lose your bet.

The bot uses technical analysis on real-time Binance BTC price data to predict the outcome, then places the trade on Polymarket right before the window closes — when we have the most information but (ideally) before the token price has fully priced in the outcome.

---

ayashiiiyo

import { createHash, createHmac, createDecipheriv, randomUUID } from 'node:crypto';
import { setTimeout } from 'node:timers/promises';

const API = 'https://api-v2.zuoyoupk.com/v1.0';
const MUSIC = 'https://musicapi-cn.zuoyoupk.com/v1.0/music_lab/separate';
const md5 = (value) => createHash('md5').update(value).digest('hex');
const DEFAULT_KEYS = {
  storageSign: '7QbB#e4a_X[V45oBooQHxcfi09',
  storageCipher: 'x!TBbOUbT6yJQi6b#321q',
  taskSign: '9f4659d5edc665d9fe3a5b232f489372',

dexhorthy

No AI Slop: A Manifesto

Written by the speakers and attendees of AIE Code Summit 2026

In 2001, 17 software engineers and leaders got together at a ski lodge in Snowbird, Utah to understand the biggest challenge of their time: heavyweight, documentation-driven software development processes.

Out of this we got the Agile Manifesto, four values and twelve principles that changed how most of the industry builds software.

Today we convene to build our own manifesto - the No AI Slop manifesto.

logicx24

name	vibecoder-review
description	Practical OWASP-focused security review for fast-moving codebases built with AI assistance - catches common patterns where speed trumps security (exposed secrets, auth bypasses, missing access controls, injection vulnerabilities)

Vibecoder Security Review

Overview

Target audience: Fast-moving codebases built by developers using AI assistance, rapid prototyping tools, and modern frameworks. These projects prioritize speed and iteration, often skipping security fundamentals.

interactivetech

# GLM-5.3 Flash on Single NVIDIA GB10 with llama.cpp

This runbook documents a working local deployment of GLM-5.3 Flash on an single NVIDIA GB10 / DGX Spark-class system, including tool-calling benchmark results.

## Hardware and software

```text
Hardware: Single NVIDIA GB10 / DGX Spark
Model:    GLM-5.3-Flash UD-Q2_K_XL GGUF
Backend:  llama.cpp

udance4ever

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

# Nov 14, 2026
#
# Script to build and patch original Fallout .exe to address audio/stuttering/slowdown issues
#
# Extension of the amazing work by @emrikol in his Fallout 2 patch:
#
#  https://gist.github.com/emrikol/313701a61d0e692798fe938cf6ac24b0

jameselsey

IMAGE := /tmp/camera.jpg
INFER_IMAGE := camera.png
DEMO_PYTHON := .demo-venv/bin/python

.PHONY: infer-it infer demo capture setup

# Demo 1: Start an interactive text conversation with the model.
infer-it:
	geniex infer qualcomm/Qwen3-VL-4B-Instruct

Alimammiya

Free GATE CSE Study Material for 2027 Aspirants: Download Subject wise Notes & PYQs

Welcome to the comprehensive, community-driven resource repository for GATE Computer Science & Information Technology (CS & IT) 2027 aspirants. Securing a top rank in the Graduate Aptitude Test in Engineering (GATE) unlocks direct admissions to premier postgraduate programs (M.Tech/Ph.D.) at IITs, NITs, and IISc, alongside prestigious technical roles within leading PSUs.

This repository serves as a centralized documentation hub compiled from authoritative open-source archives, topper strategies, and verified learning pathways for your GATE CSE study material search.

---

Table of Contents

1. Core Syllabus Structure & Weightage Analysis

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.

geohot

Compilers for Machine Learning

A hands-on one semester course where students build their own compiler from scratch, starting from elementwise programs and ending with training SOTA LLMs on GPUs. This course aggressively builds on the previous week, and is an exercise in slop management. If you let any slop in early, it will compound and you will not finish the class.

Course description: This course covers the design and implementation of a modern machine learning compiler, and examines the interaction between IR design, hardware capabilities, and the structure of machine learning programs. Topics covered include term rewriting, code generation, movement operators, kernel fusion, memory hierarchies, GPU architecture, automatic differentiation, and flash attention. It is a project course, providing experience with performance-oriented programming, managing a codebase that grows all semester, and working in 1 or 2 person teams, culminating in a compiler capable of training modern LLMs.

Prerequisites: This c