Artificial Intelligence: AI Tools

GAI tools utilize artificial intelligence to create various types of content, including text, images, audio, and video. Key features of GAI tools include the following: 

• Creativity: Generate novel and original outputs.   
• Efficiency: Produce content quickly and in large volumes.   
• Versatility: Adapt to different creative styles and formats.   
• Personalization: Tailor content to specific user preferences.

RAG tools combine the power of Large Language Models (LLMs) with external knowledge sources. LLMs excel at understanding and generating human language. RAG enhances LLMs by allowing them to access and process information from a specific knowledge base (like documents, databases, or websites). Some key features of RAG tools include the following:

• Factual Accuracy: Provides more reliable and up-to-date information.   
• Contextual Relevance: Delivers responses tailored to specific situations and queries.   
• Improved Performance: Enhances the quality and consistency of LLM outputs.

Agentic AI refers to autonomous artificial intelligence systems capable of achieving goals without constant human intervention. Key capabilities include:

• Autonomous Decision-Making: These systems analyze situations and make independent decisions.
• Goal-Oriented Behavior: They break down complex tasks into smaller steps to efficiently reach objectives.
• Proactive Actions: Agentic AI identifies opportunities and potential issues, taking initiative instead of merely reacting.
• Continuous Learning: These systems improve over time by learning from experiences.

An example is a self-driving car, which constantly analyzes traffic and makes real-time decisions for safe navigation. Agentic AI represents a shift from passive systems to proactive, autonomous ones.

Text Generation

• ChatGPT (OpenAI): A flexible conversational AI that generates text, translates languages, creates various types of creative content, and provides informative answers to user questions.
• Gemini (Google AI): Another advanced conversational AI similar to ChatGPT, recognized for its capacity to deliver thorough and informative responses.
• Copilot (Microsoft): Integrates with Microsoft applications like Word, Excel, PowerPoint, Outlook, and Teams to provide real-time assistance using large language models for content generation, summarization, and question-answering.
• Siri (Apple): Primarily a task-focused AI tool, it is evolving with recent updates to incorporate generative AI capabilities for more contextual and creative responses.
• Alexa (Amazon): Uses GAI to create new content based on user prompts, among others. 
• Claude (Anthropic): A chatbot and LLM trained on extensive natural language datasets to perform various tasks, including answering questions, summarizing documents, generating text, creating diagrams and animations, and solving math and coding challenges.
• DeepSeek is a powerful AI model that offers several advantages over other models, including efficiency, affordability, and reduced bias. However, DeepSeek is not considered transparent regarding its data collection practices. For more information, see the Ethics page.

Image Generation

• DALL-E 2 (OpenAI): Generates breathtaking and creative images based on written descriptions.
• Midjourney: Renowned for its artistic qualities and often surreal image-generation abilities.
• Stable Diffusion: An open-source image generation model that enables greater customization and experimentation.

Audio Generation

• Murf: AI-powered text-to-speech with a wide range of voices and styles.
• Synthesia: Creates realistic AI-generated videos with human-like avatars.
• ElevenLabs: Specializes in high-quality voice cloning and text-to-speech.

Code Generation

• GitHub Copilot: Assists developers with code suggestions and autocompletion.
• Amazon CodeWhisperer: Helps developers write code faster and more efficiently.

Legal Research

GAI tools can offer benefits for legal research, but they come with significant limitations, such as potential inaccuracies, biases in the training data, and ethical concerns regarding confidentiality and proper attribution. In using GAI tools for legal research, legal professionals must critically assess GAI-generated information and maintain human oversight in their decision-making processes. 

RAG tools in legal research offer significant advantages over stand-alone GAI tools by ensuring factual accuracy through the retrieval of real-world data from legal sources, thus minimizing errors and biases. They are specifically designed for the legal domain, enabling them to better understand terminology and provide tailored responses to legal queries. Additionally, RAG tools enhance transparency by offering source citations, allowing for easy verification and improved auditability of the information used.

The AI tools from Westlaw and Lexis are mainly classified as RAG tools. Although they incorporate some aspects of GAI—such as text generation—their primary focus is on retrieving and utilizing specific legal information from their own databases, which categorizes them primarily as RAG tools. Some key points include the following:

• Focus on Legal Databases: These tools primarily depend on accessing and processing information from extensive legal databases, such as case law, statutes, and regulations.
• Retrieval is Crucial: Their primary function is to retrieve relevant legal documents in response to user queries, which is fundamental to their operation.
• Generation with Context: The AI utilizes retrieved information to create summaries or analyses or draft legal documents based on the specific legal context from its databases.

While Westlaw and Lexis are not fully "agentic" in the sense of being able to independently perform complex tasks, they do have some agentic qualities, such as proactively suggesting relevant information and automating certain tasks.

OpenAI's Deep Research (considered an agentic capability within ChatGPT) purports to allow users to conduct thorough research across various domains by leveraging an optimized model for web browsing and data analysis, generating detailed reports quickly, though it is currently limited to certain users and may have occasional accuracy issues.

GAI and RAG tools signify major technological progress. GAI tools boost human creativity and productivity, while RAG tools improve the reliability and informative value of AI systems.

Focus

• GAI tools primarily focus on creative content generation.
• RAG tools prioritize factual accuracy and information retrieval.

Data Sources

• GAI tools primarily rely on internal training data.
• RAG tools integrate external knowledge sources.   

Applications

• GAI tools have a broader range of applications.
• RAG tools are particularly well-suited for tasks that require access to specific information.

AI encompasses various subfields, with GAI and agentic AI being two prominent types. GAI represents the creative aspect of AI, focusing on generating new content (like text, images, or music) by analyzing and mimicking patterns in existing data. This is evident in tools like ChatGPT and DALL-E. 

On the other hand, agentic AI is designed to operate autonomously in order to achieve specific objectives. It is characterized by its ability to make decisions and respond dynamically to real-time information, as seen in applications like autonomous vehicles and robotic process automation. For example, a smart assistant managing your calendar showcases the capabilities of agentic AI.

While GAI typically works within predefined boundaries, agentic AI is more flexible and responsive. These two types of AI can complement one another effectively; for instance, in a virtual customer service agent, GAI can craft personalized responses while agentic AI manages the interaction in real-time.

For more information, check out Bernard Marr's excellent article Generative AI Vs. Agentic AI: The Key Differences Everyone Needs To Know.