crizCraig

def generic_unsync(func: Callable[..., Any]) -> Callable[..., Any]:
    """
    A function that dynamically decides whether to run asynchronously
    or synchronously based on whether it's in an async context,
    but always returns the result synchronously so that
    you can use it from an async or sync context.
    """
    from unsync import unsync  # type: ignore  # pylint: disable=import-outside-toplevel

    @unsync  # type: ignore

crizCraig

import asyncio
from typing import AsyncGenerator

async_q: asyncio.Queue[str] = asyncio.Queue()

async def producer() -> None:
    try:
    # Assuming `a` should be a value like 1, 2, etc.
    #     a = 1
        await async_q.put(str(a))  # a not defined

crizCraig

1. Love, connection, caring, compassion, tolerance, helping others, sharing, and acceptance. We value the ability to love and to be loved, to connect with others, to care for others, to be compassionate, to be tolerant, to share, to help others, and to accept others.
2. Freedom and autonomy. We value the ability to make our own decisions and to have control over our own lives. We value the ability to believe what we want, to have our own thoughts, and to have our own feelings. We value the ability to have our own opinions and to express them freely. We value the ability to have our own goals and to pursue them. We value the ability to have our own values and to live by them. We value the ability to have our own identity and to be ourselves.
3. Harmony and peace. We value the ability to live in harmony with others and our surroundings and to live in peace without war, violence, or conflict.
4. The right to life and the pursuit of happiness. We value the ability to live and to pursue happiness. We value the abi

crizCraig

import asyncio
import time
from typing import Callable, Any

def timed(fn: Callable[..., Any]) -> Callable[..., Any]:
    """
    Decorator log test start and end time of a function

    :param fn: Function to decorate
    :return: Decorated function

crizCraig

asdf

crizCraig

from datetime import datetime

DATE_STR = datetime.now().strftime('%Y_%m-%d_%H-%M.%S.%f')

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

crizCraig

# In a family with two children, what are the chances, if **one** of the children is a girl, that both children are girls?
from random import random
n = 0
c = 0
for i in range(100000):
    a = random() < 0.5
    b = random() < 0.5
    if a or b:  # **one** implies _either_ child
        n += 1
        if a and b:

crizCraig

import os

from deepdrive_zero.experiments import utils
from spinup.utils.run_utils import ExperimentGrid
from spinup import ppo_pytorch
import torch

experiment_name = os.path.basename(__file__)[:-3]
notes = """
Simplest environment. Should reach 98% average angle accuracy in about 5 minutes

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# Lint as: python3
"""Pseudocode description of the MuZero algorithm."""
# pylint: disable=unused-argument
# pylint: disable=missing-docstring
# pylint: disable=g-explicit-length-test

from __future__ import absolute_import
from __future__ import division
from __future__ import google_type_annotations
from __future__ import print_function