New GPT-3 Capabilities: Edit & Insert

We’ve released new versions of GPT-3 and Codex which can edit or insert content into existing text, rather than just completing existing text. These new capabilities make it practical to use the OpenAI API to revise existing content, such as rewriting a paragraph of text or refactoring code. This unlocks new use cases and improves existing ones; for example, insertion is already being piloted in GitHub Copilot with promising early results.

Read Edit Documentation

Read Insert Documentation

Try in Playground

def___

fib(10)

def fib(n):
    if n 
fib(10)=>

def fib(n):
    if n 
fib(10)=>

Improve

def fib(n):
    if n 
fib(10)=>

Improve the

def fib(n):
    if n 
fib(10)=>

Improve the runtime

def fib(n):
    if n 
fib(10)=>

Improve the runtime complexity

def fib(n):
    if n 
fib(10)=>

Improve the runtime complexity of the

def fib(n):
    if n 
fib(10)=>

Improve the runtime complexity of the function

def fib(n):
    if n 
fib(10)=>

Improve the runtime complexity of the function

def fib(n, memo={}):
    if n in memo:
        return memo[n]
    if n =>

def fib(n, memo={}):
    if n in memo:
        return memo[n]
    if n =>

Translate

def fib(n, memo={}):
    if n in memo:
        return memo[n]
    if n =>

Translate to

def fib(n, memo={}):
    if n in memo:
        return memo[n]
    if n =>

Translate to JavaScript

def fib(n, memo={}):
    if n in memo:
        return memo[n]
    if n =>

Translate to JavaScript

function fibonacci(n) {
    var memo = {};
    return (function fib(n, memo) {
        if (n in memo) return memo[n];
        var f;
        if (n =>

function fibonacci(n) {
    var memo = {};
    return (function fib(n, memo) {
        if (n in memo) return memo[n];
        var f;
        if (n =>

Write

function fibonacci(n) {
    var memo = {};
    return (function fib(n, memo) {
        if (n in memo) return memo[n];
        var f;
        if (n =>

Write this

function fibonacci(n) {
    var memo = {};
    return (function fib(n, memo) {
        if (n in memo) return memo[n];
        var f;
        if (n =>

Write this as

function fibonacci(n) {
    var memo = {};
    return (function fib(n, memo) {
        if (n in memo) return memo[n];
        var f;
        if (n =>

Write this as a

function fibonacci(n) {
    var memo = {};
    return (function fib(n, memo) {
        if (n in memo) return memo[n];
        var f;
        if (n =>

Write this as a one

function fibonacci(n) {
    var memo = {};
    return (function fib(n, memo) {
        if (n in memo) return memo[n];
        var f;
        if (n =>

Write this as a one-liner

function fibonacci(n) {
    var memo = {};
    return (function fib(n, memo) {
        if (n in memo) return memo[n];
        var f;
        if (n =>

Write this as a one-liner

function fibonacci(n) {
    var memo = {};
    return (function fib(n, memo) {
        return n in memo ? memo[n] : (memo[n] = n =>


function fibonacci(n) {
    var memo = {};
    return (function fib(n, memo) {
        return n in memo ? memo[n] : (memo[n] = n =>

/
function fibonacci(n) {
    var memo = {};
    return (function fib(n, memo) {
        return n in memo ? memo[n] : (memo[n] = n =>

/**
function fibonacci(n) {
    var memo = {};
    return (function fib(n, memo) {
        return n in memo ? memo[n] : (memo[n] = n =>

/**___
function fibonacci(n) {
    var memo = {};
    return (function fib(n, memo) {
        return n in memo ? memo[n] : (memo[n] = n =>

/**
 * Recursive Fibonacci function with memoization.
 * @param {number} n
 * @returns {number}
 */
function fibonacci(n) {
    var memo = {};
    return (function fib(n, memo) {
        return n in memo ? memo[n] : (memo[n] = n =>

GPT-3 and Codex have traditionally added text to the end of existing content, based on the text that came before. Whether working with text or code, writing is more than just appending—it’s an iterative process where existing text is revised. GPT-3 and Codex can now edit text, changing what’s currently there or adding text to the middle of content.

Inserting into the middle of text

The new insert capability adds contextually relevant text in the middle of existing content. Providing future context to the model can improve the quality of completions for applications such as writing long-form text, transitioning between paragraphs, following an outline, or guiding the model toward an ending.