CONTENT
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.
Chat With AI Assistant
Chatting with AI assistants is usually not private or confidential, here are few solutions which respect the user privacy.
- Ask Brave : Website | Chat Interface
- Apertus : Website | Chat Interface
- Lumo : Website | Chat Interface
There is also local solutions, have a look here.
Ollama
This section has its own page, here.
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.
Front-Ends, GUI for Stable Diffusion
Models
Links
- Stable Diffusion Online
- Creating a Consistent Character as a Textual Inversion Embedding with Stable Diffusion
- How to use models
- Create Stunning SVG/Vector Art in Stable Diffusion | AUTOMATIC1111 Guide
- Generate Mindblowing SVG/Vector art in Stable Diffusion | AUTOMATIC1111 Guide
- How to Install Stable Diffusion on Ubuntu || Run Stable Diffusion AI on Linux
- How to Install Stable Diffusion - automatic1111
- Install Stable Diffusion | Linux Mint CPU Only
Other
- AI images for LibreOffice You write the text describing the scene and an AI generated image powered by AIHorde appears.
- gimp-stable-diffusion Gimp plugin to create images with AI powered by Stable Horde.
- Stability Matrix Multi-Platform Package Manager for Stable Diffusion.
Links
Apps that run AI locally
- Cortex Cortex is an Local AI engine for developers to run and customize Local LLMs.
- Jan Open source ChatGPT-alternative that runs 100% offline.
- LM Studio Experiment with LLMs on your computer. Chat interface and programmable API.
- Msty One app, one-click setup, no Docker, no terminal, offline and private, unique and powerful features.
- Ollama Open-source project that enables users to easily run large language models (LLMs) locally on their machines.
- Open WebUI Open WebUI is an extensible, feature-rich, and user-friendly self-hosted AI interface designed to operate entirely offline.
- Page Assist Page Assist is an open-source extension that provides a Sidebar and Web UI for your Local AI model.
Other
- Apertus EPFL, ETH Zurich, and the Swiss National Supercomputing Centre (CSCS) has released Apertus, Switzerland’s first large-scale open, multilingual language model, a milestone in generative AI for transparency and diversity.
- Civitai The Home of Open-Source Generative AI.
- Quickstart Guide to Flux
- Hugging Face The AI community building the future.
- Hugging Face / Tools Popular tools made by the community.
- Prodia Add Generative AI into your App.
- Dezgo Online Free AI Image Generator.
- Deep Dream Generator AI Image Generator: AI Picture & Video Maker to Create AI Art Photos Animation.
- Easy With AI Best AI Tools & Services.
- Best Free AI Courses to Level Up Your Skills
- Brave Brings Local AI to the Browser
- LTX-Video Real-time AI video generation open source model. | Documentation | Hugging Face | Hugging Face Playground| GitHub | fal
- How to Protect Your Privacy From ChatGPT and Other AI Chatbots
- Lumo (Proton AI Assistant) | announcement
- AI Horde This is a volunteer crowd-sourced distributed cluster of image generation workers and text generation workers by the volunteer organization Haidra.
- Haidra Haidra is the non-profit community organization behind the revolutionary AI Horde project.