Retrieval Augmented Generation - gettectonic.com
copilots and agentic ai

Copilots and Agentic AI

Agentic AI vs. Copilots: Defining the Future of Generative AI Artificial Intelligence has rapidly evolved, progressing from simple automation to generative models, to copilots. But now, a new player—Agentic AI—has emerged, promising to redefine the AI landscape. Is Agentic AI the next logical step, or will it coexist alongside copilots, each serving distinct roles? Copilots

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AI Research Agents

AI Research Agents

AI Research Agents: Transforming Knowledge Discovery by 2025 (Plus the Top 3 Free Tools) The research world is on the verge of a groundbreaking shift, driven by the evolution of AI research agents. By 2025, these agents are expected to move beyond being mere tools to becoming transformative assets for knowledge discovery, revolutionizing industries such

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Fully Formatted Facts

Fully Formatted Facts

A recent discovery by programmer and inventor Michael Calvin Wood is addressing a persistent challenge in AI: hallucinations. These false or misleading outputs, long considered an inherent flaw in large language models (LLMs), have posed a significant issue for developers. However, Wood’s breakthrough is challenging this assumption, offering a solution that could transform how AI-powered

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AI Prompts to Accelerate Academic Reading

AI Prompts to Accelerate Academic Reading

10 AI Prompts to Accelerate Academic Reading with ChatGPT and Claude AI In the era of information overload, keeping pace with academic research can feel daunting. Tools like ChatGPT and Claude AI can streamline your reading and help you extract valuable insights from research papers quickly and efficiently. These AI assistants, when used ethically and

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Salesforce Data Quality Challenges and AI Integration

Salesforce Data Quality Challenges and AI Integration

Salesforce Data Quality Challenges and AI Integration Salesforce is an incredibly powerful CRM tool, but like any system, it’s vulnerable to data quality issues if not properly managed. As organizations race to unlock the power of AI to improve sales and service experiences, they are finding that great AI requires great data. Let’s explore some

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2024 AI Glossary

2024 AI Glossary

Artificial intelligence (AI) has moved from an emerging technology to a mainstream business imperative, making it essential for leaders across industries to understand and communicate its concepts. To help you unlock the full potential of AI in your organization, this 2024 AI Glossary outlines key terms and phrases that are critical for discussing and implementing

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The Role of Data to Harness AI

The Role of Data to Harness AI

Harnessing AI for Enhanced Sales and Service: The Role of Data Organizations are racing to leverage AI to enhance their sales and service experiences. The Role of Data to Harness AI cannot be underestimated. However, great AI solutions rely on quality data. Traditionally, companies have managed structured data—neatly organized into rows and columns, such as

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LLMs Are Gullible

LLMs Are Gullible

Andrew Best wrote in Artificial Intelligence in Plain English that LLMs are gullible. Article summarized below. LLMs are gullible, which is why various experiments are often conducted on them to observe their reactions to different types of prompts. Through extensive experimentation, more insight is gained into their actual functioning. Today, a humorous discovery was made

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RAG Chunking Method

RAG Chunking Method

Enhancing Retrieval-Augmented Generation (RAG) Systems with Topic-Based Document Segmentation Dividing large documents into smaller, meaningful parts is crucial for the performance of Retrieval-Augmented Generation (RAG) systems. RAG Chunking Method. These systems benefit from frameworks that offer multiple document-splitting options. This Tectonic insight introduces an innovative approach that identifies topic changes using sentence embeddings, improving the

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Use Cases for Retrieval-Augmented Generation

Use Cases for Retrieval-Augmented Generation

The applications of Retrieval-Augmented Generation (RAG) are diverse and expanding rapidly. Use Cases for Retrieval-Augmented Generation. Here are some key examples of how and where RAG is being utilized: Search Engines Search engines have implemented RAG to deliver more accurate and up-to-date featured snippets in their search results. RAG is particularly useful for applications of

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AI Design Beyond the Chatbot

AI Design Beyond the Chatbot

As AI continues to advance, designers, builders, and creators are confronted with profound questions about the future of applications and how users will engage with digital experiences. AI Design Beyond the Chatbot. Generative AI has opened up vast possibilities, empowering people to utilize AI for tasks such as writing articles, generating marketing materials, building teaching

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Generative AI Prompts with Retrieval Augmented Generation

Generative AI Prompts with Retrieval Augmented Generation

By now, you’ve likely experimented with generative AI language models (LLMs) such as OpenAI’s ChatGPT or Google’s Gemini to aid in composing emails or crafting social media content. Yet, achieving optimal results can be challenging—particularly if you haven’t mastered the art and science of formulating effective prompts. Generative AI Prompts with Retrieval Augmented Generation. The

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Evaluating RAG With Needle in Haystack Test

Evaluating RAG With Needle in Haystack Test

Retrieval-Augmented Generation (RAG) in Real-World Applications Retrieval-augmented generation (RAG) is at the core of many large language model (LLM) applications, from companies creating headlines to developers solving problems for small businesses. Evaluating RAG With Needle in Haystack Test. Evaluating RAG systems is critical for their development and deployment. Trust in AI cannot be achieved without

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Retrieval Augmented Generation Techniques

Retrieval Augmented Generation Techniques

A comprehensive study has been conducted on advanced retrieval augmented generation techniques and algorithms, systematically organizing various approaches. This insight includes a collection of links referencing various implementations and studies mentioned in the author’s knowledge base. If you’re familiar with the RAG concept, skip to the Advanced RAG section. Retrieval Augmented Generation, known as RAG,

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