Artificial Intelligence (AI)

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What is Artificial Intelligence?

Artificial Intelligence (AI) refers to the ability of computers or machines to think and act like humans. It means that these systems can learn from data, make decisions on their own, and interact with us in various ways.

AI is like a super-smart computer program that can learn, think, and act like a human being but instead of relying on human expertise, it uses:

Algorithms: A set of instructions that help the computer make decisions.
Data: Lots of information that the computer can learn from (like examples or past experiences).
Computing power: The brain behind the operation, which makes calculations and processes data quickly.

AI can be used in many areas, such as: chatbots, virtual assistants (e.g., Alexa, Google Assistant or Siri), self-driving cars, image recognition systems, and more!

Benefits

Increased Efficiency: AI can automate repetitive tasks, freeing up human resources for more complex work.
Improved Accuracy: AI systems can reduce errors by analyzing vast amounts of data and making decisions based on patterns.
Innovation: The potential to drive innovation in various fields, such as science, art, or entertainment.

However, like any powerful technology, AI raises concerns about job losses, misuse for malicious purposes (e.g., deepfakes), and the need for careful regulation and governance.

The balance between generative and retrieval-based AI lies in understanding their respective strengths and weaknesses.

What is Retrieval-based AI?

Retrieval-based artificial intelligence (AI) refers to a type of machine learning that focuses on retrieving relevant information from existing databases or knowledge graphs. The primary goal of retrieval-based AI is to provide users with accurate and efficient access to stored data.

Key Features

Query-based: Retrieval-based AI systems respond to user queries, providing relevant results based on the input.
Database-driven: These systems rely on pre-existing databases or knowledge graphs as their primary source of information.
Information retrieval: The core function is to retrieve and provide relevant data from these stored sources.

Real-World Applications

Search Engines: Search engines use retrieval-based AI to return relevant web pages based on user queries.
Customer Support Systems: These systems use retrieval-based AI to retrieve relevant customer support data and answer common queries.
Knowledge Graphs in E-commerce: Some e-commerce platforms utilize knowledge graphs to provide customers with accurate product information.

Benefits

Efficient data access: Retrieval-based AI enables rapid access to stored data, reducing the need for manual searches.
Improved accuracy: These systems can provide more accurate results by drawing from a large database of pre-existing information.
Scalability: As databases grow in size and complexity, retrieval-based AI can handle increased volumes of queries with minimal degradation.

What is Generative-based AI?

Generative artificial intelligence (AI) refers to a type of machine learning that focuses on generating new data, such as images, text, music, or other creative content. The primary goal of generative-based AI is to produce original and diverse outputs based on patterns learned from existing data.

Key Features

Creative generation: Generative-based AI systems generate novel and realistic content without human intervention.
Learning from data: These systems learn the underlying patterns and structures in a dataset, which they can then use to create new examples.
Exploratory nature: Generative-based AI often involves exploration of uncharted territory, as it searches for new combinations of features or attributes.

Real-World Applications

Artistic content creation: Generative-based AI is used in music generation (e.g., Amper Music), image and video synthesis (e.g., Prisma), and text writing (e.g., language models).
Data augmentation: These systems can generate additional training data to improve the performance of other machine learning models.
Virtual product design: Generative-based AI is used in industries like fashion, home decor, and automotive to create virtual prototypes.

Benefits

Increased creativity: Generative-based AI enables machines to explore new ideas and concepts, which can lead to innovative solutions.
Time-saving: These systems can generate content at an incredible pace, reducing the time required for human creation.
Personalization: By generating tailored experiences based on user data, generative-based AI can improve engagement and satisfaction.

Ollama

Ollama is an open-source project that enables users to easily run large language models (LLMs) locally on their machines. It simplifies the process of downloading, installing, and interacting with a wide range of LLMs, empowering users to explore their capabilities without requiring extensive technical expertise or reliance on cloud-based platforms.

🛈 Ollama is a Command-Line (CLI) Tool, but there are front-ends, Graphical User Interface (GUI). See below.

Front-Ends, GUI for Ollama

Msty (Application)
Open WebUI (Application)
Page Assist (Web browser extension)

Free course of Ollama by Matt Williams

Install Ollama

Download Ollama from the official website.

Download for macOS
Download for Linux | Install: curl -fsSL https://ollama.com/install.sh | sh
Download for Windows

Uninstall Ollama On Linux

To uninstall Ollama on Linux, follow these steps:

1. Stop the Ollama service:

sudo systemctl stop ollama

This command halts the Ollama service.

2. Disable the Ollama service to prevent it from starting automatically on boot:

sudo systemctl disable ollama

This ensures that Ollama won’t automatically start up in the future.

3. Remove the Ollama service file from the systemd directory:

sudo rm /etc/systemd/system/ollama.service

This deletes the service file from your system.

4. Remove the Ollama binary from your system. Depending on where it was installed, run one of the following commands:

sudo rm $(which ollama)

This command removes the binary from your bin directory.

5. Delete the directory where Ollama stores its models and any associated user and group accounts:

sudo rm -r /usr/share/ollama
sudo userdel ollama
sudo groupdel ollama

These commands delete any downloaded models and remove the Ollama user and group from your system.

After completing these steps, you can verify that Ollama has been successfully uninstalled by checking for any remaining files or services. You can use the following command to check if the service is still listed:

systemctl list-units --type=service | grep ollama

If no results are returned, the uninstallation was successful.

Stable Diffusion (text-to-image)

Stable Diffusion is a type of generative artificial intelligence (AI) model that produces photorealistic images from text prompts. It’s a latent text-to-image diffusion model, trained on a massive dataset of images, which enables it to generate high-quality images that resemble real photographs.

Artificial Intelligence (AI)

CONTENT

What is Artificial Intelligence?

Benefits

What is Retrieval-based AI?

Key Features

Real-World Applications

Benefits

What is Generative-based AI?

Key Features

Real-World Applications

Benefits

Ollama

Front-Ends, GUI for Ollama

Free course of Ollama by Matt Williams

Install Ollama

Uninstall Ollama On Linux

1. Stop the Ollama service:

2. Disable the Ollama service to prevent it from starting automatically on boot:

3. Remove the Ollama service file from the systemd directory:

4. Remove the Ollama binary from your system. Depending on where it was installed, run one of the following commands:

5. Delete the directory where Ollama stores its models and any associated user and group accounts:

Links

Stable Diffusion (text-to-image)

Front-Ends, GUI for Stable Diffusion

Models

Links

Links

Apps that run AI locally

Other