Archive - The Ai Discovery

𝗘𝘅𝗽𝗹𝗼𝗿𝗶𝗻𝗴 𝘁𝗵𝗲 𝗙𝘂𝘁𝘂𝗿𝗲 𝗼𝗳 𝗔𝗜: 𝗔 𝗦𝘂𝗿𝘃𝗲𝘆 𝗼𝗻 𝗟𝗟𝗠-𝗕𝗮𝘀𝗲𝗱 𝗔𝘂𝘁𝗼𝗻𝗼𝗺𝗼𝘂𝘀 𝗔𝗴𝗲𝗻𝘁𝘀

Discover the transformative potential of large language model-based autonomous agents in AI. From social science to engineering, explore how these…

Jul 25 •

Selvaganapathy C

GPT-4o Mini: Path to affordable intelligence

GPT_4o mini - Discover the small model with big capabilities, redefining cost-efficient intelligence.

Jul 24 •

Selvaganapathy C

How Generative AI Models are Trained

The three key stages of training Generative AI models like GPT: Generative Pre-training, Supervised fine-tuning and Reinforcement Learning with Human…

Jul 6 •

Selvaganapathy C

March 2024

What is Generative AI? Exploring Its Distinction from Traditional AI

Generative AI advanced from traditional AI, to generate original content beyond analysis and classification.

Mar 27 •

Selvaganapathy C

November 2023

Transforming Enterprise Search using Large Language Models (LLM)

LLMs are reshaping enterprise search, providing semantically precise knowledge synthesis for smarter, faster business decisions.

Nov 7, 2023 •

Selvaganapathy C

September 2023

Retrieval Augmented Generation (RAG): Bridging Domain Specific Knowledge Gaps in LLM

Retrieval Augmented Generation (RAG) enhances LLMs by fusing retrieval-based and generative techniques, addressing LLM limitations like static…

Sep 10, 2023 •

Selvaganapathy C

August 2023

A Deep-Dive into the Fundamentals of Semantic Search

Semantic search - The definition, its workings in detail, how it differ from traditional keyword based search and the use cases.

Aug 31, 2023 •

Selvaganapathy C

Understanding Vector Databases: A Comparative Guide with Traditional Databases

Vector databases, designed for AI applications, contrast traditional databases with their dynamic organization and nuanced retrieval

Aug 15, 2023 •

Selvaganapathy C

July 2023

The Impact of Relevant Context Position and Context Size on LLM Performance

Optimal performance is achieved when relevant information is at the start or end of the context, and performance decreases with longer contexts and when…

Jul 30, 2023 •

Selvaganapathy C

Demystifying Training Parameters in LLM - Quality Impact and Sizing Considerations

Training parameters are a pivotal component in the design and performance of LLMs. Choosing optimal size of training parameters depends on data…

Jul 15, 2023 •

Selvaganapathy C

Integrating Custom Knowledge Base with LLM using In-Context Learning

Integrate Large Language Models (LLMs) with your custom knowledge base using techniques - In-Context Learning, Vector DB, Embedding Model, Similarity…

Jul 5, 2023 •

Selvaganapathy C

June 2023

Token Limit, every LLM Developer should Know !

Tokens in Large Language Models (LLMs) like GPT-3 and PaLM2 are units of data read in one step, with token limits affecting model performance…

Jun 23, 2023 •

Selvaganapathy C

#nojs-banner { position: fixed; bottom: 0; left: 0; padding: 16px 16px 16px 32px; width: 100%; box-sizing: border-box; background: red; color: white; font-family: -apple-system, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; font-size: 13px; line-height: 13px; } #nojs-banner a { color: inherit; text-decoration: underline; } This site requires JavaScript to run correctly. Please turn on JavaScript or unblock scripts