(or AI programming) simply means using artificial intelligence to write computer code. This means that instead of manually programming algorithms and instructions to perform a given task, you use AI to automatically generate code that will accomplish that task. Artificial intelligence programming There are several ways to use AI in programming. One of the most common approaches is to use neural networks to generate code. . By training a neural network on a large data set of computer code, it can be taught to write code that will accomplish a specific task. A neural network is a computer model inspired by the functioning of the human brain, which can learn to perform tasks by analyzing large amounts of data An example of artificial intelligence programming is , which uses a neural network to generate computer code from task specifications given in natural language. By providing the neural network with a description of a task such as "write a program that takes a list of numbers and returns the sum of all the even numbers", . t Microsoft Research's DeepCoder projec DeepCoder can automatically generate code that will accomplish this task can also be used to generate computer code in various ways. GPT-3 For example, by providing it with a natural language description of the task at hand, can generate code that will accomplish that task. It can also be used to supplement existing code, propose changes or additions to the code to make it more efficient, or add new functionality to it. GPT-3 Example: This is how I created a calculator in python with ChatGPT and this is what he replied….. # Demande à l'utilisateur de saisir deux nombres
num1 = input("Entrez un premier nombre: ")
num2 = input("Entrez un second nombre: ")

# Demande à l'utilisateur de choisir une opération à effectuer
print("Choisissez une opération:")
print("1. Addition")
print("2. Soustraction")
print("3. Multiplication")
print("4. Division")

# Demande à l'utilisateur de sélectionner un choix
choix = input("Entrez votre choix (1/2/3/4): ")

# Effectue l'opération sélectionnée
if choix == '1':
   resultat = float(num1) + float(num2)
   print(num1,"+",num2,"=",resultat)

elif choix == '2':
   resultat = float(num1) - float(num2)
   print(num1,"-",num2,"=",resultat)

elif choix == '3':
   resultat = float(num1) * float(num2)
   print(num1,"*",num2,"=",resultat)

elif choix == '4':
   resultat = float(num1) / float(num2)
   print(num1,"/",num2,"=",resultat)
else:
   print("Entrée invalide") This python code is fully functional…. I then asked it to add more complex operations to perform such as logarithms and complex numbers to the code of the calculators and here is what it gave….. # Demande à l'utilisateur de saisir deux nombres (ou un nombre et un indice pour les logarithmes)
num1 = input("Entrez un premier nombre (ou un nombre pour un logarithme): ")
num2 = input("Entrez un second nombre (ou un indice pour un logarithme): ")

# Demande à l'utilisateur de choisir une opération à effectuer
print("Choisissez une opération:")
print("1. Addition")
print("2. Soustraction")
print("3. Multiplication")
print("4. Division")
print("5. Racine carrée")
print("6. Logarithme")
print("7. Nombre complexe")

# Demande à l'utilisateur de sélectionner un choix
choix = input("Entrez votre choix (1/2/3/4/5/6/7): ")

# Effectue l'opération sélectionnée
if choix == '1':
   resultat = float(num1) + float(num2)
   print(num1,"+",num2,"=",resultat)

elif choix == '2':
   resultat = float(num1) - float(num2)
   print(num1,"-",num2,"=",resultat)

elif choix == '3':
   resultat = float(num1) * float(num2)
   print(num1,"*",num2,"=",resultat)

elif choix == '4':
   resultat = float(num1) / float(num2)
   print(num1,"/",num2,"=",resultat)

elif choix == '5':
   resultat = float(num1) ** 0.5
   print("La racine carrée de", num1, "est", resultat)

elif choix == '6':
   import math
   resultat = math.log(float(num1), float(num2))
   print("Le logarithme de", num1, "à base", num2, "est", resultat)

elif choix == '7':
   num1 = input("Entrez la partie réelle: ")
   num2 = input("Entrez la partie imaginaire: ")
   resultat = complex(float(num1), float(num2))
   print(num1,"+",num2,"i","=",resultat)

else:
   print("Entrée invalide") Again the code is perfectly functional I then decided to go even further by asking him to create a calculator with a graphical interface and again it worked The more complex the problem becomes, the more it will be necessary to have the necessary knowledge to be able to debug the code. Conclusion : . However, it should be noted that AI is and it is important to carefully before using it in critical applications. Artificial intelligence programming can be very useful in many cases, as it allows you to quickly generate code without having to manually write complex algorithms not infallible check and test AI-generated code A possible is to develop . Currently, it is necessary to manually check the code generated by GPT-3 to ensure that it works correctly and that it follows good programming practices. By developing methods to automatically assess the quality of the code generated by GPT-3, it will be possible to make programming by artificial intelligence even more efficient and fast. This would make it possible to extend the possibilities of programming by artificial intelligence to a greater number of domains. improvement of this technique methods to automatically evaluate the quality of the code generated by GPT-3

This story contains new, firsthand information uncovered by the writer.

Welcome to the World of Artificial Intelligence Programming

About Author

Comments

TOPICS

THIS ARTICLE WAS FEATURED IN

Related Stories

Untitled Story

The Noonification: How Often Do NFTs Pass The Howey Test? (1/13/2023)

Darwin's Hybrid Intelligence to Align AI & Human Goals for Startups & VCs

The Noonification: White Man (11/26/2022)

The Noonification: The Metaverse is a Sh*tshow (11/2/2022)

100 Days of AI Day 1: From Newsletter to Podcast, Leveraging AI for Audio Transformation

The Noonification: How Often Do NFTs Pass The Howey Test? (1/13/2023)

Darwin's Hybrid Intelligence to Align AI & Human Goals for Startups & VCs

The Noonification: White Man (11/26/2022)

The Noonification: The Metaverse is a Sh*tshow (11/2/2022)

100 Days of AI Day 1: From Newsletter to Podcast, Leveraging AI for Audio Transformation

Light-Mode

Classic

Newspaper

Dark-Mode

Neon Noir

Minty

HN StartUps