crizCraig

Game of AGI

Play the game in Colab

View simulator source

Game of AGI (GOA) is a socio-techno monte carlo simulation which estimates the existential risk posed by AGI. You play by setting various factors, i.e. AI spending and AGI safety spending, along with their uncertainties and GOA returns the existential risk, corruption risk, and value alignment probability associated with your guesses by sampling 1M times from guassian distributions of your guesses.

N.B. When referring to AGI's as separate entities, I am referring to autonomous groups of humans (i.e. companies, governments, groups, organizations) that are in control of some tech stack capable of AGI. There may be several autonomous AGIs within any certain stack, but we assume they have an umbrella objective defined by

EpicWink

# Licensed under the Apache License, Version 2.0
# License included at https://github.com/docker/docker-py/blob/master/LICENSE

"""Patch Docker for Python with device-requests."""

from docker.types import base as docker_types_base
from docker.models import containers as docker_models_containers
from docker.types import containers as docker_types_containers
from docker.utils import utils as docker_utils

crizCraig

#!/usr/bin/env bash

set -e  # Abort script at first error, when a command exits with non-zero status (except in until or while loops, if-tests, list constructs)
set -u  # Attempt to use undefined variable outputs error message, and forces an exit
set -x  # Similar to verbose mode (-v), but expands commands
set -o pipefail  # Causes a pipeline to return the exit status of the last command in the pipe that returned a non-zero return value.

DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"

# end boilerplate from: https://gist.github.com/crizCraig/f42bc250754bed764ada5f95d101dbea

andrewjong

import torch
from torchvision import datasets

class ImageFolderWithPaths(datasets.ImageFolder):
    """Custom dataset that includes image file paths. Extends
    torchvision.datasets.ImageFolder
    """

    # override the __getitem__ method. this is the method that dataloader calls
    def __getitem__(self, index):

jbenet

IPFS Tooling for datasets

Background

We need some tooling for a certain set of use cases around archival and dataset management. This tooling is for fitting how people work with large files and large datasets.

Grounding Assumptions

Basic grounding assumptions here:

• datasets are "large" (From GB to EB in size)

jbn

import asyncio
from aiohttp import web
import subprocess


async def uptime_handler(request):
    # http://HOST:PORT/?interval=90
    interval = int(request.GET.get('interval', 1))
    
    # Without the Content-Type, most (all?) browsers will not render 

crizCraig

"\e[A": history-search-backward
"\e[B": history-search-forward
set show-all-if-ambiguous on
set completion-ignore-case on

acdha

#!/usr/bin/env python
# encoding: utf-8

from pprint import pformat, pprint
import logging


class PasswordMaskingFilter(logging.Filter):
    """Demonstrate how to filter sensitive data:"""

till

#!/usr/bin/env python

import sys
import os
import boto
import pprint

del_flag = ''
if len(sys.argv) > 1:
    del_flag = sys.argv[1]

itsderek23

# docker build -t="rails" .

FROM ubuntu:12.04

RUN apt-get update

## MYSQL
RUN apt-get install -y -q mysql-client libmysqlclient-dev

## RUBY