Artificial intelligence creation

Question

Need help creating an Artificial intelligence 🥺

Answer 1

Louis Musanda let's start by answering a few questions ..

What problem or problems do you want your AI to solve?
This could be anything from recognizing objects in images to generating creative text.

What kind of AI do you need?
Consider options like machine learning, deep learning, or rule-based systems.

Answer 2

ChatGPT and other AI tools have API's that you can use. They provide an API, with a key, and you can use python libraries to talk to those APIs with your key. You can read about that here: https://platform.openai.com/docs/overview

Other AI tools are available and have APIs as well.

Answer 3

You know you can use neuroscience the study of the human brain and somehow make something similar in code

Answer 4

Julian Willis How do we do that?

Answer 5

It is simple but here is a neural network

Answer 6

import tensorflow as tf
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Flatten
from tensorflow.keras.datasets import mnist
from tensorflow.keras.utils import to_categorical

# Load and preprocess the MNIST dataset
(x_train, y_train), (x_test, y_test) = mnist.load_data()
x_train = x_train / 255.0 # Normalize pixel values to [0, 1]
x_test = x_test / 255.0

# One-hot encode the labels
y_train = to_categorical(y_train, 10)
y_test = to_categorical(y_test, 10)

# Build the neural network
model = Sequential([
Flatten(input_shape=(28, 28)), # Flatten 28x28 images into 1D vectors
Dense(128, activation='relu'), # First hidden layer with 128 neurons
Dense(64, activation='relu'), # Second hidden layer with 64 neurons
Dense(10, activation='softmax') # Output layer for 10 classes
])

# Compile the model
model.compile(optimizer='adam',
loss='categorical_crossentropy',
metrics=['accuracy'])

# Train the model
model.fit(x_train, y_trai