zurawiki

Keybase proof

I hereby claim:

• I am rzurawicki on github.
• I am rmz (https://keybase.io/rmz) on keybase.
• I have a public key whose fingerprint is 4E6E C089 CFFF 1CD5 D89F B3BA A6A3 8DB5 86CA D001

To claim this, I am signing this object:

zurawiki

Keybase proof

I hereby claim:

• I am zurawiki on github.
• I am rmz (https://keybase.io/rmz) on keybase.
• I have a public key whose fingerprint is 4E6E C089 CFFF 1CD5 D89F B3BA A6A3 8DB5 86CA D001

To claim this, I am signing this object:

zurawiki

A3 Design Doc

Rottweiler OS161

Stella Pantella - Roger Zurawicki

Data Structures

Coremap

zurawiki

"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np

# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)

zurawiki

/**
 * This file contains AI generated code. Generated code exists
 * between the BEGIN AI SECTION and END AI SECTION designators.
 *
 * @ai-generated model=openai.gpt-4
 */
import React from "react";

interface Person {
  name: string;

zurawiki

Readme Example

This is an proposal for how to label code that is AI-generated from code that is human authors.

These annotations are useful for human-driven code review, allowing code reviews to have more context on where the code is coming from. These annotations are also useful for AI and code applications. AIs can find places generated code can be optimized and future models can better distinguish generated code from human code.

Core Spec